7 resultados para Coastal sensitivity mapping

em Repositório da Produção Científica e Intelectual da Unicamp


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To determine if magnesium deficiency aggravates the effects of a high-fat diet in growing rats in terms of obesity, lipid profile and insulin resistance. The study population comprised 48 newly weaned male Wistar Hannover rats distributed into four groups according to diet, namely, control group (CT; n = 8), control diet provided ad libitum; pair-feeding control group (PF; n = 16), control diet but in the same controlled amount as animals that received high-fat diets; high-fat diet group (HF; n = 12), and magnesium-deficient high-fat diet group (HFMg(-); n = 12). The parameters investigated were adiposity index, lipid profile, magnesium status, insulin sensitivity and the phosphorylation of proteins involved in the insulin-signaling pathway, i.e. insulin receptor β-subunit, insulin receptor substrate 1 and protein kinase B. The HF and HFMg(-) groups were similar regarding gain in body mass, adiposity index and lipid profile, but were significantly different from the PF group. The HFMg(-) group exhibited alterations in magnesium homeostasis as revealed by the reduction in urinary and bone concentrations of the mineral. No inter-group differences were observed regarding glucose homeostasis. Protein phosphorylation in the insulin-signaling pathway was significantly reduced in the high-fat groups compared with the control groups, demonstrating that the intake of fat-rich diets increased insulin resistance, a syndrome that was aggravated by magnesium deficiency. Under the experimental conditions tested, the intake of a magnesium-deficient high-fat diet led to alterations in the insulin-signaling pathway and, consequently, increased insulin resistance.

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The search for an Alzheimer's disease (AD) biomarker is one of the most relevant contemporary research topics due to the high prevalence and social costs of the disease. Functional connectivity (FC) of the default mode network (DMN) is a plausible candidate for such a biomarker. We evaluated 22 patients with mild AD and 26 age- and gender-matched healthy controls. All subjects underwent resting functional magnetic resonance imaging (fMRI) in a 3.0 T scanner. To identify the DMN, seed-based FC of the posterior cingulate was calculated. We also measured the sensitivity/specificity of the method, and verified a correlation with cognitive performance. We found a significant difference between patients with mild AD and controls in average z-scores: DMN, whole cortical positive (WCP) and absolute values. DMN individual values showed a sensitivity of 77.3% and specificity of 70%. DMN and WCP values were correlated to global cognition and episodic memory performance. We showed that individual measures of DMN connectivity could be considered a promising method to differentiate AD, even at an early phase, from normal aging. Further studies with larger numbers of participants, as well as validation of normal values, are needed for more definitive conclusions.

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Dulce de leche samples available in the Brazilian market were submitted to sensory profiling by quantitative descriptive analysis and acceptance test, as well sensory evaluation using the just-about-right scale and purchase intent. External preference mapping and the ideal sensory characteristics of dulce de leche were determined. The results were also evaluated by principal component analysis, hierarchical cluster analysis, partial least squares regression, artificial neural networks, and logistic regression. Overall, significant product acceptance was related to intermediate scores of the sensory attributes in the descriptive test, and this trend was observed even after consumer segmentation. The results obtained by sensometric techniques showed that optimizing an ideal dulce de leche from the sensory standpoint is a multidimensional process, with necessary adjustments on the appearance, aroma, taste, and texture attributes of the product for better consumer acceptance and purchase. The optimum dulce de leche was characterized by high scores for the attributes sweet taste, caramel taste, brightness, color, and caramel aroma in accordance with the preference mapping findings. In industrial terms, this means changing the parameters used in the thermal treatment and quantitative changes in the ingredients used in formulations.

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The evolution and population dynamics of avian coronaviruses (AvCoVs) remain underexplored. In the present study, in-depth phylogenetic and Bayesian phylogeographic studies were conducted to investigate the evolutionary dynamics of AvCoVs detected in wild and synanthropic birds. A total of 500 samples, including tracheal and cloacal swabs collected from 312 wild birds belonging to 42 species, were analysed using molecular assays. A total of 65 samples (13%) from 22 bird species were positive for AvCoV. Molecular evolution analyses revealed that the sequences from samples collected in Brazil did not cluster with any of the AvCoV S1 gene sequences deposited in the GenBank database. Bayesian framework analysis estimated an AvCoV strain from Sweden (1999) as the most recent common ancestor of the AvCoVs detected in this study. Furthermore, the analysis inferred an increase in the AvCoV dynamic demographic population in different wild and synanthropic bird species, suggesting that birds may be potential new hosts responsible for spreading this virus.

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Mapping of elements in biological tissue by laser induced mass spectrometry is a fast growing analytical methodology in life sciences. This method provides a multitude of useful information of metal, nonmetal, metalloid and isotopic distribution at major, minor and trace concentration ranges, usually with a lateral resolution of 12-160 µm. Selected applications in medical research require an improved lateral resolution of laser induced mass spectrometric technique at the low micrometre scale and below. The present work demonstrates the applicability of a recently developed analytical methodology - laser microdissection associated to inductively coupled plasma mass spectrometry (LMD ICP-MS) - to obtain elemental images of different solid biological samples at high lateral resolution. LMD ICP-MS images of mouse brain tissue samples stained with uranium and native are shown, and a direct comparison of LMD and laser ablation (LA) ICP-MS imaging methodologies, in terms of elemental quantification, is performed.

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PURPOSE: To compare intraocular pressure (IOP) rise in normal individuals and primary open-angle glaucoma patients and the safety and efficacy of ibopamine eye drops in different concentrations as a provocative test for glaucoma. METHODS: Glaucoma patients underwent (same eye) the ibopamine provocative test with two concentrations, 1% and 2%, in a random sequence at least 3 weeks apart, but not more than 3 months. The normal individuals were randomly submitted to one of the concentrations of ibopamine (1% and 2%). The test was considered positive if there was an IOP rise greater than 3 or 4 mmHg at 30 or 45 minutes to test which subset of the test has the best sensitivity (Se)/specificity (Sp). RESULTS: There was no statistically significant difference in any of the IOP measurements, comparing 1% with 2% ibopamine. The IOP was significantly higher at 30 and 45 minutes with both concentrations (p<0.001). The best sensitivity/specificity ratio was achieved with the cutoff point set as greater than 3 mmHg at 45 minutes with 2% ibopamine (area under the ROC curve: 0.864, Se: 84.6%; Sp:73.3%). All patients described a slight burning after ibopamine's instillation. CONCLUSION: 2% ibopamine is recommended as a provocative test for glaucoma. Because both concentrations have similar ability to rise IOP, 1% ibopamine may be used to treat ocular hypotony.

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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.