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| Size | Qty | Add To Basket |
|---|---|---|
| 1×48 T | ||
| 1×96 T |
| Product Description | The quantitative human ISLR (glycosylated) sandwich ELISA kit is designed to detect human immunoglobulin superfamily containing leucine rich repeat protein (ISLR) levels. ISLR is a cell adhesion molecule involved in neuronal development, angiogenesis, and tissue morphogenesis. It plays a role in cell-cell interactions and signaling pathways. The kit is suitable for various biological samples such as tissue homogenates, cell lysates. Its sensitivity is 0.125 ng/mL, which can accurately detect low concentrations of ISLR in the sample. |
| Target | ISLR |
| N-Glycosylation Site | 51, 309 |
| Sample Types | Tissue homogenates, cell lysates |
| Sample Volume | 100 μL |
| Sensitivity | 0.125 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. |
| Species | Human |
| Full Name | Immunoglobulin superfamily containing leucine rich repeat protein |
| Alternate Names | ISLR; Immunoglobulin superfamily containing leucine rich repeat protein; Immunoglobulin superfamily containing leucine-rich repeat protein |
| Uniprot No. | O14498 |
| Application | The quantitative human ISLR (glycosylated) sandwich ELISA kit is useful for researchers studying neurological disorders, vascular diseases, and developmental biology, where ISLR expression and function are relevant. By quantifying ISLR, researchers can gain insights into its role in these conditions and explore potential diagnostic or therapeutic applications. |
| Kit Components | Pre-coated ELISA plate; Lyophilized standard; Biotin-labeled antibody; HRP-avidin; Various diluents; Wash buffer; TMB chromogenic substrate; Stop solution |
| Precision | Intra-Assay: n=20, CV <8%; Inter-Assay: n=20, CV <10%; |
| Recovery | Serum sample: n=5, 80-100%; Plasma sample: n=4, 95-105%; |
| Standard Curve | ![]() The standard curve is for reference only, and a new standard curve should be generated for each set of samples tested. |