[1]. Han BR, et al. MAPK inhibitors enhance cell death in pyrogallol-treated human pulmonary fibroblast cells via increasing O2•- levels. Oncol Lett. 2017 Jul;14(1):1179-1185
Insulin ELISA 英文简述： The ALPCO Insulin ELISA kit is a FDA registered in vitro diagnostic tool for the quantification of human insulin in a clinical setting or research laboratory. Utilizing a dual-monoclonal antibody sandwich ELISA format, bi-level control set, and 96-well microplate comprising removable strips, a single Insulin ELISA kit has the performance characteristics and flexibility necessary to confidently measure up to 40 samples in duplicate. The shelf-life of the components and the resealable microplate pouch allow for convenient storage for future use if the entire kit is not needed at one time. Additional information regarding the Insulin ELISA kit can be accessed by clicking on the “Protocol” link or “Support” tab above.
PRINCIPLE OF THE ASSAY The ALPCO Insulin ELISA is a sandwich type immunoassay. The 96-well microplate is coated with a monoclonal antibody specific for insulin. The standards, controls, and samples are added to the microplate wells with the Detection Antibody. The microplate is then incubated on a microplate shaker at 700-900 rpm. After the first incubation is complete, the wells are washed with Wash Buffer and blotted dry. TMB Substrate is added, and the microplate is incubated a second time on a microplate shaker at 700-900 rpm. Once the second incubation is complete, Stop Solution is added, and the optical density （OD） is measured by a spectrophotometer at 450 nm. The intensity of the color generated is directly proportional to the amount of insulin in the sample.
CALCULATION OF RESULTS Construct a standard curve from the standards. The Zero Standard should be used as a blank with its average value subtracted from each well. It is recommended to use a software program to calculate the standard curve and to determine the concentration of the samples. The Insulin ELISA is a ligand binding assay, with responses exhibiting a sigmoidal relationship to the analyte concentration. Currently accepted reference models for such curves use a 4 or 5 parameter logistic （pl） fit, as these models optimize the accuracy and precision across a greater range. Although cubic spline and other models are acceptable methods, they generally show less intra-assay accuracy and precision at the low and high ends of the range. In the example below, a 5 pl curve fit was used to maximize the accuracy and precision of samples with low concentrations. However, the accuracy and precision of all models are limited at the lowest and highest ends of the detectable range due to the influence of individual laboratory conditions. As a result, caution should always be used when interpreting results where the analyte response becomes non-linear.
