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Hoffmann, R. A wiki for the life sciences where authorship matters. Nature Genetics (2008)
 
 
 

Estimation of estradiol in mouse serum samples: evaluation of commercial estradiol immunoassays.

The University of Virginia Center for Research in Reproduction Ligand Core performed an evaluation of nine commercial estradiol (E2) immunoassays for use with mouse serum. The evaluation had two components. 1) Recovery Studies: a mouse pool was spiked with E2 concentrations across the assay range, and percent recovery and parallelism to the assay standard curve were determined. 2) Correlation Studies: serum pools were collected from intact females, ovariectomized (OVX) and OVX-E2 treated mice and E2 assayed, then measured by gas chromatography/tandem mass spectrometry (GC/MSMS) for comparison to a gold standard method. Recovery results showed that E2 recovery from spiked mouse pools varied greatly (from <18% to >640%) among kits tested. However, three kits (DiaSorin Radioimmunoassay, Siemens Double Antibody RIA, and CalBiotech Enzyme Immunoassay) showed reasonable recoveries and parallelism. Data collected from the Correlation Study showed that values from intact, OVX and OVX-E2-treated mouse pools varied by several fold vs. GC/MSMS for most of the kits tested. The DiaSorin RIA and CalBiotech Enzyme Immunoassay Kits showed the best correlation to GC/MSMS. Unfortunately, while this evaluation was ongoing, the DiaSorin Kit was discontinued. In summary, the CalBiotech Kit was the only available assay tested that demonstrated good E2 parallelism to the assay standard curve and accuracy vs. a gold standard method (i.e. GC/MSMS). Also of note, the CalBiotech assay is sensitive and requires minimal sample volume. Therefore, based on these findings the CalBiotech E2 assay has been implemented for use in mouse serum samples within the Ligand Core.[1]

References

  1. Estimation of estradiol in mouse serum samples: evaluation of commercial estradiol immunoassays. Haisenleder, D.J., Schoenfelder, A.H., Marcinko, E.S., Geddis, L.M., Marshall, J.C. Endocrinology (2011) [Pubmed]
 
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