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| Size | Qty | Add To Basket |
|---|---|---|
| 1×48 T | ||
| 1×96 T |
| Product Description | The quantitative human AMR (glycosylated) sandwich ELISA kit is designed to detect human adrenomedullin receptor (AMR) levels. AMR, also known as calcitonin receptor-like receptor (CALCRL) in complex with RAMP2 or RAMP3, is a G protein-coupled receptor that mediates the effects of adrenomedullin, a peptide involved in vasodilation, angiogenesis, and cell proliferation. It plays a crucial role in cardiovascular and renal function. 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 AMR in the sample. |
| Target | AMR |
| N-Glycosylation Site | 28, 37 |
| 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 | Adrenomedullin receptor |
| Alternate Names | AMR; Adrenomedullin receptor; ADMR; GPR182; G protein-coupled receptor 182 |
| Uniprot No. | O15218 |
| Application | The quantitative human AMR (glycosylated) sandwich ELISA kit is valuable for researchers investigating cardiovascular diseases, sepsis, and cancer, where adrenomedullin signaling is implicated. By quantifying AMR, researchers can gain insights into its role in disease pathogenesis and explore potential therapeutic targets related to vasodilation and angiogenesis. |
| 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, 90-105%; 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. |