AT2S1 Antibody
Description
Definition and Function of AT1R Antibodies
AT1R antibodies are autoantibodies or therapeutic antibodies targeting the angiotensin II type 1 receptor, a key component of the renin-angiotensin system. These antibodies are implicated in pathologies such as systemic sclerosis (SSc), antibody-mediated rejection (AMR) in transplants, and cardiovascular inflammation .
Key Properties:
Antibody Specificity and Cross-Reactivity
Commercially available AT1R antibodies vary in specificity and cross-reactivity. Below is a comparison of key antibodies from published studies:
Critical Findings:
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Non-specific binding: Multiple antibodies (e.g., sc-1173, sc-579) show identical immunoreactivity in wild-type and AT1A knockout mice, suggesting off-target binding .
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Tissue variability: Antibody performance differs significantly across liver, kidney, and hypothalamus, complicating interpretation .
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Functional activity: Some antibodies (e.g., in SSc patients) directly activate AT1R, enhancing TGF-β signaling and fibrosis .
Systemic Sclerosis (SSc)
AT1R antibodies are strongly associated with SSc pathogenesis:
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Mechanisms: Induce endothelial apoptosis, promote fibroblast activation, and upregulate pro-inflammatory cytokines (e.g., IL-8, CCL18) .
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Prognostic Value: High serum levels correlate with pulmonary arterial hypertension, digital ulcers, and mortality .
Solid Organ Transplantation
Key Controversies:
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Diagnostic thresholds: Varying cutoffs (>10–17 U/mL) complicate clinical interpretation .
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Complement-independent injury: Suggested by lack of C4d staining in biopsy samples .
Experimental Models
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Immunization studies: Mice immunized with AT1R develop perivascular inflammation, lymphocytic alveolitis, and skin fibrosis, mimicking SSc-like pathology .
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Monoclonal antibodies: Generated mAT1R Abs induce profibrotic responses in dermal fibroblasts via TGF-β signaling .
Future Directions
Product Specs
Constituents: 50% Glycerol, 0.01M Phosphate Buffered Saline (PBS), pH 7.4
Target Background
Q&A
Given the lack of specific information on "AT2S1 Antibody" in the search results, I will create a general FAQ for researchers focusing on antibodies in academic research scenarios. This FAQ will cover both basic and advanced research questions related to antibody use in scientific studies.
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To assess the specificity of an antibody, you should:
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Use controls: Include negative controls (e.g., samples without the target antigen) and positive controls (samples with known amounts of the target antigen).
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Cross-reactivity testing: Test the antibody against closely related proteins or antigens to ensure it does not cross-react.
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Validate with multiple methods: Use different techniques (e.g., Western blot, immunofluorescence, ELISA) to confirm the antibody's specificity.
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When selecting an antibody, consider:
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Specificity: Ensure the antibody is specific to your target antigen and does not cross-react with other proteins.
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Sensitivity: Choose an antibody that provides a strong signal in your assay.
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Epitope: If known, ensure the epitope is accessible in your experimental conditions.
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Species reactivity: Ensure the antibody reacts with your species of interest.
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When analyzing contradictory data:
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Assess assay conditions: Differences in buffer, temperature, or incubation time might affect results.
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Validate with multiple antibodies: Use different antibodies targeting the same antigen to confirm findings.
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Consider epitope accessibility: The epitope might be masked or altered in certain conditions.
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Advanced techniques include:
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Single-cell analysis: Use techniques like single-cell RNA sequencing or flow cytometry to analyze antibody responses at the single-cell level.
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Topological data analysis: Apply this method to understand complex antibody dynamics and interactions.
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Bioinformatics tools: Utilize tools like BLAST for assessing target and species homology.
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To maintain antibody efficacy:
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Purification methods: Use Protein A/G for monoclonal antibodies and immunogen affinity purification for polyclonal antibodies.
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Storage conditions: Store antibodies at -20°C or -80°C with preservatives like sodium azide to prevent bacterial contamination.
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To optimize antibody concentration:
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Titration experiments: Perform serial dilutions to find the optimal concentration that provides the strongest signal while minimizing background noise.
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Consider antigen abundance: Adjust concentrations based on the abundance of your target antigen.
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When interpreting ELISA results:
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Standard curves: Create a standard curve for each ELISA kit to ensure accurate interpolation of results.
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Inter-assay variability: Be aware that different kits may introduce variability due to differences in manufacturing processes.
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To study antibody dynamics in disease models:
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Use longitudinal sampling: Collect samples over time to track changes in antibody levels and specificity.
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Combine with other immune markers: Analyze antibody responses alongside other immune markers like T cell responses.
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Bioinformatics tools include:
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BLAST: For assessing target and species homology.
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Epitope prediction software: Tools like IEDB or DiscoTope can predict potential epitopes on antigens.
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Emerging trends include:
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Single-domain antibodies: These offer advantages in terms of size and stability.
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Engineered antibodies: Techniques like antibody engineering can enhance specificity and affinity.
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Computational modeling: Using computational models to predict antibody-antigen interactions and design new antibodies.
