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Human Insulin ELISA Kit

Human Insulin ELISA Kit

SKU: 31380

★ Download Datasheet PDF ★

Download MSDS

 

Assay range: 3 - 120 uU/mL

Sample Size: 25 uL

Kit Size: 96 wells/kit

  • INTRODUCTION

    Insulin is a peptide hormone exclusively produced in pancreatic beta-cells. It consists of A chain and B chain, which are linked by two disulfide bridges.
    Insulin is the primary hormone responsible for glucose metabolism. Impaired insulin secretion and insulin resistance are key causes of type 2 diabetes (T2D).

  • PRINCIPLE OF THE ASSAY

    This assay is a two-site ELISA. The micro-plate is pre-coated with a monoclonal antibody against insulin. Standards and samples are added into the wells and coincubated with a monoclonal antibody conjugated to horseradish peroxidase (HRP) enzyme. After wash step to remove any unbound substances, TMB substrate is added and colour develops in proportion to the amount of insulin bound initially. The assay is stopped and the optical density of the wells determined using a micro-plate reader. Since the increases in absorbance are directly proportional to the amount of captured insulin, the unknown sample concentration can be interpolated from a reference curve included in each assay.

  • ASSAY PERFORMANCE

    A. Typical representation of standard curve

    The following standard curve is provided for demonstration only. A standard curve should be generated for each assay.

    Insulin (µU/mL)

    Absorbance

    (450 nm)

    Blanked Absorbance

    0

    0.052

    0

    3

    0.074

    0.022

    6

    0.114

    0.062

    12

    0.226

    0.174

    25

    0.549

    0.497

    50

    1.189

    1.137

    120

    2.705

    2.653

     

    B. Sensitivity

    The lowest insulin level that can be measured by this assay is 3 µU/mL.

     

    C. Precision

    Intra-assay Precision (Precision within an assay) C.V. < 3.4%.

    Inter-assay Precision (Precision between assays) C.V. <5.0%.

     

    D. Recovery

    The recovery of the assay was determined by adding various amounts insulin to a sample. The measured concentration of the spiked sample in the assay was compared to the expected concentration. The average recovery was 92%.

     

    E. Specificity

    Percent of cross reactivity

    Mouse insulin: 100%

    Rat insulin: 100%

  • PUBLICATIONS CITING THIS PRODUCT

    1. Liu Y, Wang Y, Ni Y, Cheung CK, Lam KS, Wang Y, Xia Z, Ye D, Guo J, Tse MA, Panagiotou G. Gut microbiome fermentation determines the efficacy of exercise for diabetes prevention. Cell metabolism. 2020 Jan 7;31(1):77-91.
    2. Lui MM, Mak JC, Chong PW, Lam DC, Ip MS. Circulating adipocyte fatty acid–binding protein is reduced by continuous positive airway pressure treatment for obstructive sleep apnea—a randomized controlled study. Sleep and Breathing. 2020 Sep;24(3):817-24.
    3. Wong TH, Wan JM, Iris MY, Sit WH, Louie JC. Consuming decaffeinated coffee with milk and sugar added before a high-glycaemic index meal improves postprandial glycaemic and insulinaemic responses in healthy adults. British Journal of Nutrition. 2020 Oct;124(8):785-96.
    4. Wong THT, Wan JMF, Louie JCY. Flash Glucose Monitoring Can Accurately Reflect Postprandial Glucose Changes in Healthy Adults in Nutrition Studies. J Am Coll Nutr. 2021 Jan;40(1):26-32.
    5. WONG TH, WAN JM, TSE IM, SIT WH, LOUIE JC. Consumption of decaffeinated coffee with milk and sugar added before a high-glycemic-index meal lowers postprandial glucose surge when compared with consuming it after the meal. Human Nutrition & Metabolism. 2021 Mar 20:200124.
    6. Yang Y, Wu J, Wang X, Yao J, Lao KS, Qiao Y, Xu Y, Hu Y, Feng Y, Cui Y, Shi S. Circulating fibroblast growth factor 21 as a potential biomarker for missed abortion in humans. Fertility and Sterility. 2021 Jun 21.
    7. So WY, Liu WN, Teo AK, Rutter GA, Han W. Paired box 6 programs essential exocytotic genes in the regulation of glucose-stimulated insulin secretion and glucose homeostasis. Science Translational Medicine. 2021 Jun 30;13(600):eabb1038.
    8. Diaz-Canestro C, Chen J, Liu Y, Han H, Wang Y, Honore´ E, Lee CH, Lam KSL, Tse MA, Xu A. A machine-learning algorithm integrating baseline serum proteomic signatures predicts exercise responsiveness in overweight males with prediabetes. Cell Reports Medicine. 2023 Feb 7;100944.
    9. Chen J, Wang Z, Wang T, Cheng J, Zhuang R, Wang W. SNAP23 decreases insulin secretion by competitively inhibiting the interaction between SNAP25 and STX1A. Biosci Rep. 2023 May 31;43(5):BSR20222594.
$330.00Price

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