Research on Beef Skeletal Maturity Determination Based on Shape Description and Neural Network

Physiological maturity is an important indicator for beef quality. In traditional method, the maturity grade is determined by subjectively evaluating the degree of cartilage ossification at the tips of the dorsal spine of the thoracic vertebrae. This paper uses the computer vision to replace the artificial method for extracting object (cartilage and bone) regions. Hu invariant moments of object region were calculated as the regional shape characteristic parameters. A trained Hopfield neural network model was used for recognizing cartilage and bone area in thoracic vertebrae image based on minimum Euclidean distance. The result showed that the accuracy of network recognition for cartilage and bone region was 92.75% and 87.68%, respectively. For automatically maturity prediction, the accuracy of prediction was 86%. Algorithm proposed in this paper proved the image description and neural network modeling was an effective method for extracting image feature regions

Baicalin Normalizes Blood Glucose Level in Streptozotocin -induced Diabetic Rats

This study aimed to determine the effect of baicalin on insulin resistance, glucose absorption, and blood lipids in type 2 diabetic rat model. Diabetic rats were treated with baicalin (40, 80 mg/kg) for 40 days. The results showed that diabetic rats treated with baicalin resulted in a significant decrease in the concentration of plasma triglycerides and high-density lipoprotein cholesterol, improved the body weight. Furthermore, baicalin markedly decreased blood glucose level in the diabetic rats. The levels of plasma insulin and resistin exhibited significantly lower in the diabetic rats treated with baicalin than those of the model group. These findings suggest that baicalin can improve adipose metabolic disturbance in the experimental type 2 diabetic rats, can effectively ameliorate insulin resistance and plasma glucose transport by decreasing the levels of plasma resistin.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Baicalin Normalizes Blood Glucose Level in Streptozotocin -induced Diabetic Rats

This study aimed to determine the effect of baicalin on insulin resistance, glucose absorption, and blood lipids in type 2 diabetic rat model. Diabetic rats were treated with baicalin (40, 80 mg/kg) for 40 days. The results showed that diabetic rats treated with baicalin resulted in a significant decrease in the concentration of plasma triglycerides and high-density lipoprotein cholesterol, improved the body weight. Furthermore, baicalin markedly decreased blood glucose level in the diabetic rats. The levels of plasma insulin and resistin exhibited significantly lower in the diabetic rats treated with baicalin than those of the model group. These findings suggest that baicalin can improve adipose metabolic disturbance in the experimental type 2 diabetic rats, can effectively ameliorate insulin resistance and plasma glucose transport by decreasing the levels of plasma resistin.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Total alkaloids from Solanum Iyratum Thunb. inhibited hela cells proliferation through induction of apoptosis and cell cycle arrest

The object of the present study was to investigate the anticancer properties of total alkaloids from Solanum lyratum Thunb (SLT-A), including the inhibitory effect of SLT-A on HeLa cells and the apoptosis-inducing capacity in vitro. In our study, cytotoxicity was measured by the growth inhibition assay and detection of apoptosis was performed by Hoechst33324 and Tdt-mediated dUTP nick end labeling (TUNEL) staining assays. The in vitro cytotoxic studies were complemented by the cell cycle analysis and determination caspase-3 activity. Reverse transcription-polymerase chain reaction (RT-PCR) assay was applied on the expression of apoptosis-associated genes. The result showed that treatment of HeLa cells with SLT-A resulted in the growth inhibition effect, and the IC50 value was approximately 82 µg/ml. SLTA (80 µg/ml) induced more cell apoptosis of HeLa cells and accumulated the cells in the G2/M phase compared with the control cells. On the other hand, the expression of p53 and Bax gene was increased in the cells treated with SLT-A (80 µg/ml), with an increase in the activity of caspase-3, while Bcl-2 expression was not changed compared to the control cells. Our results demonstrated that SLT-A presented antiproliferative activity in HeLa cells and might be a potential anticancer drug.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Baicalin Normalizes Blood Glucose Level in Streptozotocin -induced Diabetic Rats

This study aimed to determine the effect of baicalin on insulin resistance, glucose absorption, and blood lipids in type 2 diabetic rat model. Diabetic rats were treated with baicalin (40, 80 mg/kg) for 40 days. The results showed that diabetic rats treated with baicalin resulted in a significant decrease in the concentration of plasma triglycerides and high-density lipoprotein cholesterol, improved the body weight. Furthermore, baicalin markedly decreased blood glucose level in the diabetic rats. The levels of plasma insulin and resistin exhibited significantly lower in the diabetic rats treated with baicalin than those of the model group. These findings suggest that baicalin can improve adipose metabolic disturbance in the experimental type 2 diabetic rats, can effectively ameliorate insulin resistance and plasma glucose transport by decreasing the levels of plasma resistin.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Comprehensive Analysis and Comparison on the Codon Usage Pattern of Whole Mycobacterium tuberculosis Coding Genome from Different Area

Phenomenon of unequal use of synonymous codons in Mycobacterium tuberculosis is common. Codon usage bias not only plays an important regulatory role at the level of gene expression, but also helps in improving the accuracy and efficiency of translation. Meanwhile, codon usage pattern of Mycobacterium tuberculosis genome is important for interpreting evolutionary characteristics in species. In order to investigate the codon usage pattern of the Mycobacterium tuberculosis genome, 12 Mycobacterium tuberculosis genomes from different area are downloaded from the GeneBank. The correlations between G3, GC12, whole GC content, codon adaptation index, codon bias index, and so on of Mycobacterium tuberculosis genomes are calculated. The ENC-plot, relationship between A3/(A3+T3) and G3/(G3+C3), GC12 versus GC3 plot, and the RSCU of overall/separated genomes all show that the codon usage bias exists in all 12 Mycobacterium tuberculosis genomes. Lastly, relationship between CBI and the equalization of ENC shows a strong negative correlation between them. The relationship between protein length and GC content (GC3 and GC12) shows that more obvious differences in the GC content may be in shorter protein. These results show that codon usage bias existing in the Mycobacterium tuberculosis genomes could be used for further study on their evolutionary phenomenon

Optimizing the Predictive Ability of Machine Learning Methods for Landslide Susceptibility Mapping Using SMOTE for Lishui City in Zhejiang Province, China

The main goal of this study was to use the synthetic minority oversampling technique (SMOTE) to expand the quantity of landslide samples for machine learning methods (i.e., support vector machine (SVM), logistic regression (LR), artificial neural network (ANN), and random forest (RF)) to produce high-quality landslide susceptibility maps for Lishui City in Zhejiang Province, China. Landslide-related factors were extracted from topographic maps, geological maps, and satellite images. Twelve factors were selected as independent variables using correlation coefficient analysis and the neighborhood rough set (NRS) method. In total, 288 soil landslides were mapped using field surveys, historical records, and satellite images. The landslides were randomly divided into two datasets: 70% of all landslides were selected as the original training dataset and 30% were used for validation. Then, SMOTE was employed to generate datasets with sizes ranging from two to thirty times that of the training dataset to establish and compare the four machine learning methods for landslide susceptibility mapping. In addition, we used slope units to subdivide the terrain to determine the landslide susceptibility. Finally, the landslide susceptibility maps were validated using statistical indexes and the area under the curve (AUC). The results indicated that the performances of the four machine learning methods showed different levels of improvement as the sample sizes increased. The RF model exhibited a more substantial improvement (AUC improved by 24.12%) than did the ANN (18.94%), SVM (17.77%), and LR (3.00%) models. Furthermore, the ANN model achieved the highest predictive ability (AUC = 0.98), followed by the RF (AUC = 0.96), SVM (AUC = 0.94), and LR (AUC = 0.79) models. This approach significantly improves the performance of machine learning techniques for landslide susceptibility mapping, thereby providing a better tool for reducing the impacts of landslide disasters

Investigation on the blurred image restoration based on brain‐inspired model

Abstract Though relatively good effect has been achieved by the image de‐blurring method based on deep learning, the existing methods still suffer from the problem of unclear restoration of the edges. Therefore, brain‐inspired image restoration model based on human attention and “fine vision” is proposed to improve the blind restoration quality of the image in this paper according to the response mechanism of the different cerebral cortices for high and low spatial resolutions. The designed brain‐inspired model consists of dual‐channel network available to realize the function of feature merger for low and high resolutions, which is used to extract the image edges with detailed information filtered out. Confirmatory experiment is implemented based on the blurred image in the data set of GOPRO, LIVE and set14. As per the result, the model proposed is available for relatively good restoration of blurred image and super‐resolution, as well as looking results by visual inspection

Non-invasive positive pressure ventilation offers greater improvement in COPD-related respiratory failure when combined with naloxone

To improve efficacy of non-invasive positive pressure ventilation (NPPV), this study investigated the combination of NPPV with naloxone in COPD patients with respiratory failure. One hundred four patients with COPD-related respiratory failure were enrolled prospectively and randomly divided into a control group treated with NPPV alone (n = 52) and an observation group treated with NPPV combined with 4.0 mg naloxone by continuous infusion (n = 52). At 3 and 5 days after the start of treatment, the respiratory mechanics, pulmonary function, and oxygen metabolism parameters were significantly improved in the NPPV + naloxone group compared to the NPPV alone group (p<0.05). Further, the improvements in the NPPV plus naloxone group were greater at day 5 than at day 3 (p<0.05). These findings indicate that non-invasive positive pressure ventilation combined with naloxone can more effectively improve respiratory mechanics, pulmonary function and oxygen metabolism of COPD patients with respiratory failure than NPPV alone, offering a new treatment approach.