652 research outputs found
Curcumin ameliorates renal impairment in a diabetic rat model
Purpose: To investigate the molecular mechanisms of action of curcumin in regulating kidney injury in diabetic rats.Methods: Diabetes was induced in male Wistar rats by intraperitoneal administration of streptozotocin (STZ). The rats were divided into four groups, labelled as follows: blank control, positive control of curcumin-untreated STZ-rats, curcumin-treated STZ-rats (20 mg/kg), and curcumin-treated STZ-rats (50 mg/kg). After 24 weeks, blood glucose, HbA1c, mean arterial pressure (MAP), heart rates, and body weights were measured. Fasting blood samples were also collected for albumin, lipocalin-2, osteopontin, and kidney-injury-molecule 1 (KIM1) The samples were also evaluated by enzyme linked immunosorbent assay (ELISA). Rat kidneys were isolated for assessment of renal impairment by haematoxylin and eosin staining (H&E), TUNEL assays, polymerase chain reaction (PCR), and western blotting.Results: Compared with STZ group, STZ + Cur (50 mg/kg) group significantly decreased blood glucose (284.57 ± 4.28 mg/dL, p < 0.01 vs. STZ), HbA1c (5.22 ± 0.33 %, p < 0.01 vs. STZ), and MAP (76 ± 2 mmHg, p < 0.05 vs. STZ), heart rate (300 ± 6 bpm, p < 0.05 vs. STZ), and body weight (356 ± 6 g, p < 0.01 vs. STZ) were significantly increased. Kidney protein index was significantly increased, indicating improvement of renal pathological damage. The inflammatory and apoptotic cells were less than that of the STZ group in the renal tissues. The mRNA abundance and relative protein expression levels of Wnt 5a and β-catenin were also enhanced. Curcumin regulation of the Wnt signal pathway was inhibited by protease inhibitor, XAV-939.Conclusion: These results demonstrated that curcumin treatment in diabetic rats alleviates renal damage by regulating Wnt signal pathway.Keywords: Curcumin, Renal impairment, Diabetes, Wnt signal pathwa
Multivariate Regression and Variance in Concrete Curing Methods: Strength Prediction with Experiments
Because concrete strengths and quality are affected by various factors, multivariate regression models are often used to analyze the differences between predicted and target outputs. However, the variableness of a predicted output and how individual input parameters affect prediction reliabilities are still uncertain in practical applications, especially for the prediction of compressive strengths of concrete. This study aims to develop multivariate models for predicting concrete strengths and providing the variance analysis of prediction results by comparisons with experiment outcomes. First, this paper provides an in-depth examination of established variance analysis methods in the context of commonly used multivariate regression models. Then, based on Gaussian process regression, this study melds principal component analysis (PCA), linear discriminant analysis (LDA), and multivariate analysis of variance (MANOVA) to assess the variability in concrete strength prediction using different curing methods. This innovative approach proves effective in evaluating the precision of the correlation and regression models (R-squared values ≥ 0.9049). The comparison between prediction results and experiment outcomes shows that retaining heat in cylinders can make them become too hot and overestimate in-place concrete strength. This study improves the methodologies of regression modeling for variance analysis and improves the reliability of concrete strength prediction. Additionally, the outcomes of this research can help save a substantial amount of financial resources and time that are required to obtain experimental data on the strengths of concrete components
Deep Learning Model for Personalized Prediction of Positive MRSA Culture Using Time-Series Electronic Health Records
Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing antibiotic therapy. Our study introduced a deep learning model, PyTorch_EHR, which leverages electronic health record (EHR) time-series data, including wide-variety patient specific data, to predict MRSA culture positivity within two weeks. 8,164 MRSA and 22,393 non-MRSA patient events from Memorial Hermann Hospital System, Houston, Texas are used for model development. PyTorch_EHR outperforms logistic regression (LR) and light gradient boost machine (LGBM) models in accuracy (AURO
Enhancements of the Kronos Simulation Package and Database for Geometric Design Planning, Operations and Traffic Management in Freeway Networks/Corridors (Phase II)
This report summarizes the enhancement results of the KRONOS freeway traffic simulation package. KRONOS is a personal computer-based, dynamic freeway simulation software, which is based on the continuum flow modeling approach. Unlike other macroscopic simulation programs, KRONOS explicitly models interrupted flow behavior such as merging, diverging, and weaving. The resulting KRONOS version, v8.0, which operates under the MS-DOS® environment, can simulate two freeways merging/diverging with a common section for a total length up to 20 miles with eight lanes. The new multi-stage incident module can handle up to six capacity-variant stages, which allows evaluation of various management strategies. A spread-sheet formatted output file stores the simulated results of traffic parameters, such as flow, speed, and density. Separate output files also store the measures of effectiveness, such as delay and total travel time. The current version takes approximately three minutes to simulate a 20-mile section for one hour on an IBM-PC compatible with the Pentium-90 MHZ processor
Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-Level Optimization
Masked Autoencoder (MAE) is a notable method for self-supervised pretraining
in visual representation learning. It operates by randomly masking image
patches and reconstructing these masked patches using the unmasked ones. A key
limitation of MAE lies in its disregard for the varying informativeness of
different patches, as it uniformly selects patches to mask. To overcome this,
some approaches propose masking based on patch informativeness. However, these
methods often do not consider the specific requirements of downstream tasks,
potentially leading to suboptimal representations for these tasks. In response,
we introduce the Multi-level Optimized Mask Autoencoder (MLO-MAE), a novel
framework that leverages end-to-end feedback from downstream tasks to learn an
optimal masking strategy during pretraining. Our experimental findings
highlight MLO-MAE's significant advancements in visual representation learning.
Compared to existing methods, it demonstrates remarkable improvements across
diverse datasets and tasks, showcasing its adaptability and efficiency. Our
code is available at: https://github.com/Alexiland/MLOMA
A saúde mental é o fator mais importante que influencia a qualidade de vida de idosos deixados para trás quando as famÃlias emigram da China rural
OBJECTIVES: to investigate the quality of life and the associated factors on left behind elderly in rural China. METHOD: the research was conducted cluster sampling to select 456 elderly left behind when family members migrated out of rural China to participate in a cross-sectional study by completing a general data questionnaire and Quality of Life questionnaire. RESULTS: 91.5% of the elderly requested psychological counseling and education. For the elderly, scores for mental health (39.56±13.73) were significantly lower compared with Chinese standard data (61.6±13.7) (POBJETIVOS: investigar la calidad de vida y los factores asociados a los adultos mayores que se quedan en las zonas rurales de China. MÉTODO: la investigación se realizó por medio de muestreo por conglomerados para seleccionar 456 adultos mayores que se quedaron cuando los miembros de la familia emigraron de zonas rurales de China, para participar en un estudio de corte transversal, completando un cuestionario de datos generales y cuestionario de calidad de vida. RESULTADOS: el 91.5% de los adultos mayores solicitó asistencia psicológica y educación. Para los adultos mayores, las puntuaciones de salud mental (39.56±13.73) fueron significativamente más bajos en comparación con los datos estándar de China (61.6±13.7) (pOBJETIVOS: investigar a qualidade de vida e fatores associados de idosos deixados para trás na China rural. MÉTODO: foi realizada amostragem por conglomerado para selecionar 456 idosos deixados para trás quando os membros da famÃlia emigram da China rural. Este é um estudo transversal com preenchimento de um questionário de dados gerais e de qualidade de vida. RESULTADOS: 91,5% dos idosos convidados solicitaram aconselhamento e educação psicológicos. Para os idosos, os escores de saúde mental (39,56±13,73) foram significativamente menores em comparação aos dados padrões chineses (61,6±13,7) (
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