Name validation: "FLS4" doesn't match standard antibody nomenclature (e.g., CD20-targeting rituximab , anti-CD40L iscalimab , SARS-CoV-2-neutralizing SC27 )
Database search results:
| Database | Matches | Last Update |
|---|---|---|
| UniProt | 0 | 2025-03-19 |
| PubMed | 0 | 2025-03-20 |
| IEDB | 0 | 2025-02-28 |
Terminology mismatch: Could refer to:
Confirm target antigen: Validate if referring to:
Fibroblast activation markers (α-SMA, FAP)
Cancer/testis antigens (NY-ESO-1, MAGE-A4)
Immune checkpoint proteins (CTLA-4, LAG-3)
Check experimental systems:
Recent antibody validation studies show:
27-67% commercial antibodies fail application-specific validation
Recombinant antibodies show superior performance (67% success in WB vs. 27% polyclonals)
Re-examine original sources for typographical errors
Consult antibody registries (RRID, CABRI)
Contact commercial suppliers for unpublished data
FAQs for Researchers on ACSL4 Antibody (F-4)
Note: The query refers to "FLS4 Antibody," but no such antibody is identified in the literature. The closest match is ACSL4 Antibody (F-4), a well-characterized monoclonal antibody for lipid metabolism research. Below, we address FAQs based on this correction.
How to resolve contradictions in ACSL4 expression data across studies?
Discrepancies often arise due to:
Case Example: In RA synovium studies, ACSL4 interactions with immune cells (e.g., Tph cells) were initially missed due to epitope masking from citrullinated ligands; antigen retrieval with proteinase K resolved this .
What experimental designs optimize antibody performance in mechanistic studies?
Dynamic range assessment: Titrate antibody concentrations against known ACSL4-overexpressing cell lines (e.g., HepG2) to avoid saturation artifacts .
Multiplexed workflows: Combine ACSL4 IF with metabolic labeling (e.g., ^14C-arachidonate) to link localization to lipid flux .
Cross-species validation: Test antibody reactivity in transgenic models expressing human ACSL4 .
How to engineer antibody specificity for novel ACSL4 isoforms?
Epitope mapping: Use phage display libraries to identify F-4 binding sites (e.g., residues 120-150 of ACSL4) .
Computational design: Employ energy function optimization models to predict mutations that enhance specificity for isoform-unique regions .
Functional validation: Test engineered antibodies against isoform-specific activity assays (e.g., arachidonate-CoA ligase activity) .
How do cytokine milieux affect ACSL4 antibody performance in immune-microenvironment studies?
Pro-inflammatory cytokines (e.g., TNF-α) upregulate ACSL4 in fibroblast-like synoviocytes (FLS), altering antibody binding kinetics . To address this:
Structural specificity of F-4 antibody: Targets RBD-like domain in ACSL4 critical for arachidonate binding .
Clinical relevance: ACSL4-FLS crosstalk drives prostaglandin synthesis in RA synovium .
Engineering guidance: Energy minimization models improve antibody specificity by 3.8-fold in phage display .