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Quantitative Human Siglec-6 (Glycosylated) Sandwich ELISA Kit

CAT#: GLJF-0525-HX62

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Specifications
Product Description
The quantitative human Siglec-6 (glycosylated) sandwich ELISA kit is designed to detect human sialic acid binding Ig like-lectin 6 (Siglec-6) levels. Siglec-6 is a transmembrane receptor belonging to the Siglec family, primarily expressed on B cells and placental trophoblasts. The kit is suitable for various biological samples such as tissue homogenates, cell lysates. Its sensitivity is 0.092 ng/mL, which can accurately detect low concentrations of Siglec-6 in the sample.
Target
Siglec-6
Kit Components
Pre-coated ELISA plate; Lyophilized standard; Biotin-labeled antibody; HRP-avidin; Various diluents; Wash buffer; TMB chromogenic substrate; Stop solution
Sample Types
Tissue homogenates, cell lysates
Sample Volume
100 μL
Sensitivity
0.092 ng/mL
Detection Principle
Quantitative sandwich ELISA
Detection Range
1 ng/mL-10 ng/mL
Detection Time
1 h-5 h
Detection Wavelength
450 nm
Storage
Store at 2-8°C for long term storage.
Target Information
Species
Human
Full Name
Sialic acid binding Ig like lectin 6
Alternate Names
Siglec-6; Sialic acid binding Ig like lectin 6; CD33L; OBBP1; SIGLEC-6; CD327; CD33 antigen-like 1
Uniprot No.
N-Glycosylation Site
103, 149, 163, 233
Application Notes
Application
The quantitative human Siglec-6 (glycosylated) sandwich ELISA kit is utilized in research to investigate the expression patterns and regulatory mechanisms of Siglec-6, particularly in studies related to immune system disorders, cancer, and placental function. By accurately quantifying Siglec-6 levels, researchers can explore its involvement in disease mechanisms, assess its potential as a biomarker for diagnostic or prognostic purposes, and evaluate the effects of therapeutic interventions targeting this receptor.
Precision
Intra-Assay: n=20, CV <8%;
Inter-Assay: n=20, CV <10%;
Recovery
Serum sample: n=5, 90-105%;
Plasma sample: n=4, 85-100%;
Standard Curve

The standard curve is for reference only, and a new standard curve should be generated for each set of samples tested.
For Research Use Only.
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