Baicalein is a flavonoid inhibitor of 12-lipoxygenase. Here, we investigated its effect on hydrogen peroxide-induced damage to NG108-15 cells. Hydrogen peroxide activated the mitochondrial apoptotic pathway, decreased Nrf2 expression, increased reactive oxygen species (ROS) levels, reduced viability, and increased cell death after 2-24 h treatment of NG108-15 cells. Co-treatment with hydrogen peroxide and baicalein completely suppressed the activation of mitochondrial apoptotic pathway by upregulating Nrf2 expression and reducing ROS stress and partially inhibited the effects on cell viability and cell death. Silencing of 12-lipoxygenase had a similar protective effect to baicalein on hydrogen peroxide-induced damage by blocking the hydrogen peroxide-induced decrease in Nrf2 expression and increase in ROS levels. Neither protective effect was altered by addition of 12-hydroxyeicosatetraenoic acid, the product of 12-lipoxygenase, suggesting that hydrogen peroxide induced damage via 12-lipoxygenase by another, as yet unknown, mechanism, rather than activating it. Co-treatment of cells with hydrogen peroxide and N-acetylcysteine or the Nrf2 inducer sulforaphane reduced hydrogen peroxide-induced damage in a similar fashion to baicalein, while the Nrf2 inhibitor retinoic acid blocked the protective effect of baicalein. Silencing Nrf2 also inhibited the protective effects of baicalein, sulforaphane, and N-acetylcysteine and resulted in high ROS levels, suggesting ROS elimination was mediated by Nrf2. Taken together our results suggest that baicalein protects cells from hydrogen peroxide-induced activation of the mitochondrial apoptotic pathway by upregulating Nrf2 and inhibiting 12-lipoxygenase to block the increase in ROS levels. Hydrogen peroxide also activates a second mitochondrial dysfunction independent death pathway which is resistant to baicalein.
The prediction of whether active NBA players can be inducted into the Hall of Fame (HOF) is interesting and important. However, no such research have been published in the literature, particularly using the artificial neural network (ANN) technique. The aim of this study is to build an ANN model with an app for automatic prediction and classification of HOF for NBA players. We downloaded 4728 NBA players’ data of career stats and accolades from the website at basketball-reference.com. The training sample was collected from 85 HOF members and 113 retired Non-HOF players based on completed data and a longer career length (≥15 years). Featured variables were taken from the higher correlation coefficients (<0.1) with HOF and significant deviations apart from the two HOF/Non-HOF groups using logistical regression. Two models (i.e., ANN and convolutional neural network, CNN) were compared in model accuracy (e.g., sensitivity, specificity, area under the receiver operating characteristic curve, AUC). An app predicting HOF was then developed involving the model’s parameters. We observed that (1) 20 feature variables in the ANN model yielded a higher AUC of 0.93 (95% CI 0.93–0.97) based on the 198-case training sample, (2) the ANN performed better than CNN on the accuracy of AUC (= 0.91, 95% CI 0.87–0.95), and (3) an ready and available app for predicting HOF was successfully developed. The 20-variable ANN model with the 53 parameters estimated by the ANN for improving the accuracy of HOF has been developed. The app can help NBA fans to predict their players likely to be inducted into the HOF and is not just limited to the active NBA players.
We present the first CE method for the separation and quantification of SMN1 and SMN2 genes. Spinal muscular atrophy (SMA) is an inherited neuromuscular disorder deleted or mutated in SMN1 gene and retained at least one copy of SMN2 gene. However, these two genes are highly homologous, differentiation and quantification of SMN1 and SMN2 are therefore required in diagnosis to identify SMA patients and carriers. We developed a fluorescence-labeled conformation-sensitive CE method to quantitatively analyze PCR products covering the variable position in the SMN1/SMN2 genes using a copolymer solution composed of hydroxyethylcellulose and hydroxypropylcellulose. The DNA samples included 24 SMA patients, 52 parents of SMA patients (obligatory carriers), and 255 controls. Those 331 samples were blind analyzed to evaluate the method, and the results compared with those obtained using denaturing HPLC (DHPLC). Validation of accuracy was performed by comparing the results with those of DHPLC. Nine of total samples showed different results. Diagnosis of one fetus DNA among them was related to abortion or not, which was further confirmed by gel electrophoresis and DNA sequencing. Our method showed good coincidence with them, and proved the misdiagnosis of DHPLC. This simple and reliable CE method is a powerful tool for clinical genotyping of large populations to detect carriers and SMA patients.
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