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#generative ai Open access

PREreview of "Evaluation of Ante-Mortem Sampling Matrices for qPCR Detection of Canine Distemper Virus"

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22958187. The baseline strategy of evaluating clinical sample types to optimize qPCR diagnostic sensitivity grids for Canine Distemper Virus is highly relevant to contemporary mole ular virology. Independent validation of different antemortem matrices is historically neglected, leading to false negatives during acute viral shielding windows. While the comparative approach across urine, conjunctival, and whole blood fractions is structurally useful, the underlying experimental design requires tighter calibration boundaries regarding extraction variance. The authors must fully report the specific standard deviations and intra-assay coefficients of variation observed across high-density Ct values. Bypassing these numerical data limits introduces significant noise into target copy number estimations. Additionally, tracking target sequence mutations that dynamically alter primer-bining kinetics under selective host pressures is essential to prove long-term assay validation. This technical adjustment establishes an objective benchmark for diagnostic networks mapping cross-host morbillivirus transmission tracks without dry-lab limitations. Competing interests The author declares that they have no competing interests. Use of Artificial Intelligence (AI) The author declares that they did not use generative AI to come up with new ideas for their review.

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