This study determined the effect of sample mishandling on the performance of ELISAs for detection of antibodies against infectious bronchitis virus (IBV), avian encephalomyelitis virus (AEV) and chicken anaemia virus (CAV) in the serum of chickens. The effects of five different sample mishandling treatments were assessed: heat treatment, repetitive freezing and thawing and three levels of severity of haemolysis. These mishandling treatments simulated different conditions that might occur during routine blood collection, transport or storage in a clinical practice setting. Each mishandling treatment was experimentally applied under laboratory conditions and then samples were assayed for antibodies against IBV, AEV and CAV using commercial ELISA kits. Severe haemolysis had the most consistent detrimental effect on ELISA performance, producing results that were significantly different from the reference standard in all three ELISAs, although the direction of the effect varied (less positive for the IBV and CAV assays; more positive for the AEV assay). Moderate levels of haemolysis had a similar, but less consistent, effect to that of severe haemolysis, producing results that were significantly different from the reference standard only for the IBV (less positive) and AEV (more positive) ELISAs. Repetitive freeze-thawing also produced a significant effect on ELISA results for IBV (less positive) and AEV (more positive). The IBV ELISA appeared to be most susceptible to the effects of serum maltreatment. The findings from this study suggest that unpredictable variation in the results of ELISAs can occur due to different sample mishandling treatments.
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http://dx.doi.org/10.1016/j.tvjl.2011.08.028 | DOI Listing |
Food Res Int
January 2025
Department of Animal and Public Health, School of Veterinary Medicine, Universidad Nacional Mayor de San Marcos, Av. Circunvalacion 2800, San Borja 15021, Lima 41, Peru; Tropical and Highlands Veterinary Research Institute, Universidad Nacional Mayor de San Marcos, Jr. 28 de Julio s/n, Jauja, 12150, Peru; Global Health Center, Universidad Peruana Cayetano Heredia, Av. Honorio Delgado 430, San Martín de Porres 15102, Lima 41, Peru. Electronic address:
Campylobacter is a major cause of foodborne gastroenteritis worldwide, with the mishandling of contaminated chicken meat among the main pathways for human infection. Granted the disease burden due to this pathogen, systematic assessments of its potential impact are necessary. The aims of this study were to evaluate both presence and load of Campylobacter in chicken meat sold in traditional markets, assess risk factors related with the infrastructure and hygienic conditions of market stalls, and evaluate control strategies for campylobacteriosis in Peru through a quantitative microbiological risk assessment (QMRA), a data-driven, systematic approach to quantitatively assess risks by integrating empirical contamination levels, microbial behavior, and consumer exposure.
View Article and Find Full Text PDFACS Omega
December 2024
Biobank Väst, SE-413 45 Gothenburg, Sweden.
The preanalytical handling of plasma, how it is drawn, processed, and stored, influences its composition. Samples in biobanks often lack this information and, consequently, important information about their quality. Especially metabolite concentrations are affected by preanalytical handling, making conclusions from metabolomics studies particularly sensitive to misinterpretations.
View Article and Find Full Text PDFPharmaceutics
September 2024
Instituto de Investigación Biosanitaria ibs.GRANADA, Avda de Madrid, 15, 18012 Granada, Spain.
Sci Total Environ
October 2024
Department of Food Analysis and Nutrition, Faculty of Food and Biochemical Technology, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6 - Dejvice, Prague, Czech Republic.
Mol Biol Evol
July 2024
Institute of Computational Life Science, Zurich University of Applied Science, Wädenswil, Switzerland.
Despite having important biological implications, insertion, and deletion (indel) events are often disregarded or mishandled during phylogenetic inference. In multiple sequence alignment, indels are represented as gaps and are estimated without considering the distinct evolutionary history of insertions and deletions. Consequently, indels are usually excluded from subsequent inference steps, such as ancestral sequence reconstruction and phylogenetic tree search.
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