Cat NO.:	EL0035Hu
Product:	Sunlong Medical™ Human Adiponectin ELISA Kit
Storage	4℃ (unopened) for two years
Shipping Condition	4℃
Sample Type:	Serum | plasma | cell culture supernatant and other biological samples
Spike Recovery Range:	95% - 106%
Mean Spike Recovery:	0.99
CV of Intra plate:	3.4 % - 4.9 %
CV of Inter plate:	2.4 % - 5.7 %
NCBI_Gene:	9370
UniProtKB:	Q15848

 

PLATFORM	ELISA
PLATE	Detachable 96-well plate
SIZE	96T/48T
STORAGE	If the reagent kit is unopened, it should be stored at 4℃. However, if it has been opened, the standard solution should be stored at -20℃, while the other components should be stored at 4℃.
DELIVERY	4℃ blue ice transportation
COMPONENTS	96-well polystyrene enzyme-linked immunosorbent assay (ELISA) plate coated with anti-Adiponectin/Acrp30 monoclonal antibody Human Adiponectin/Acrp30 freeze-dried standard Adiponectin/Acrp30 detect Antibody Standard Diluent Assay Buffer(10×) Substrate TMB Stop Solution Washing Buffer(20×) Sealing Film
ASSAY PRINCIPLE	This kit utilizes the double antibody sandwich enzyme-linked immunosorbent assay (ELISA) detection technique.Specific anti-human Adiponectin antibodies are precoated on a high-affinity ELISA plate. Standard samples, test samples, and biotinylated detection antibodies are added to the wells of the ELISA plate. After incubation, Adiponectin present in the samples binds to the solid-phase antibodies and the detection antibodies. After washing to remove unbound substances, streptavidin-HRP labeled with horseradish peroxidase is added. After washing, a colorimetric substrate, TMB, is added and the plate is incubated in the dark for color development. The intensity of the color reaction is directly proportional to the concentration of Adiponectin in the samples. A stop solution is added to terminate the reaction, and the absorbance value is measured at a wavelength of 450 nm (with a reference wavelength range of 570-630 nm).

 

 1. Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning

Frontiers in Endocrinology 2023-08-29

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