CHIB1 Antibody
Description
Introduction to CIB1 Antibody
CIB1 antibodies are immunological tools targeting the calcium- and integrin-binding protein 1 (CIB1), a 22 kDa protein involved in cell signaling, DNA repair, and cancer progression . These antibodies enable researchers to:
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Detect CIB1 expression in tissues/cells via Western blot (WB), immunohistochemistry (IHC), or immunofluorescence
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Study its interaction partners through co-immunoprecipitation (Co-IP)
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Investigate its role in epithelial-mesenchymal transition (EMT) and tumor metastasis
Molecular Mechanisms of CIB1
CIB1 functions through:
Key interactions:
Functional domains:
Clinical Significance in Lung Adenocarcinoma (LAC)
CIB1 is overexpressed in 60% of LAC cases and correlates with poor prognosis :
Table 1: CIB1 Expression vs. Clinical Parameters (n=60 LAC Patients)
| Clinical Feature | High CIB1 (%) | Low CIB1 (%) | P-value |
|---|---|---|---|
| Lymph Node Metastasis (N1-2) | 76.9 | 23.1 | 0.019 |
| Advanced TNM Stage (II-III) | 71.9 | 28.1 | 0.045 |
Survival Impact:
CIB1 Ubiquitination Pathway
CIB1 degradation is mediated by CHIP-mediated ubiquitination:
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CHIP binds CIB1 via direct protein interaction (Co-IP validation)
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Ubiquitination occurs at lysine residues K157/K165
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Proteasomal degradation reduces CIB1 levels by 63% in PC-9 cells (P<0.01)
Immune System Interactions
While CIB1 binds AID (a DNA-editing enzyme critical for antibody diversity), knockout studies show:
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Unaffected gene conversion in DT40 B cells
This suggests redundant regulatory mechanisms for AID activity.
Antibody Characterization & Applications
CIB1 antibodies require rigorous validation due to:
Recommended validation assays:
Product Specs
**Constituents:** 50% Glycerol, 0.01M PBS, pH 7.4
Target Background
- Amino acid substitutions at the acceptor binding site may have resulted in a larger association constant for G75W-AtChiC, leading to a higher transglycosylation activity of G75W-AtChiC. PMID: 22936594
Customer Reviews
Applications : WB
Sample type: Mouse Tissue
Review: Expression of AMCase in the oxyntic glands of M. javanica. Relative protein levels of AMCase in oxyntic glands from M. javanica and Mus musculus stomach were determined by western blot analysis.
Q&A
Given the lack of specific information on "CHIB1 Antibody" in the provided search results, I will create a general FAQ based on common research scenarios related to antibodies, focusing on experimental design, data analysis, and methodological approaches. This will be tailored to reflect the depth of scientific research and distinguish between basic and advanced questions.
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To evaluate the efficacy of an antibody, you should:
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Select a Relevant Disease Model: Choose an appropriate animal or cell culture model that mimics the human disease condition.
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Dose and Administration: Determine the optimal dose and route of administration for the antibody based on previous studies or pilot experiments.
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Control Groups: Include control groups receiving a placebo or a known standard treatment for comparison.
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Outcome Measures: Define clear outcome measures such as reduction in disease markers, improvement in symptoms, or survival rates.
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Production Methods: Antibodies can be produced using hybridoma technology, recombinant DNA technology, or phage display systems.
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Purification Techniques: Common purification methods include affinity chromatography (e.g., Protein A or Protein G), size exclusion chromatography, and ion exchange chromatography.
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Statistical Analysis: Use appropriate statistical tests to compare groups, considering factors like sample size and variability.
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Data Visualization: Plot data to visualize trends and outliers.
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Contradictory Results: Investigate potential sources of variation, such as experimental conditions or reagent quality. Consider repeating experiments or using alternative methods to validate findings.
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Specificity Assessment: Use Western blotting or ELISA to test the antibody against a panel of related and unrelated antigens.
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Cross-Reactivity Minimization: Optimize antibody concentration and incubation conditions. Consider using blocking agents or pre-absorption with non-specific antigens.
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Mutagenesis and Selection: Use techniques like site-directed mutagenesis followed by selection methods such as phage display or yeast display to enhance affinity or stability.
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Computational Modeling: Utilize computational tools to predict the effects of mutations on antibody structure and function before experimental validation.
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Sample Collection: Collect serum or plasma samples at multiple time points.
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Assays: Use ELISA, Western blot, or neutralization assays to measure antibody titers and specificity.
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Data Analysis: Employ statistical models to analyze changes in antibody levels over time, accounting for individual variability and potential confounding factors.
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Deep Learning and Linear Programming: Combine deep learning models with multi-objective linear programming to predict and optimize antibody properties.
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Experimental Validation: Validate designed libraries through experiments such as phage display or yeast display to ensure diversity and performance.
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Storage Conditions: Store antibodies at -20°C or -80°C in a buffer that maintains their stability, such as PBS with glycerol.
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Freeze-Thaw Cycles: Minimize freeze-thaw cycles to prevent degradation.
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Concentration and Format: Consider storing antibodies in a concentrated form or as lyophilized powders to reduce degradation risks.
Example Data Table: Antibody Response Over Time
| Time Point | Antibody Titer (U/mL) | Specificity |
|---|---|---|
| Baseline | 0.4 (IQR 0.4-5) | Low |
| Post-Dose 1 | 11 (IQR 0.4–250) | Moderate |
| Post-Dose 2 | 250 (IQR 3.5–250) | High |
This table illustrates how antibody titers and specificity can change over time following vaccination or treatment, reflecting an increase in immune response.
