{"title":"Infectious Disease","description":"","products":[{"product_id":"nos2-antibody-sc-f0177","title":"iNOS Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOS2 is a target of interest in many antibody-based workflows. Inducible nitric oxide synthase (iNOS) is one of three enzymes that produce nitric oxide (NO) from l-arginine. iNOS-derived NO is crucial in physiological processes like blood pressure regulation, wound repair, and host defense, as well as in pathological conditions such as inflammation, infection, cancer, liver cirrhosis, and diabetes. The iNOS gene, located on chromosome 17, shares sequence similarity with nNOS and eNOS. iNOS is commonly linked to malignant diseases and is stimulated by cytokines like TNF-alpha, IL-1, and IFN-gamma. Depending on the literature source, NOS2 may also be discussed as iNOS and iNOS\/NOS Type II.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following NOS2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNOS2 is commonly interpreted in the context of immunology, inflammation, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NOS2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NOS2 reflect biology rather than handling. When interpreting NOS2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NOS2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577423602009,"sku":"F0177-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577423634777,"sku":"F0177-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577423667545,"sku":"F0177-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0177-wb.gif?v=1773598182"},{"product_id":"eif2alpha-antibody-sc-f0316","title":"eIF2α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eEIF2ALPHA is a target of interest in many antibody-based workflows. eIF2 plays a central role in the rate-limiting step of mRNA translation. It binds GTP and Met-tRNAi, facilitating the transfer of Met-tRNAi to the 40S ribosomal subunit. At the end of the initiation process, GTP bound to eIF2 is hydrolyzed to GDP, and phosphorylation of eIF2 alpha effectively inhibits the formation of the eIF2. Depending on the literature source, EIF2ALPHA may also be discussed as EIF2S1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following EIF2ALPHA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eEIF2ALPHA is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for EIF2ALPHA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in EIF2ALPHA reflect biology rather than handling. When interpreting EIF2ALPHA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep EIF2ALPHA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577442410841,"sku":"F0316-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577442443609,"sku":"F0316-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577442476377,"sku":"F0316-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0316-IHC1.jpg?v=1773598326"},{"product_id":"ddx58-antibody-sc-f0360","title":"Rig-I Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eDDX58 is a target of interest in many antibody-based workflows. RIG-I-like receptors (RLRs) are crucial for detecting viral RNA, initiating innate antiviral responses. RIG-I specifically senses double-stranded RNA (dsRNA), which accumulates in infected cells but is absent in uninfected ones. RIG-I binds RNA with 5′-triphosphate ends and features two caspase recruitment domain (CARD)-like motifs at its N terminus. Depending on the literature source, DDX58 may also be discussed as Rig-I and RIG-I\/DDX58.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell junction, cell membrane, cell projection, and cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following DDX58 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eDDX58 is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell junction, cell membrane, and cell projection, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell junction, cell membrane, and cell projection across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DDX58. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in DDX58 reflect biology rather than handling. When interpreting DDX58, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep DDX58 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577446277465,"sku":"F0360-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577446310233,"sku":"F0360-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577446343001,"sku":"F0360-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0360-wb.gif?v=1773598374"},{"product_id":"prdm1-antibody-sc-f0425","title":"Blimp-1\/PRDI-BF1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePRDM1 is a target of interest in many antibody-based workflows. Blimp-1\/PRDI-BF1, is a 789-amino-acid transcriptional repressor that contains five carboxy-terminal zinc finger motifs mediating sequence-specific DNA binding. It is expressed in activated B cells and sustained in plasma cells, where it functions as a master regulator of terminal B-cell differentiation by repressing genes such as c-myc to halt proliferation and promote plasma cell identity. Depending on the literature source, PRDM1 may also be discussed as Blimp-1\/PRDI-BF1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PRDM1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePRDM1 is commonly interpreted in the context of immunology, developmental biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PRDM1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PRDM1 reflect biology rather than handling. When interpreting PRDM1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PRDM1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577451749721,"sku":"F0425-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577451782489,"sku":"F0425-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577451815257,"sku":"F0425-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0425-IF.png?v=1773598450"},{"product_id":"irf3-antibody-sc-f0521","title":"IRF3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eThe interferon regulatory factor (IRF) family of transcription factors plays a crucial role in human innate antiviral immune responses, primarily through the production of interferons (IFNs). Among them, IRF3 is recognized as a key early regulator of type I IFNs (TI-IFNs) downstream of intracellular virus sensing. Depending on the literature source, IRF3 may also be discussed as IRF-3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, nucleus, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following IRF3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIRF3 is commonly interpreted in the context of immunology, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, nucleus, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, nucleus, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IRF3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IRF3 reflect biology rather than handling. When interpreting IRF3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IRF3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577467019609,"sku":"F0521-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577467052377,"sku":"F0521-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577467085145,"sku":"F0521-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0521-IHC1.jpg?v=1773598575"},{"product_id":"tbk1-antibody-sc-f0525","title":"NAK\/TBK1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTANK-binding kinase 1 (TBK1) is a serine\/threonine kinase that plays a crucial role in various cellular functions, including innate immunity, inflammatory cytokine production, autophagy, metabolism, and cell survival. It is activated by signals such as pathogen-associated molecular patterns (PAMPs), damage-associated molecular patterns (DAMPs), inflammatory cytokines, and oncogenic kinases, which trigger the production of Type I interferons (IFN-α, IFN-β), vital for antiviral defense. Depending on the literature source, TBK1 may also be discussed as NAK\/TBK1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following TBK1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTBK1 is commonly interpreted in the context of cancer, immunology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TBK1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TBK1 reflect biology rather than handling. When interpreting TBK1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TBK1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577467281753,"sku":"F0525-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577467314521,"sku":"F0525-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577467347289,"sku":"F0525-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0525-IHC1.jpg?v=1773598578"},{"product_id":"ifit1-antibody-sc-f0542","title":"IFIT1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eInterferon-induced protein with tetratricopeptide repeats (IFIT) genes are a key subset of interferon-stimulated genes (ISGs). The human IFIT gene family includes four members: IFIT1, IFIT2, IFIT3, and IFIT5. While their expression is minimal in most cell types under normal conditions, it is significantly upregulated in response to interferon signaling, viral infections, or stimulation by pathogen-associated molecular patterns (PAMPs).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following IFIT1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIFIT1 is commonly interpreted in the context of immunology and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IFIT1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IFIT1 reflect biology rather than handling. When interpreting IFIT1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IFIT1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577469444441,"sku":"F0542-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577469477209,"sku":"F0542-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577469509977,"sku":"F0542-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0542-wb.gif?v=1773598597"},{"product_id":"stat2-antibody-sc-f0554","title":"Phospho-STAT2 (Tyr690) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePhospho-STAT2 (Tyr690) refers to the tyrosine-phosphorylated form of the STAT2 (Signal Transducer and Activator of Transcription 2) protein, specifically phosphorylated at the tyrosine residue at position 690. STAT2 is a multidomain protein, an essential transcription factor in type I IFN mediated anti-viral and anti-proliferative signaling. Depending on the literature source, STAT2 may also be discussed as Phospho-STAT2 (Tyr690) and Signal transducer and activator of transcription 2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following STAT2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eSTAT2 is commonly interpreted in the context of immunology, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for STAT2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in STAT2 reflect biology rather than handling. When interpreting STAT2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep STAT2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577470263641,"sku":"F0554-20UL","price":189.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577470296409,"sku":"F0554-100UL","price":389.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577470329177,"sku":"F0554-2X100UL","price":579.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0554-wb.gif?v=1773598615"},{"product_id":"junb-antibody-sc-f0578","title":"JunB Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eJunB, a transcription factor characterized by a basic region and leucine zipper (bZIP), is part of the Jun family, which also includes c-Jun and JunD. Members of the Jun family have the capacity to form homodimers or heterodimers with Fos and ATF proteins, creating the functional transcription factor AP-1 (activator protein 1).\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following JUNB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eJUNB is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for JUNB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in JUNB reflect biology rather than handling. When interpreting JUNB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep JUNB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577472721241,"sku":"F0578-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577472754009,"sku":"F0578-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577472786777,"sku":"F0578-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0578-IHC1.jpg?v=1773598650"},{"product_id":"nup98-antibody-sc-f0584","title":"NUP98 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNucleoporins (Nups) are proteins forming nuclear pore complexes (NPCs), which govern the transport of molecules like proteins and RNA across the nuclear envelope. Certain nucleoplasmic Nups, like Nup153, Nup98, Nup50, and sPom121, require active RNA Polymerase II (RNA Pol II) transcription for mobility. Nup98, with its FG and GLFG repeats, is of particular interest due to its involvement in haematopoietic malignancies via gene fusions.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, nuclear pore complex, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following NUP98 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNUP98 is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, nuclear pore complex, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between membrane, nuclear pore complex, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NUP98. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NUP98 reflect biology rather than handling. When interpreting NUP98, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NUP98 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577482158425,"sku":"F0584-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577482191193,"sku":"F0584-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577482223961,"sku":"F0584-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0584-IF.png?v=1773598658"},{"product_id":"usp7-antibody-sc-f0629","title":"HAUSP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHerpes virus-associated ubiquitin-specific protease (HAUSP or USP7) is a multifunctional enzyme involved in various biological processes such as genome stability, epigenetic regulation, cell cycle progression, apoptosis, viral infection, immunity, and stem cell maintenance. Its significance extends to cancer and other pathological conditions. HAUSP interacts with and stabilizes MDM2, which mediates Rb degradation through both ubiquitin-dependent and ubiquitin-independent mechanisms. Depending on the literature source, USP7 may also be discussed as HAUSP.\u003c\/p\u003e\u003cp\u003eReported cellular context includes chromosome, cytoplasm, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following USP7 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eUSP7 is commonly interpreted in the context of cancer and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans chromosome, cytoplasm, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between chromosome, cytoplasm, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for USP7. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in USP7 reflect biology rather than handling. When interpreting USP7, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep USP7 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577492873561,"sku":"F0629-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577492906329,"sku":"F0629-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577492939097,"sku":"F0629-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0629-IF.png?v=1773598718"},{"product_id":"kiaa0151-antibody-sc-f0631","title":"IKKε Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eKIAA0151 is a target of interest in many antibody-based workflows. LUBAC, or Linear Ubiquitin Chain Assembly Complex, plays a crucial role in modulating signaling pathways mediated by various immune receptors. In the TNF signaling pathway, LUBAC facilitates the recruitment and activation of TBK1 and IKKε at the TNFR1 signaling complex (TNFR1-SC). Although LUBAC activity has limited effects on TNF-induced gene activation, it is essential for preventing TNF-induced cell death. Depending on the literature source, KIAA0151 may also be discussed as IKKepsilon and IKKi\/IKKe; IKKepsilon; IKBKE; IKKE.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following KIAA0151 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eKIAA0151 is commonly interpreted in the context of immunology, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for KIAA0151. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in KIAA0151 reflect biology rather than handling. When interpreting KIAA0151, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep KIAA0151 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577493070169,"sku":"F0631-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577493102937,"sku":"F0631-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577493135705,"sku":"F0631-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0631-IF.png?v=1773598722"},{"product_id":"olfm4-antibody-sc-f0742","title":"Olfm4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eOlfactomedin 4 (OLFM4) is a neutrophil-specific granule protein expressed in a subset of human and mouse neutrophils. It belongs to a well-conserved family of glycoproteins containing the olfactomedin domain. OLFM4 is naturally expressed in neutrophils, intestinal crypts, and the prostate, and plays a critical role in innate immunity, inflammation, and carcinogenesis.\u003c\/p\u003e\u003cp\u003eReported cellular context includes mitochondrion and secreted, which can matter when signal is compared across treatments or changing cell states. Following OLFM4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eOLFM4 is commonly interpreted in the context of immunology, inflammation, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans mitochondrion and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between mitochondrion and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for OLFM4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in OLFM4 reflect biology rather than handling. When interpreting OLFM4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep OLFM4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577511223641,"sku":"F0742-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577511256409,"sku":"F0742-100UL","price":439.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577511289177,"sku":"F0742-2X100UL","price":659.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0742-IF-Mouse-Small-Intestine.jpg?v=1773598866"},{"product_id":"jund-antibody-sc-f0893","title":"JunD Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eJUND is a target of interest in many antibody-based workflows. Activating Protein-1 (AP-1) is an important transcription factor complex that controls gene expression in cells. It is made up of different dimeric complexes formed by proteins from the Jun, Fos, and ATF\/CREB families. These proteins have special structures called leucine-zipper motifs that allow them to pair up and basic DNA-binding domains that help them interact with DNA.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following JUND across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eJUND is commonly interpreted in the context of cancer and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for JUND. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in JUND reflect biology rather than handling. When interpreting JUND, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep JUND trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577557197145,"sku":"F0893-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577557229913,"sku":"F0893-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577557262681,"sku":"F0893-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0893-IF.png?v=1773599067"},{"product_id":"ccnt1-antibody-sc-f0943","title":"Cyclin T1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCCNT1 is a target of interest in many antibody-based workflows. Cyclin T1 is a key component of the P-TEFb complex, critical in regulating transcription elongation. As part of the heterodimer with CDK9, cyclin T1 helps phosphorylate RNA polymerase II (RNAPII) to transition from transcription initiation to productive elongation. This process is essential for relieving the inhibitory effects of negative elongation factors like DSIF and NELF. Depending on the literature source, CCNT1 may also be discussed as Cyclin T1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus, which can matter when signal is compared across treatments or changing cell states. Following CCNT1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCCNT1 is commonly interpreted in the context of infectious disease and epigenetics research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within nucleus relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003elinks between target behavior and transcriptional or chromatin-state changes\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CCNT1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CCNT1 reflect biology rather than handling. When interpreting CCNT1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CCNT1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577575121241,"sku":"F0943-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577575154009,"sku":"F0943-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577575186777,"sku":"F0943-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0943-wb.gif?v=1773599119"},{"product_id":"cad-antibody-sc-f0980","title":"CAD Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCAD (Carbamoyl-phosphate synthetase 2, Aspartate transcarbamoylase, and Dihydroorotase) is a multifunctional protein involved in the initial three speed-limiting steps of pyrimidine nucleotide synthesis. It consists of a hexamer made up of a 243 kDa polypeptide chain, comprising four domains: glutamine amidotransferase (GATase), carbamylphosphatesynthetase II (CPSIIase), aspartate transcarbamylase (ATCase), and dihydroorotase (DHOase). Depending on the literature source, CAD may also be discussed as BM1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following CAD across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCAD is commonly interpreted in the context of cancer, metabolism, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CAD. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CAD reflect biology rather than handling. When interpreting CAD, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CAD trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577583051097,"sku":"F0980-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577583083865,"sku":"F0980-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577583116633,"sku":"F0980-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F0980-IF.png?v=1773599152"},{"product_id":"ptx1-antibody-sc-f1024","title":"C Reactive Protein Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePTX1 is a target of interest in many antibody-based workflows. C-reactive protein (CRP) is a highly conserved, homopentameric plasma protein classified as an acute-phase inflammatory marker. During infection or inflammation, CRP levels can increase dramatically-by as much as 1,000-fold. In the presence of calcium, CRP binds to phosphocholine (PCh) and other polysaccharide structures found on microbial surfaces, initiating the classical complement cascade by interacting with C1q, thereby contributing to innate immune defense. Depending on the literature source, PTX1 may also be discussed as C Reactive Protein and CRP.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following PTX1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePTX1 is commonly interpreted in the context of immunology, inflammation, and cardiovascular research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PTX1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PTX1 reflect biology rather than handling. When interpreting PTX1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PTX1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577592193369,"sku":"F1024-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577592226137,"sku":"F1024-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577592258905,"sku":"F1024-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1024-wb.gif?v=1773599201"},{"product_id":"cd14-antibody-sc-f1070","title":"CD14 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHuman monocyte differentiation antigen CD14 is a pattern recognition receptor (PRR) that enhances innate immune responses. It is well-known as a co-receptor for various Toll-like Receptors (TLRs), facilitating the transfer of bacterial cell wall products to TLRs to initiate signaling cascades both at the cell surface and within the endosomal compartment.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, golgi apparatus, membrane, and secreted, which can matter when signal is compared across treatments or changing cell states. Following CD14 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCD14 is commonly interpreted in the context of immunology, metabolism, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, golgi apparatus, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, golgi apparatus, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CD14. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CD14 reflect biology rather than handling. When interpreting CD14, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CD14 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577603498329,"sku":"F1070-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577603531097,"sku":"F1070-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577603563865,"sku":"F1070-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1070-wb.gif?v=1773599251"},{"product_id":"notch4-antibody-sc-f1202","title":"NOTCH4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNOTCH4 is a target of interest in many antibody-based workflows. Notch proteins, encompassing Notch1-4, are a family of transmembrane receptors pivotal for developmental processes and cell fate determination. These receptors are synthesized and arranged as heterodimeric proteins, each composed of a large extracellular ligand-binding domain, a single-pass transmembrane domain, and a smaller cytoplasmic subunit known as Notch intracellular domain (NICD).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following NOTCH4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNOTCH4 is commonly interpreted in the context of cancer, cardiovascular, and developmental biology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, membrane, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, membrane, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NOTCH4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NOTCH4 reflect biology rather than handling. When interpreting NOTCH4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NOTCH4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577649537369,"sku":"F1202-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577649570137,"sku":"F1202-100UL","price":319.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577649602905,"sku":"F1202-2X100UL","price":479.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1202-wb.gif?v=1773599428"},{"product_id":"plk3-antibody-sc-f1257","title":"PLK3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003ePLK3 (Polo-like kinase 3) is a highly conserved serine\/threonine kinase belonging to the polo-like kinase family, characterized by an N-terminal catalytic kinase domain and a C-terminal polo-box domain (PBD) that mediates substrate binding and subcellular localization. Unlike PLK1, which is active during mitosis, PLK3 is predominantly expressed earlier in the cell cycle and localizes to the nucleolus when intact, becoming undetectable during mitosis. Depending on the literature source, PLK3 may also be discussed as Serine\/threonine-protein kinase PLK3 and Cytokine-inducible serine\/threonine-protein kinase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, golgi apparatus, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PLK3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePLK3 is commonly interpreted in the context of cancer, infectious disease, and cell cycle research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and golgi apparatus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and golgi apparatus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003ecell-cycle linked differences in abundance, timing, or compartmental enrichment\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PLK3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PLK3 reflect biology rather than handling. When interpreting PLK3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PLK3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577673392473,"sku":"F1257-20UL","price":139.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577673425241,"sku":"F1257-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577673458009,"sku":"F1257-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1257-wb.gif?v=1773599502"},{"product_id":"ifi16-antibody-sc-f1288","title":"IFI16 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eIFI16 is a prominent sensor of nuclear pathogenic DNA, initiating innate immune signaling and suppressing viral transcription. It is a nuclear protein belonging to the interferon-inducible HIN-200 family, characterized by an N-terminal PYRIN domain, which is involved in apoptosis, inflammation, and immune responses, and two C-terminal HIN domains, each comprising tightly packed OB-fold subdomains. Depending on the literature source, IFI16 may also be discussed as Gamma-interferon-inducible protein 16 and Ifi-16.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following IFI16 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIFI16 is commonly interpreted in the context of cancer, immunology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IFI16. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IFI16 reflect biology rather than handling. When interpreting IFI16, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IFI16 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577680961881,"sku":"F1288-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577680994649,"sku":"F1288-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577681027417,"sku":"F1288-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1288-wb.gif?v=1773599547"},{"product_id":"ago3-antibody-sc-f1322","title":"Argonaute 3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAGO3 is a target of interest in many antibody-based workflows. Argonaute proteins are part of a highly conserved family that plays a key role in gene silencing through pathways such as RNA interference (RNAi). This family is divided into AGO and PIWI proteins, both of which bind small RNA guides ranging from 21 to 35 nucleotides in length, which then direct the silencing of specific genes. Depending on the literature source, AGO3 may also be discussed as Argonaute 3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following AGO3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eAGO3 is commonly interpreted in the context of developmental biology and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for AGO3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in AGO3 reflect biology rather than handling. When interpreting AGO3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep AGO3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577688858969,"sku":"F1322-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577688891737,"sku":"F1322-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577688924505,"sku":"F1322-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1322-wb.gif?v=1773599590"},{"product_id":"mavs-antibody-sc-f1399","title":"MAVS Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMAVS is an adapter protein involved in RIG-I-like receptor (RLR) signaling in mitochondria, peroxisomes, and mitochondria-associated ER membranes (MAMs), essential for innate immunity to RNA viruses. MAVS is crucial for RLR signaling-regulated metabolic reprogramming. Peroxisomal MAVS selectively induces type III IFN expression via IRF1, while mitochondrial MAVS induces type I IFN and ISGs expression.\u003c\/p\u003e\u003cp\u003eReported cellular context includes membrane, mitochondrion, mitochondrion outer membrane, and peroxisome, which can matter when signal is compared across treatments or changing cell states. Following MAVS across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eMAVS is commonly interpreted in the context of metabolism, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans membrane, mitochondrion, and mitochondrion outer membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between membrane, mitochondrion, and mitochondrion outer membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for MAVS. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in MAVS reflect biology rather than handling. When interpreting MAVS, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep MAVS trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577722380633,"sku":"F1399-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577722413401,"sku":"F1399-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577722446169,"sku":"F1399-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1399-IHC1.jpg?v=1773599700"},{"product_id":"atg4b-antibody-sc-f1446","title":"Atg4B Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eATG4B is a member of the ATG4 family of cysteine proteases, which plays a crucial role in regulating autophagy by mediating the processing and deconjugation of ATG8 proteins during autophagosome formation. In its inactive state, ATG4B conceals its catalytic site through structural domains, which undergo a conformational change upon binding to ATG8, thereby exposing the active site and enabling substrate cleavage.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoplasmic vesicle, endoplasmic reticulum, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following ATG4B across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eATG4B is commonly interpreted in the context of cancer, infectious disease, and autophagy research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoplasmic vesicle, and endoplasmic reticulum, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoplasmic vesicle, and endoplasmic reticulum across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003einterpretation alongside flux, cargo handling, or lysosomal context\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ATG4B. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ATG4B reflect biology rather than handling. When interpreting ATG4B, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ATG4B trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577747841369,"sku":"F1446-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577747874137,"sku":"F1446-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577747906905,"sku":"F1446-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1446-wb.gif?v=1773599760"},{"product_id":"tmem49-vmp1-antibody-sc-f1488","title":"TMEM49\/VMP1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTMEM49\/VMP1 is a target of interest in many antibody-based workflows. Vacuole membrane protein 1 (VMP1), also known as TMEM49, is an integral membrane protein with seven transmembrane domains and 406 amino acids, essential for autophagy and ER-lipid transport. Structurally, it interacts with autophagy factors like Beclin1 and TMEM41B to facilitate autophagosome formation, lipid transport from the ER, and fusion with lysosomes. Depending on the literature source, TMEM49\/VMP1 may also be discussed as TMEM49\/VMP1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, endoplasmic reticulum, membrane, and vacuole, which can matter when signal is compared across treatments or changing cell states. Following TMEM49\/VMP1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTMEM49\/VMP1 is commonly interpreted in the context of metabolism, infectious disease, and autophagy research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, endoplasmic reticulum, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, endoplasmic reticulum, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003einterpretation alongside flux, cargo handling, or lysosomal context\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TMEM49\/VMP1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TMEM49\/VMP1 reflect biology rather than handling. When interpreting TMEM49\/VMP1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TMEM49\/VMP1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577761898841,"sku":"F1488-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577761931609,"sku":"F1488-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577761964377,"sku":"F1488-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1488-wb.gif?v=1773599810"},{"product_id":"pc-antibody-sc-f1491","title":"PC Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProprotein Convertases (PCs) are a family of nine serine proteases responsible for the activation of precursor proteins through specific proteolytic cleavage, enabling various biological processes. These enzymes, including furin, PC1\/3, PC2, PC5\/6, and PCSK9, have a common structure comprising a signal peptide for secretion, an auto-cleaved prodomain, a catalytic domain with an Asp-His-Ser triad, a P-domain for pH\/calcium stability, and a C-terminal domain for membrane interaction. Depending on the literature source, PC may also be discussed as PAX5.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasmic vesicle and secreted, which can matter when signal is compared across treatments or changing cell states. Following PC across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePC is commonly interpreted in the context of cancer, metabolism, and endocrinology research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasmic vesicle and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasmic vesicle and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003eresponses to hormone-dependent signaling or endocrine feedback context\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PC. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PC reflect biology rather than handling. When interpreting PC, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PC trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577763930457,"sku":"F1491-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577763963225,"sku":"F1491-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577763995993,"sku":"F1491-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1491-IF.png?v=1773599813"},{"product_id":"sintbad-antibody-sc-f1501","title":"SINTBAD Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eSINTBAD is an adaptor protein associated with TBK1 and IKKε, kinases crucial for the innate immune response. A central region of SINTBAD, known as the TBK binding domain (TBD), can act as a dominant negative protein, disrupting IRF-3 activation. Additionally, SINTBAD and NAP1 can interact with NDP52, a protein that binds to poly-ubiquitinated proteins found on bacterial surfaces, thereby initiating autophagy. Depending on the literature source, SINTBAD may also be discussed as N4N12.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, which can matter when signal is compared across treatments or changing cell states. Following SINTBAD across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eSINTBAD is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasm relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for SINTBAD. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in SINTBAD reflect biology rather than handling. When interpreting SINTBAD, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep SINTBAD trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577767534937,"sku":"F1501-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577767567705,"sku":"F1501-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577767600473,"sku":"F1501-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1501-wb.gif?v=1773599827"},{"product_id":"ace2-antibody-sc-f1542","title":"ACE2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eAngiotensin-converting enzyme 2 (ACE2) is a type I integral membrane protein that serves as a critical regulator of the renin-angiotensin system (RAS), playing a key role in blood pressure regulation and cardiovascular function. ACE2 was identified as the functional receptor for SARS-CoV and SARS-CoV-2, the viruses responsible for severe acute respiratory syndrome (SARS) and COVID-19, respectively.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, cytoplasm, and membrane, which can matter when signal is compared across treatments or changing cell states. Following ACE2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eACE2 is commonly interpreted in the context of cardiovascular, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and cytoplasm, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and cytoplasm across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ACE2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ACE2 reflect biology rather than handling. When interpreting ACE2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ACE2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577771532633,"sku":"F1542-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577771565401,"sku":"F1542-100UL","price":399.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577771598169,"sku":"F1542-2X100UL","price":599.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1542-IHC1.jpg?v=1773599852"},{"product_id":"g3bp1-antibody-sc-f1559","title":"G3BP1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eRas-GTPase-activating protein (SH3 domain)-binding protein (G3BP) is an RNA-binding protein that plays a crucial role in the formation and regulation of stress granules (SGs). It binds to the SH3 domain of the Ras-GTPase activating protein (GAP) in serum-stimulated cells. The G3BP family includes three homologous proteins: G3BP1, G3BP2a, and G3BP2b. Depending on the literature source, G3BP1 may also be discussed as G3BP.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following G3BP1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eG3BP1 is commonly interpreted in the context of neuroscience, developmental biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for G3BP1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in G3BP1 reflect biology rather than handling. When interpreting G3BP1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep G3BP1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577777168729,"sku":"F1559-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577777201497,"sku":"F1559-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577777234265,"sku":"F1559-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1559-IF.png?v=1773599875"},{"product_id":"pkr-antibody-sc-f1597","title":"Phospho-PKR (Thr446) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProtein Kinase R (PKR) is a pivotal serine\/threonine kinase that plays a crucial role in the cellular response to stress and viral infections. It plays a major role in central cellular processes such as mRNA translation, transcriptional control, regulation of apoptosis, and proliferation. It is initially kept inactive through interactions with regulatory domains or binding partners. Depending on the literature source, PKR may also be discussed as Phospho-PKR (Thr446) and Phospho PKR (Thr 446).\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PKR across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePKR is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003edifferences between total target abundance and site-specific regulation when modified forms are compared\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PKR. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PKR reflect biology rather than handling. When interpreting PKR, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PKR trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577789456729,"sku":"F1597-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577789489497,"sku":"F1597-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577789522265,"sku":"F1597-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1597-wb.gif?v=1773599919"},{"product_id":"mpo-antibody-sc-f1614","title":"Myeloperoxidase Heavy Chain Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMyeloperoxidase (MPO) is a heme-containing enzyme predominantly expressed in neutrophils, where it plays a vital role in antimicrobial defence by catalyzing the production of hypochlorous acid (HOCl) from hydrogen peroxide and chloride ions. MPO is stored in azurophilic granules within neutrophils and is released upon cell activation to help kill pathogens. Depending on the literature source, MPO may also be discussed as Myeloperoxidase Heavy Chain and Myeloperoxidase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes lysosome, which can matter when signal is compared across treatments or changing cell states. Following MPO across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eMPO is commonly interpreted in the context of immunology and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans lysosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within lysosome relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for MPO. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in MPO reflect biology rather than handling. When interpreting MPO, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep MPO trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577794568537,"sku":"F1614-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577794601305,"sku":"F1614-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577794634073,"sku":"F1614-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1614-IHC1.jpg?v=1773599940"},{"product_id":"cybb-antibody-sc-f1615","title":"NOX2\/gp91phox Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCYBB is a target of interest in many antibody-based workflows. NOX2, also known as gp91phox, is a membrane-bound enzyme, the prototypical member of the NADPH oxidase NOX superfamily and produces superoxide (O2•−), a key reactive oxygen species (ROS) that is essential in innate and adaptive immunity. It serves as the catalytic core of the NADPH oxidase complex, predominantly found in phagocytic cells like neutrophils and macrophages. Depending on the literature source, CYBB may also be discussed as NOX2\/gp91phox and gp91-phox.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, which can matter when signal is compared across treatments or changing cell states. Following CYBB across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCYBB is commonly interpreted in the context of immunology, infectious disease, and oxidative stress research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cell membrane relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eredox-associated shifts that may alter abundance, localization, or pathway coupling\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CYBB. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CYBB reflect biology rather than handling. When interpreting CYBB, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CYBB trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577795748185,"sku":"F1615-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577795780953,"sku":"F1615-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577795813721,"sku":"F1615-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1615-wb.gif?v=1773599941"},{"product_id":"mapk1-antibody-sc-f1637","title":"ERK2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eMAPK1 is a target of interest in many antibody-based workflows. Extracellular signal-regulated kinase 2 (ERK2) is a crucial serine\/threonine protein kinase and a member of the mitogen-activated protein kinase (MAPK) family. It plays a key role in transmitting extracellular signals to intracellular targets and is involved in mitosis, meiosis, and postmitotic functions. Its pathway is triggered by a range of stimuli, such as growth factors, cytokines, and viral infections. Depending on the literature source, MAPK1 may also be discussed as ERK2 and MAP Kinase 2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, nucleus, and microtubule, which can matter when signal is compared across treatments or changing cell states. Following MAPK1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eMAPK1 is commonly interpreted in the context of infectious disease and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for MAPK1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in MAPK1 reflect biology rather than handling. When interpreting MAPK1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep MAPK1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577805447513,"sku":"F1637-20UL","price":95.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577805480281,"sku":"F1637-100UL","price":289.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577805513049,"sku":"F1637-2X100UL","price":459.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1637-IHC1.jpg?v=1773599975"},{"product_id":"c3-antibody-sc-f1700","title":"C3 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eC3 is the central component of the complement system, produced mainly by the liver and present in high concentrations in blood, tissues, and intracellularly. It plays a crucial role in immunity by enhancing bacterial clearance, regulating CD4+ and CD8+ T-cell responses during viral infections, and promoting B-cell responses. Depending on the literature source, C3 may also be discussed as C3b and Complement C3.\u003c\/p\u003e\u003cp\u003eReported cellular context includes secreted, which can matter when signal is compared across treatments or changing cell states. Following C3 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eC3 is commonly interpreted in the context of immunology and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within secreted relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for C3. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in C3 reflect biology rather than handling. When interpreting C3, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep C3 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577824092505,"sku":"F1700-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577824125273,"sku":"F1700-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577824158041,"sku":"F1700-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1700-IHC1.jpg?v=1773600044"},{"product_id":"ticam-1-antibody-sc-f1867","title":"TICAM-1(TRIF) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTICAM-1 (TIR-domain-containing adapter molecule 1), also known as TRIF, is an adaptor protein involved in innate immune signaling. It contains a Toll\/Interleukin-1 receptor (TIR) domain, which is essential for its interactions with Toll-like receptors (TLRs) such as TLR3 and TLR4, and a N-terminal region that recruits kinases like TBK1 and IKKi. Depending on the literature source, TICAM-1 may also be discussed as TICAM-1(TRIF) and TRIF.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoplasmic vesicle, and mitochondrion, which can matter when signal is compared across treatments or changing cell states. Following TICAM-1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTICAM-1 is commonly interpreted in the context of immunology, inflammation, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoplasmic vesicle, and mitochondrion, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoplasmic vesicle, and mitochondrion across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TICAM-1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TICAM-1 reflect biology rather than handling. When interpreting TICAM-1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TICAM-1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577831792985,"sku":"F1867-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577831825753,"sku":"F1867-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577831858521,"sku":"F1867-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F1867-IF.png?v=1773600073"},{"product_id":"laminin-r-antibody-sc-f2036","title":"Laminin Receptor Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eLAMININ-R is a target of interest in many antibody-based workflows. The 67 kDa high-affinity laminin receptor (67LR) is a non-integrin cell surface receptor primarily located in lipid rafts of the cell membrane, derived from the dimerization of the 37 kDa precursor (37LRP). While its main function is mediating cell adhesion, migration, proliferation, and survival by binding to laminin, 67LR also serves as a receptor for viruses, bacteria, prions, and epigallocatechin gallate (EGCG). Depending on the literature source, LAMININ-R may also be discussed as Laminin Receptor and 67kDa Laminin Receptor.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cytoplasm, membrane, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following LAMININ-R across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eLAMININ-R is commonly interpreted in the context of cancer and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cytoplasm, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cytoplasm, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for LAMININ-R. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in LAMININ-R reflect biology rather than handling. When interpreting LAMININ-R, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep LAMININ-R trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577848668505,"sku":"F2036-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577848701273,"sku":"F2036-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577848734041,"sku":"F2036-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2036-IF.png?v=1773600126"},{"product_id":"cd21-antibody-sc-f2098","title":"CD21 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCD21 (Complement receptor type 2) also known as (CR2) , is a surface glycoprotein primarily expressed on mature B cells and follicular dendritic cells, playing a key role in bridging innate and adaptive immunity. Structurally, it consists of 15-16 short consensus repeats (SCRs), with the N-terminal SCR1 and SCR2 mediating interactions with complement components like C3d, iC3b, and C3dg, as well as the Epstein-Barr virus (EBV) glycoprotein gp350\/220.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane and membrane, which can matter when signal is compared across treatments or changing cell states. Following CD21 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCD21 is commonly interpreted in the context of immunology, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CD21. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CD21 reflect biology rather than handling. When interpreting CD21, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CD21 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577861153113,"sku":"F2098-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577861185881,"sku":"F2098-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577861218649,"sku":"F2098-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2098-IF.png?v=1773600170"},{"product_id":"dynll1-pin-antibody-sc-f2116","title":"DYNLL1\/PIN Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eDYNLL1\/PIN is a target of interest in many antibody-based workflows. DYNLL1 (dynein light chain 1, also known as LC8-1 or PIN) is a small, highly conserved 10 kDa protein that regulates multiple neuronal functions. It is involved in the regulation of neuron proteins implicated in glaucomatous retinal ganglion cell (RGC) death, such as nitric oxide (NO) synthases, the pro-apoptotic protein Bim, and the dynein intermediate chain. Depending on the literature source, DYNLL1\/PIN may also be discussed as DYNLL1\/PIN.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytoskeleton, microtubule organizing center, and centrosome, which can matter when signal is compared across treatments or changing cell states. Following DYNLL1\/PIN across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eDYNLL1\/PIN is commonly interpreted in the context of neuroscience and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytoskeleton, and microtubule organizing center, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytoskeleton, and microtubule organizing center across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for DYNLL1\/PIN. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in DYNLL1\/PIN reflect biology rather than handling. When interpreting DYNLL1\/PIN, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep DYNLL1\/PIN trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577866592601,"sku":"F2116-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577866625369,"sku":"F2116-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577866658137,"sku":"F2116-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2116-IF.png?v=1773600191"},{"product_id":"tlr4-antibody-sc-f2122","title":"TLR4 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eToll-like receptor 4 (TLR4) is part of the pattern recognition receptor (PRR) family, which are highly conserved receptors that detect pathogen-associated molecular patterns (PAMPs). This makes them essential for the initial defense against infections. TLR4 is present on the cell surface of both hematopoietic and non-hematopoietic cells, including endothelial cells, cardiac myocytes, and cells within the central nervous system (CNS). Depending on the literature source, TLR4 may also be discussed as Toll-like Receptor 4.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, cell projection, endosome, and membrane, which can matter when signal is compared across treatments or changing cell states. Following TLR4 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTLR4 is commonly interpreted in the context of inflammation, cardiovascular, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, cell projection, and endosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, cell projection, and endosome across matched conditions\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003echanges linked to vascular, contractile, or hemodynamic cell-state cues\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TLR4. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TLR4 reflect biology rather than handling. When interpreting TLR4, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TLR4 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577870000473,"sku":"F2122-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577870033241,"sku":"F2122-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577870066009,"sku":"F2122-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2122-IF.png?v=1773600200"},{"product_id":"transportin-1-mip-antibody-sc-f2128","title":"Transportin 1\/MIP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTransportin 1\/MIP (Trn1), also known as karyopherin-β2 (Kapβ2), is a nuclear import receptor widely expressed across tissues, including neurons and immune cells, facilitating the transport of proteins with M9 or PY-motifs into the nucleus. Structurally, it features 20 HEAT repeats forming a superhelical architecture, with its N-terminal domain binding cargo and the C-terminal domain interacting with nucleoporins at the nuclear pore complex.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following Transportin 1\/MIP across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTransportin 1\/MIP is commonly interpreted in the context of neuroscience and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003ecompartment-specific patterns relevant to neuronal polarity, transport, or synaptic context\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for Transportin 1\/MIP. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in Transportin 1\/MIP reflect biology rather than handling. When interpreting Transportin 1\/MIP, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep Transportin 1\/MIP trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577870098777,"sku":"F2128-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577870131545,"sku":"F2128-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577870164313,"sku":"F2128-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2128-IF.png?v=1773600202"},{"product_id":"il18-antibody-sc-f2146","title":"IL-18 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eIL18 is a target of interest in many antibody-based workflows. Interleukin-18 (IL-18) is a pro-inflammatory cytokine from the IL-1 family that plays a vital role in innate and adaptive immune responses. It stimulates the production of interferon-gamma (IFN-γ) by activating T helper 1 (Th1) cells, natural killer (NK) cells, and macrophages, especially in the presence of IL-12. Depending on the literature source, IL18 may also be discussed as IL-18.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and secreted, which can matter when signal is compared across treatments or changing cell states. Following IL18 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eIL18 is commonly interpreted in the context of immunology, inflammation, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses associated with cytokine exposure, inflammatory tone, or tissue stress\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for IL18. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in IL18 reflect biology rather than handling. When interpreting IL18, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep IL18 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577872261465,"sku":"F2146-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577872294233,"sku":"F2146-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577872327001,"sku":"F2146-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2146-IHC1.jpg?v=1773600213"},{"product_id":"ythdf2-antibody-sc-f2153","title":"YTHDF2 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eYTHDF2 is a crucial m6A \"reader\" protein that plays a significant role in various biological processes by recognizing and regulating m6A-modified RNA. It is involved in the dynamic and reversible post-transcriptional modification of RNA, affecting the stability, processing, and function of mRNA. YTHDF2 specifically targets m6A sites to modulate the degradation of RNAs, influencing processes such as hematopoietic stem cell self-renewal, pluripotent stem cell differentiation, adipogenesis, and viral infections.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm, cytosol, and nucleus, which can matter when signal is compared across treatments or changing cell states. Following YTHDF2 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eYTHDF2 is commonly interpreted in the context of cancer, stem cell biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm, cytosol, and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm, cytosol, and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estate transitions between self-renewal, priming, and differentiation\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for YTHDF2. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in YTHDF2 reflect biology rather than handling. When interpreting YTHDF2, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep YTHDF2 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577874260313,"sku":"F2153-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577874293081,"sku":"F2153-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577874325849,"sku":"F2153-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2153-wb.gif?v=1773600221"},{"product_id":"trim25-efp-antibody-sc-f2162","title":"TRIM25\/EFP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eTRIM25\/EFP is a target of interest in many antibody-based workflows. TRIM25, a member of the tripartite motif (TRIM) family of E3 ubiquitin ligases, is pivotal in regulating innate immune responses, particularly in antiviral defense. It has RING, B-box, and coiled-coil domains that facilitate its E3 ligase activity and interaction with various substrates. TRIM25 activates the RIG-I-like receptor pathway by mediating the K63-linked polyubiquitination of RIG-I, which enhances RIG-I's ability to initiate downstream antiviral signaling and the production of type I interferons. Depending on the literature source, TRIM25\/EFP may also be discussed as TRIM25\/EFP and TRIM25.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following TRIM25\/EFP across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eTRIM25\/EFP is commonly interpreted in the context of immunology, infectious disease, and cell signaling research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003esignal-dependent shifts after ligand, inhibitor, or growth-factor perturbation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for TRIM25\/EFP. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in TRIM25\/EFP reflect biology rather than handling. When interpreting TRIM25\/EFP, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep TRIM25\/EFP trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577878126937,"sku":"F2162-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577878159705,"sku":"F2162-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577878192473,"sku":"F2162-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2162-IF.png?v=1773600236"},{"product_id":"npc1-antibody-sc-f2166","title":"Niemann Pick C1 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNiemann-Pick C1 (NPC1) is a large, 165 kDa, multi-transmembrane protein primarily localized in lysosomal membranes. It plays a crucial role in cellular cholesterol homeostasis by promoting the transport of cholesterol out of lysosomes and late endosomes. NPC1 is an essential intracellular receptor for several viral infections, including filoviruses (e. g., Ebola virus), quasi-enveloped variants of hepatitis A virus, hepatitis E virus, and reovirus. Depending on the literature source, NPC1 may also be discussed as Niemann Pick C1.\u003c\/p\u003e\u003cp\u003eReported cellular context includes endosome and lysosom, which can matter when signal is compared across treatments or changing cell states. Following NPC1 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eNPC1 is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans endosome and lysosom, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between endosome and lysosom across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for NPC1. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in NPC1 reflect biology rather than handling. When interpreting NPC1, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep NPC1 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577878585689,"sku":"F2166-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577878618457,"sku":"F2166-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577878651225,"sku":"F2166-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2166-IHC1.jpg?v=1773600241"},{"product_id":"cd36-antibody-sc-f2168","title":"CD36 Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCD36 is a heavily glycosylated integral membrane protein and scavenger receptor widely expressed in various tissues, including adipocytes, myocytes, enterocytes, immune cells, and endothelial cells. Structurally, it features two transmembrane domains, two short intracellular domains at both termini (short cytoplasmic tails), and a large extracellular domain containing a conserved hydrophobic pocket and multiple ligand-binding sites. Depending on the literature source, CD36 may also be discussed as GP3B and GP4.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, golgi apparatus, and membrane, which can matter when signal is compared across treatments or changing cell states. Following CD36 across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCD36 is commonly interpreted in the context of immunology, metabolism, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, golgi apparatus, and membrane, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, golgi apparatus, and membrane across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003eresponses linked to nutrient status, mitochondrial state, or metabolic rewiring\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CD36. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CD36 reflect biology rather than handling. When interpreting CD36, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CD36 trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577879961945,"sku":"F2168-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577879994713,"sku":"F2168-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577880027481,"sku":"F2168-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}]},{"product_id":"cd8alpha-antibody-sc-f2204","title":"CD8α Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eCD8ALPHA is a target of interest in many antibody-based workflows. CD8α (Cluster of Differentiation 8 alpha) is a transmembrane glycoprotein encoded by the CD8A gene and functions as a co-receptor in immune responses. Structurally, CD8α has three main regions: N-terminal extracellular ectodomain: Contains a single immunoglobulin variable (IgV)-like domain and a proline-rich, flexible hinge or stalk region, Transmembrane helix, Cytoplasmic region and forms homodimers (CD8αα) or heterodimers with CD8β (CD8αβ), containing an extracellular immunoglobulin-like domain, a transmembrane region, and a cytoplasmic tail that associates with the Src-family kinase Lck to facilitate T cell receptor (TCR) signaling. Depending on the literature source, CD8ALPHA may also be discussed as CD8a and Lyt-2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cell membrane, membrane, and secreted, which can matter when signal is compared across treatments or changing cell states. Following CD8ALPHA across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eCD8ALPHA is commonly interpreted in the context of immunology, developmental biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cell membrane, membrane, and secreted, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cell membrane, membrane, and secreted across matched conditions\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for CD8ALPHA. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in CD8ALPHA reflect biology rather than handling. When interpreting CD8ALPHA, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep CD8ALPHA trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577892020569,"sku":"F2204-20UL","price":169.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577892053337,"sku":"F2204-100UL","price":379.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577892086105,"sku":"F2204-2X100UL","price":569.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2204-wb.gif?v=1773600274"},{"product_id":"wtap-antibody-sc-f2216","title":"WTAP Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eWilms’ tumor 1-associating protein (WTAP), a 44 kDa protein encoded on human chromosomal region 6q25. 3, is a critical regulator of diverse biological processes through its role in N6-methyladenosine (m6A) modification, pre-mRNA splicing, and other cellular pathways. WTAP localizes to both the nucleus and cytoplasm and forms a key component of the m6A methyltransferase complex (MTC) alongside METTL3, METTL14, VIRMA, CBLL1, ZC3H13, and RBM15\/15B.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following WTAP across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eWTAP is commonly interpreted in the context of cancer, developmental biology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003estage-dependent patterns during differentiation, morphogenesis, or lineage commitment\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for WTAP. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in WTAP reflect biology rather than handling. When interpreting WTAP, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep WTAP trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577892577625,"sku":"F2216-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577892610393,"sku":"F2216-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577892643161,"sku":"F2216-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2216-IF.png?v=1773600278"},{"product_id":"hnrnpc-antibody-sc-f2233","title":"hnRNP C1 + C2\/HNRNPC Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eHeterogeneous nuclear ribonucleoproteins C1 and C2 (hnRNP C1\/C2) are RNA-binding proteins encoded by the HNRNPC gene, differing by 13 amino acids due to alternative splicing. These proteins form heterotetramers consisting of three C1 molecules and one C2 molecule, utilizing an RNA recognition motif and a leucine zipper-like domain to bind RNA. hnRNP C1\/C2 are involved in critical cellular processes such as mRNA splicing, stability, transport, and protein translation. Depending on the literature source, HNRNPC may also be discussed as hnRNP C1 + C2\/HNRNPC and hnRNP C1\/C2.\u003c\/p\u003e\u003cp\u003eReported cellular context includes nucleus and spliceosome, which can matter when signal is compared across treatments or changing cell states. Following HNRNPC across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eHNRNPC is commonly interpreted in the context of infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans nucleus and spliceosome, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between nucleus and spliceosome across matched conditions\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003cli\u003etime-matched comparisons so changes reflect biology rather than handling or sampling drift\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for HNRNPC. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in HNRNPC reflect biology rather than handling. When interpreting HNRNPC, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep HNRNPC trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577900769625,"sku":"F2233-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577900802393,"sku":"F2233-100UL","price":329.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577900835161,"sku":"F2233-2X100UL","price":489.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2233-IF.png?v=1773600293"},{"product_id":"pkr-antibody-sc-f2372","title":"Phospho-PKR (Thr451) Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eProtein kinase R (PKR) is an interferon-induced serine\/threonine kinase that plays a central role in innate antiviral defense and regulation of cell growth. Structurally, PKR contains two tandem dsRNA-binding motifs at its N-terminus, a flexible linker, and a C-terminal kinase domain that adopts a bilobal fold. Depending on the literature source, PKR may also be discussed as Phospho-PKR (Thr451) and PRKR.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasm and nucleus, which can matter when signal is compared across treatments or changing cell states. Following PKR across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003ePKR is commonly interpreted in the context of cancer, immunology, and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasm and nucleus, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eapparent redistribution between cytoplasm and nucleus across matched conditions\u003c\/li\u003e\n\u003cli\u003echanges associated with proliferative state, oncogenic signaling, or treatment response\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for PKR. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in PKR reflect biology rather than handling. When interpreting PKR, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep PKR trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577925935449,"sku":"F2372-20UL","price":199.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577925968217,"sku":"F2372-100UL","price":489.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577926000985,"sku":"F2372-2X100UL","price":729.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2372-wb.gif?v=1773600348"},{"product_id":"elane-antibody-sc-f2430","title":"Neutrophil Elastase Antibody","description":"\u003ch2\u003eAbout the Target\u003c\/h2\u003e\u003cp\u003eNeutrophil elastase is a serine protease encoded by the ELANE gene and stored in the azurophilic granules of neutrophils, playing a key role in innate immunity by degrading extracellular matrix proteins and bacterial virulence factors. Structurally, it is a trypsin-type serine protease with a catalytic triad of histidine, aspartate, and serine, synthesized as a proenzyme and activated through post-translational modifications. Depending on the literature source, ELANE may also be discussed as Neutrophil Elastase.\u003c\/p\u003e\u003cp\u003eReported cellular context includes cytoplasmic vesicle, which can matter when signal is compared across treatments or changing cell states. Following ELANE across matched perturbations can help separate abundance effects from shifts in localization, complex assembly, or pathway state.\u003c\/p\u003e\u003ch2\u003eResearch Context\u003c\/h2\u003e\u003cp\u003eELANE is commonly interpreted in the context of immunology and infectious disease research, and readouts are often stronger when a study separates expression changes from compartment-level redistribution. When reported signal spans cytoplasmic vesicle, a defined reference condition can make comparisons more interpretable across perturbations, passages, or replicate sets.\u003c\/p\u003e\u003cp\u003eConsider these angles when interpreting target-level changes:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003esignal enrichment within cytoplasmic vesicle relative to the broader cellular background\u003c\/li\u003e\n\u003cli\u003econtext differences tied to immune-cell state, activation, or lineage composition\u003c\/li\u003e\n\u003cli\u003ehost-response changes during infection or pathogen-associated stimulation\u003c\/li\u003e\n\u003cli\u003eco-patterning with orthogonal markers and control conditions that clarify pathway state\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eVariant Considerations\u003c\/h2\u003e\u003cp\u003eIf your project spans exploratory questions, the regular version offers a balanced option for establishing baseline signal behavior for ELANE. This can help when protocols evolve over time and the goal is to compare experiments using a stable reference workflow.\u003c\/p\u003e\u003cp\u003eStandardize sampling time, control choice, and downstream analysis thresholds so apparent differences in ELANE reflect biology rather than handling. When interpreting ELANE, it is often useful to decide early whether the main question is overall abundance, compartmental enrichment, or context-dependent redistribution.\u003c\/p\u003e\u003cp\u003eFor multi-run studies, a shared reference condition can keep ELANE trends easier to compare across datasets. That kind of consistency is especially helpful when follow-up work expands to new perturbations, model systems, or longitudinal collections.\u003c\/p\u003e","brand":"Selleck Chemicals","offers":[{"title":"20 µl","offer_id":57577941631321,"sku":"F2430-20UL","price":149.0,"currency_code":"EUR","in_stock":true},{"title":"100 µl","offer_id":57577941664089,"sku":"F2430-100UL","price":359.0,"currency_code":"EUR","in_stock":true},{"title":"2 × 100 µl","offer_id":57577941696857,"sku":"F2430-2X100UL","price":539.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0923\/1011\/0553\/files\/F2430-IF.png?v=1773600393"}],"url":"https:\/\/absource-diagnostics.myshopify.com\/collections\/infectious-disease.oembed?page=2","provider":"Absource Diagnostics","version":"1.0","type":"link"}