895 resultados para BLOOD PLASMA
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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Enxertos venosos ao avesso e normal, preenchidos com plasma rico em plaquetas em nervo misto de rato
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This work has as main theme optimize the method of determination of fatty acids such as methyl octanoate, methyl palmitate, methyl stearate, methyl oleate, methyl linoleate and methyl linolenate in blood plasma samples from mice. The method proved to be very suitable for the analysis, in which we obtained the following linear coefficients: 0.9992, 0.9989, 0.9996, 0.9995, 0.9999 for methyl linoleate acid, methyl oleate, methyl palmitate, methyl stearate and methyl octanoate, respectively. Esterification of the samples gave good reading of chromatograms of samples without interfering peaks. The results obtained were as expected from the diet of mices
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Zootecnia - FMVZ
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.
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Abstract Background To identify the most appropriate cut-off points of fasting glycemia for the screening of diabetes mellitus type 2 (DM2) with the comparison of the properties of capillary glycemia (CG) and venous blood plasma glycemia (PG) in a population of Japanese origin from the community of Mombuca, Guatapará - SP, Brazil. Methods This was a population-based descriptive cross-sectional study conducted on a sample of 131 individuals of both genders aged 20 years or more (66.8% of the target population). CG was measured with a glucometer in a blood sample obtained from the fingertip and PG was determined by an enzymatic method (hexokinase) in venous blood plasma, after a 10-14 hour fast in both cases. Data were analyzed by the receiver operating characteristic (ROC) curve in order to identify the best cut-off point for fasting glycemia (CG and PG) for the diagnosis of DM, using the 2-hour plasma glycemia > 200 mg/dl as gold - standard. Results The ROC curve revealed that the best cut-off point for the screening of DM was 110 mg/dl for CG and 105 mg/dl for PG, values that would optimize the relation between individuals with positive and false-positive results. The area under the ROC curve was 0.814 for CG (p < 0.01) and 0.836 for PG (p < 0.01). Conclusions The cut-off points of 105 mg/dl(5.8 mmol/l) for PG and of 110 mg/dl(6.1 mmol/l) for CG appear to be the most appropriate for the screening of DM2 in the population under study, with emphasis on the fact that the value recommended for CG is 5 mg/dl higher than that for PG, in contrast to WHO recommendations.
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O objetivo deste estudo foi analisar a influência da crioimersão corporal (CIC) imediata ao esforço físico agudo no estresse oxidativo (EOx) no plasma sanguíneo. Participaram do presente estudo 12 homens, com idade média de 22±1 anos, submetidos ao teste de esforço físico intenso em esteira, seguido de CIC em um tanque com água a 10ºC durante 10 minutos contínuos. Do repouso ao final da CIC, os indivíduos foram monitorados através de alguns parâmetros como: o índice de percepção subjetiva do esforço (IPE) expresso conforme escala de Borg, frequência cardíaca (FC), pressão arterial (PA) e temperatura corporal (TC) através da temperatura timpânica. A análise morfológica do EOx plasmático foi realizada de acordo com o método denominado Morfologia Óptica do Estresse Oxidativo no Plasma (MEOP), utilizando-se gotas de sangue capilar. Observou-se uma significativa elevação (p<0,01) no grau do estresse oxidativo plasmático após a realização do esforço físico, em relação ao respectivo grau em repouso. Porém, esta elevação no grau do EOx foi significativamente reduzida (p<0,001) em função da CIC. Embora sejam necessários mais estudos científicos com o MEOP, concluiu-se que, para o presente estudo, este teste mostrou-se viável. Os dados encontrados no presente estudo sugerem que a CIC em água a 10ºC por 10 minutos imediatos ao esforço físico agudo com intensidade alta, apresenta-se como uma importante conduta fisioterapêutica para a normalização do EOx pós-esforço.
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Hundred forty-four Shaver White laying hens were used over a 4 week experimental period to investigate the effect of 3% of soybean oil, corn oil (MIL), canola oil, flaxseed oil (LIN), salmon oil (SAL) or tuna and sardine oil (SR/AT) added to the diets, upon the fatty acid egg yolk composition, blood plasma levels and incorporation time of each fatty acid into the egg yolk. Hens were allocated into 72 cages and the experimental design was a 6 x 6 randomized factorial model. Hens fed 3% of different oils, responded with increased polyunsaturated fatty acids omega 3 (ω-3 PUFAs), except for corn oil. The addition of flaxseed, soybean or corn oil into the diet increased the PUFAs levels into the egg yolk and in the blood plasma. Adding tuna and sardine oil into the diet increased the concentration of yolk saturated fatty acids. The levels of ω-3 PUFAs were increased in the tuna and sardine oil treatment, while the flaxseed oil increased the plasma fatty acids. The deposition of 349.28 mg/yolk of a-linolenic fatty acids (ALA) was higher in the group fed LIN, while the higher equal to 157.13 mg DHA/yolk was observed in group SR/AT. In the plasma, deposition increased from 0.33% (MIL) for 6.29% ALA (LIN), while that of DHA increase of 0.47% (MIL) for 4.24% (SAL) and 4.48% (SR/AT) and of 0.98% (MIL) for 6.14% (SR/AT) and 8.44% (LIN) of ω-3 PUFAs. The percentage of EPA into the yolk and plasma was higher for the hens fed 3% tuna and sardine oil diet, as well as the levels of yolk DHA. The concentration of DHA into the plasma was higher for the salmon and tuna/sardine oil treatments. The PUFAs yolk decreased during the first eight days of experiment, while the ω-3 PUFAs increased during the same period. The concentration of ALA increased until ten days of experiment, while the percentage of EPA and DHA increased up to the eighth experimental day
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A global metabolic profiling methodology based on gas chromatography coupled to time-of-flight mass spectrometry (GC-TOFMS) for human plasma was applied to a human exercise study focused on the effects of beverages containing glucose, galactose, or fructose taken after exercise and throughout a recovery period of 6 h and 45 min. One group of 10 well trained male cyclists performed 3 experimental sessions on separate days (randomized, single center). After performing a standardized depletion protocol on a bicycle, subjects consumed one of three different beverages: maltodextrin (MD)+glucose (2:1 ratio), MD+galactose (2:1), and MD+fructose (2:1), consumed at an average of 1.25 g of carbohydrate (CHO) ingested per minute. Blood was taken straight after exercise and every 45 min within the recovery phase. With the resulting blood plasma, insulin, free fatty acid (FFA) profile, glucose, and GC-TOFMS global metabolic profiling measurements were performed. The resulting profiling data was able to match the results obtained from the other clinical measurements with the addition of being able to follow many different metabolites throughout the recovery period. The data quality was assessed, with all the labelled internal standards yielding values of <15% CV for all samples (n=335), apart from the labelled sucrose which gave a value of 15.19%. Differences between recovery treatments including the appearance of galactonic acid from the galactose based beverage were also highlighted.
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Binding of hydrophobic chemicals to colloids such as proteins or lipids is difficult to measure using classical microdialysis methods due to low aqueous concentrations, adsorption to dialysis membranes and test vessels, and slow kinetics of equilibration. Here, we employed a three-phase partitioning system where silicone (polydimethylsiloxane, PDMS) serves as a third phase to determine partitioning between water and colloids and acts at the same time as a dosing device for hydrophobic chemicals. The applicability of this method was demonstrated with bovine serum albumin (BSA). Measured binding constants (K(BSAw)) for chlorpyrifos, methoxychlor, nonylphenol, and pyrene were in good agreement with an established quantitative structure-activity relationship (QSAR). A fifth compound, fluoxypyr-methyl-heptyl ester, was excluded from the analysis because of apparent abiotic degradation. The PDMS depletion method was then used to determine partition coefficients for test chemicals in rainbow trout (Oncorhynchus mykiss) liver S9 fractions (K(S9w)) and blood plasma (K(bloodw)). Measured K(S9w) and K(bloodw) values were consistent with predictions obtained using a mass-balance model that employs the octanol-water partition coefficient (K(ow)) as a surrogate for lipid partitioning and K(BSAw) to represent protein binding. For each compound, K(bloodw) was substantially greater than K(S9w), primarily because blood contains more lipid than liver S9 fractions (1.84% of wet weight vs 0.051%). Measured liver S9 and blood plasma binding parameters were subsequently implemented in an in vitro to in vivo extrapolation model to link the in vitro liver S9 metabolic degradation assay to in vivo metabolism in fish. Apparent volumes of distribution (V(d)) calculated from the experimental data were similar to literature estimates. However, the calculated binding ratios (f(u)) used to relate in vitro metabolic clearance to clearance by the intact liver were 10 to 100 times lower than values used in previous modeling efforts. Bioconcentration factors (BCF) predicted using the experimental binding data were substantially higher than the predicted values obtained in earlier studies and correlated poorly with measured BCF values in fish. One possible explanation for this finding is that chemicals bound to proteins can desorb rapidly and thus contribute to metabolic turnover of the chemicals. This hypothesis remains to be investigated in future studies, ideally with chemicals of higher hydrophobicity.
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The aim of the present study was to evaluate the diurnal rhythm of melatonin concentration in blood and milk of dairy cows. Blood was sampled and the entire milk was removed every hour and melatonin concentration was measured throughout 24 hours in June in 12 dairy cows (around 16 hours daylight). Both, blood plasma and milk melatonin concentration showed a diurnal pattern with high levels during scotoperiod and low levels during photoperiod. Average blood plasma melatonin was 16.2 +/- 2.3 pg/mL during the photoperiod (0800-2200h), started to increase at 2100h, and reached a plateau at 2300h (16.0 +/- 4.4 pg/mL). Peak concentration was reached at 0100h (25.4 +/- 5.6 pg/mL). At 0700h melatonin decreased to baseline level again. The melatonin pattern in milk paralleled the pattern in blood. However, the concentration of melatonin was much lower in milk than in blood with a maximum concentration of 2.9 +/- 0.6 pg/mL at all tested time points.