The cause of the abnormal reaction of clinical chemistry was confirmed by electrophoresis

2016 ◽  
Vol 60 (1) ◽  
pp. 27-30
Author(s):  
Masanori Seimiya ◽  
Yachiyo Endo ◽  
Mariko Watanabe ◽  
Haruna Asano ◽  
Saori Honda ◽  
...  
Keyword(s):  
Clinical Chemistry

Drug-interference in clinical chemistry analyses pseudohypertriglyceridaemia

2014 ◽  
Vol 3 (2) ◽  
pp. 153
Author(s):  
P Swathi ◽  
M Prasanth ◽  
MM Suchitra ◽  
AparnaR Bitla
Keyword(s):  
Clinical Chemistry ◽  
Drug Interference

Textbook of clinical chemistry

1986 ◽  
Vol 14 (3) ◽  
pp. 146 ◽  
Author(s):  
F Vella
Keyword(s):  
Clinical Chemistry

scholarly journals Generation and Characterization of dickkopf3 Mutant Mice

2006 ◽  
Vol 26 (6) ◽  
pp. 2317-2326 ◽  
Author(s):  
Ivan del Barco Barrantes ◽  
Ana Montero-Pedrazuela ◽  
Ana Guadaño-Ferraz ◽  
Maria-Jesus Obregon ◽  
Raquel Martinez de Mena ◽  
...  
Keyword(s):  
Thyroid Hormone ◽  
Clinical Chemistry ◽  
Lung Ventilation ◽  
Immunoglobulin M ◽  
Mutant Mice ◽  
Phenotypic Analysis ◽  
Thyroid Hormone Metabolism ◽  
Hormone Binding Protein ◽  
Deficient Mice

ABSTRACT dickkopf (dkk) genes encode a small family of secreted Wnt antagonists, except for dkk3, which is divergent and whose function is poorly understood. Here, we describe the generation and characterization of dkk3 mutant mice. dkk3-deficient mice are viable and fertile. Phenotypic analysis shows no major alterations in organ morphology, physiology, and most clinical chemistry parameters. Since Dkk3 was proposed to function as thyroid hormone binding protein, we have analyzed deiodinase activities, as well as thyroid hormone levels. Mutant mice are euthyroid, and the data do not support a relationship of dkk3 with thyroid hormone metabolism. Altered phenotypes in dkk3 mutant mice were observed in the frequency of NK cells, immunoglobulin M, hemoglobin, and hematocrit levels, as well as lung ventilation. Furthermore, dkk3-deficient mice display hyperactivity.

scholarly journals Clinical Evaluation of the Torq Zero Delay Centrifuge System for Decentralized Blood Collection and Stabilization

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1019
Author(s):  
Kyungjin Hong ◽  
Gabriella Iacovetti ◽  
Ali Rahimian ◽  
Sean Hong ◽  
Jon Epperson ◽  
...  
Keyword(s):  
Clinical Chemistry ◽  
Blood Collection ◽  
Test Results ◽  
Sample Collection ◽  
Rapid Separation ◽  
Cell Counts ◽  
Collection Device ◽  
Precision Study ◽  
Clinically Significant ◽  
Blood Specimens

Blood sample collection and rapid separation—critical preanalytical steps in clinical chemistry—can be challenging in decentralized collection settings. To address this gap, the Torq™ zero delay centrifuge system includes a lightweight, hand-portable centrifuge (ZDrive™) and a disc-shaped blood collection device (ZDisc™) enabling immediate sample centrifugation at the point of collection. Here, we report results from clinical validation studies comparing performance of the Torq System with a conventional plasma separation tube (PST). Blood specimens from 134 subjects were collected and processed across three independent sites to compare ZDisc and PST performance in the assessment of 14 analytes (K, Na, Cl, Ca, BUN, creatinine, AST, ALT, ALP, total bilirubin, albumin, total protein, cholesterol, and triglycerides). A 31-subject precision study was performed to evaluate reproducibility of plasma test results from ZDiscs, and plasma quality was assessed by measuring hemolysis and blood cells from 10 subject specimens. The ZDisc successfully collected and processed samples from 134 subjects. ZDisc results agreed with reference PSTs for all 14 analytes with mean % biases well below clinically significant levels. Results were reproducible across different operators and ZDisc production lots, and plasma blood cell counts and hemolysis levels fell well below clinical acceptance thresholds. ZDiscs produce plasma samples equivalent to reference PSTs. Results support the suitability of the Torq System for remotely collecting and processing blood samples in decentralized settings.

scholarly journals NMR Metabolite Profiles in Male Meat-Eaters, Fish-Eaters, Vegetarians and Vegans, and Comparison with MS Metabolite Profiles

Metabolites ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 121
Author(s):  
Julie A. Schmidt ◽  
Georgina K. Fensom ◽  
Sabina Rinaldi ◽  
Augustin Scalbert ◽  
Marc J. Gunter ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Clinical Chemistry ◽  
Saturated Fatty Acids ◽  
Density Lipoprotein ◽  
Diet Group ◽  
Gas Liquid Chromatography ◽  
Very Low Density Lipoproteins ◽  
Animal Products ◽  
Total N ◽  
Metabolite Profiles

Metabolomics may help to elucidate mechanisms underlying diet-disease relationships and identify novel risk factors for disease. To inform the design and interpretation of such research, evidence on diet-metabolite associations and cross-assay comparisons is needed. We aimed to compare nuclear magnetic resonance (NMR) metabolite profiles between meat-eaters, fish-eaters, vegetarians and vegans, and to compare NMR measurements to those from mass spectrometry (MS), clinical chemistry and capillary gas-liquid chromatography (GC). We quantified 207 serum NMR metabolite measures in 286 male participants of the European Prospective Investigation into Cancer and Nutrition (EPIC)-Oxford cohort. Using univariate and multivariate analyses, we found that metabolite profiles varied by diet group, especially for vegans; the main differences compared to meat-eaters were lower levels of docosahexaenoic acid, total n-3 and saturated fatty acids, cholesterol and triglycerides in very-low-density lipoproteins, various lipid factions in high-density lipoprotein, sphingomyelins, tyrosine and creatinine, and higher levels of linoleic acid, total n-6, polyunsaturated fatty acids and alanine. Levels in fish-eaters and vegetarians differed by metabolite measure. Concentrations of 13 metabolites measured using both NMR and MS, clinical chemistry or GC were mostly similar. In summary, vegans’ metabolite profiles were markedly different to those of men consuming animal products. The studied metabolomics platforms are complementary, with limited overlap between metabolite classes.

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