There is no product in the shopping cart, buy it!
| Size | Qty | Add To Basket |
|---|---|---|
| 1×48 T | ||
| 1×96 T |
| Product Description | The quantitative human EREG (glycosylated) sandwich ELISA kit is designed to detect human epiregulin (EREG) levels. EREG is a growth factor that belongs to the epidermal growth factor (EGF) family, playing a role in cell proliferation, differentiation, and tissue remodeling. It is involved in various physiological and pathological processes, including wound healing and cancer progression. The kit is suitable for various biological samples such as tissue homogenates, cell lysates, serum, plasma. Its sensitivity is 7.136 pg/mL, which can accurately detect low concentrations of EREG in the sample. |
| Target | EREG |
| N-Glycosylation Site | 47 |
| Sample Types | Tissue homogenates, cell lysates, serum, plasma |
| Sample Volume | 100 μL |
| Sensitivity | 7.136 pg/mL |
| Detection Principle | Quantitative sandwich ELISA |
| Detection Range | 20 pg/mL-1000 pg/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 | Epiregulin |
| Alternate Names | EREG; Epiregulin; EPR; ER |
| Uniprot No. | O14944 |
| Application | The quantitative human EREG (glycosylated) sandwich ELISA kit is valuable for researchers investigating cancer, inflammatory diseases, and wound healing, where EREG signaling is implicated. By quantifying EREG, researchers can gain insights into its role in disease pathogenesis and explore potential diagnostic or therapeutic applications related to EGF receptor signaling. |
| 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, 80-100%; |
| Standard Curve | ![]() The standard curve is for reference only, and a new standard curve should be generated for each set of samples tested. |