Hemolysis is a common cause of errors in laboratory tests as it affects blood parameters and leads to a positive or negative bias. This study aims to examine the relationship between the level of hemolysis (expressed as cell-free hemoglobin concentration, g/L) and the variability of metabolic and endocrine parameters and to determine the threshold level of hemolysis that causes an analytically and clinically significant bias for the twenty most frequently examined blood parameters in cows. Paired blood samples of 10 mL each were obtained from 30 cows. One was subjected to mechanical trauma and plasma was extracted directly from the other. Hemolyzed and non-hemolyzed samples from the same animal were mixed to obtain final samples with cell-free hemoglobin concentrations of 0, 1, 2, 4, 6, 8, and 10 g/L. Metabolic and endocrine parameters were measured in the samples and their deviation and the linear equation between the level of hemolysis and the deviation were determined. The following threshold values of hemolysis were determined, which correspond to the acceptable analytical (lower value) and clinical (upper value) levels of parameter variability: BHB 0.96 and 4.81; NEFA 0.39 and 3.31; GLU 0.38 and 3.90; ALB 1.12 and 6.11; TPROT 1.40 and 6.80; UREA 6.62 and 20.1; TBIL 0.75 and 5.65; AST 0.11 and 2.18; GGT 1.71 and 8.90, LDH 0.01 and 0.11, ALP 0.97 and 2.95; TGC 1.56 and 15.5; CHOL 1.29 and 8.56; Ca 5.68 and 25.7; P 0.57 and 8.43; Mg 1.10 and 8.47; INS 1.15 and 3.89; T3 8.19 and 15.6; T4 8.97 and 18.5; and CORT 2.78 and 11.22 g/L cell-free hemoglobin. Three decision levels are available for each metabolic and endocrine parameter: if hemolysis is below the lower (analytical) threshold value, results can be reported without restriction; if hemolysis is between the lower and upper thresholds, the results can be issued with guidance in the form of corrective linear equations; and if hemolysis is above the upper (clinical) threshold, the results and sample must be discarded. This method contributes to an optimal approach to hemolysis interference with metabolic profile parameters in blood samples from cows.
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http://dx.doi.org/10.3390/ani14121773 | DOI Listing |
Diabetes Obes Metab
January 2025
BFA, UMR 8251, CNRS, Team « Biologie et Pathologie du Pancréas Endocrine », Université Paris Cité, Paris, France.
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Department of Biology, Islamshahr Branch, Islamic Azad University, Islamshahr, Tehran, Iran.
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Environ Res
January 2025
School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo, Brazil; National Institute of Science and Technology for Detection, Toxicological Evaluation and Removal of Micropollutants and Radioactive Substances (INCT-DATREM). Electronic address:
Diisopentyl phthalate (DiPP) is present in many consumer goods, but can be absorbed into the human body, and can disrupt the endocrine system affecting reproductive health and fetal development. Studies revealed that biological samples of pregnant women in Brazil contained DiPP, raising even more the concerns about its usage. This study investigated how DiPP concentrations (12.
View Article and Find Full Text PDFEat Weight Disord
January 2025
Obesity Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Reprod Toxicol
January 2025
Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain; Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain; Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y la Nutrición (CIBEROBN), Institute of Health Carlos III, Madrid, Spain.
This study aimed to investigate the association between estimated dietary intake of polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) and human sperm quality. This study cross-sectionally assessed the associations between estimated dietary intake of PCDD/Fs and sperm quality parameters in 200 participants aged 18-40 years from the Led-Fertyl study. Linear regression models, accounting for potential confounding variables, were employed to evaluate the relationships.
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