Identification of Antioxidant Proteins With Deep Learning From Sequence Information

Antioxidant proteins have been found closely linked to disease control for its ability to eliminate excess free radicals. Because of its medicinal value, the study of identifying antioxidant proteins is on the upsurge. Many machine-learning classifiers have performed poorly owing to the nonlinear and unbalanced nature of biological data. Recently, deep learning techniques showed advantages over many state-of-the-art machine learning methods in various fields. In this study, a deep learning based classifier was proposed to identify antioxidant proteins based on mixed g-gap dipeptide composition feature vector. The classifier employed deep autoencoder to extract nonlinear representation from raw input. The t-Distributed Stochastic Neighbor Embedding (t-SNE) was used for dimensionality reduction. Support vector machine was finally performed for classification. The classifier achieved F1 score of 0.8842 and MCC of 0.7409 in 10-fold cross validation. Experimental results show that our proposed method outperformed the traditional machine learning methods and could be a promising tool for antioxidant protein identification. For the convenience of others' scientific research, we have developed a user-friendly web server called IDAod for antioxidant protein identification, which can be accessed freely at http://bigroup.uestc.edu.cn/IDAod/

Ischemic stroke risk in a southeastern Chinese population: Insights from 5-lipoxygenase activating protein and phosphodiesterase 4D single-nucleotide polymorphisms

Through a genome-wide linkage scan, an Icelandic genetic research group identified two new genes associated with ischemic stroke: the 5-lipoxygenase activating protein (ALOX5AP) gene and the phosphodiesterase 4D (PDE4D) gene. Because they regulate arterial inflammation and are closely related to atherosclerosis and plaque instability, these two mutated genes have become a research hotspot. The purpose of this study was to investigate the association between the risk of ischemic stroke and single-nucleotide polymorphisms (SNPs) in the ALOX5AP and PDE4D genes in a southeastern Chinese population. Methods: A total of 459 patients with stroke and 462 control individuals were recruited in the study. Four ALOX5AP SNPs (SG13S32, SG13S42, SG13S89, and SG13S114), and three PDE4D SNPs (SNP83, SNP87, and SNP45) were studied. SNP genotypes were determined by polymerase chain reaction amplification followed by allele-specific primer extension, with detection by matrix-assisted laser desorption/ionization time-of-flight. Data were coded and entered in SPSS Windows (version 16.0). Odds ratios and 95% confidence intervals were calculated using multivariate logistic regression analysis. Generalized multifactor dimensionality reduction (GMDR) analysis was applied to detect gene–gene interactions. Results: No statistically significant differences were found in the SNP genotype frequencies between cases and controls for the seven SNPs studied. GMDR analysis revealed no evidence of interactions between these seven polymorphic sites and an increased stroke risk. In addition, no association between different stroke types and the control group was detected. Results showed that only the ALOX5AP gene, and specifically the rs9551963 and rs4769060 genotypes, exhibited significantly different distributions between the stroke and control groups in female participants. Conclusion: No association was found between SNPs of ALOX5AP or PDE4D and the risk of overall ischemic stroke in a southeastern Chinese population. Interactions between these two genes were not risk factors for cerebral infarction. In atherothrombotic and small-artery disease subtypes, none of the seven SNPs was associated with any stroke risk; however, the ALOX5AP gene might be related to ischemic stroke incidence in females

Curcumin Reverses NNMT-Induced 5-Fluorouracil Resistance via Increasing ROS and Cell Cycle Arrest in Colorectal Cancer Cells

Nicotinamide N-methyltransferase (NNMT) plays multiple roles in improving the aggressiveness of colorectal cancer (CRC) and enhancing resistance to 5-Fluorouracil (5-FU), making it an attractive therapeutic target. Curcumin (Cur) is a promising natural compound, exhibiting multiple antitumor effects and potentiating the effect of 5-FU. The aim of the present study is to explore the effect of Cur on attenuating NNMT-induced resistance to 5-FU in CRC. A panel of CRC cell lines with different NNMT expressions are used to characterize the effect of Cur. Herein, it is observed that Cur can depress the expression of NNMT and p-STAT3 in CRC cells. Furthermore, Cur can induce inhibition of cell proliferation, G2/M phase cell cycle arrest, and reactive oxygen species (ROS) generation, especially in high-NNMT-expression CRC cell lines. Cur can also re-sensitize high-NNMT-expression CRC cells to 5-FU both in vitro and in vivo. In summary, it is proposed that Cur can reverse NNMT-induced cell proliferation and 5-FU resistance through ROS generation and cell cycle arrest. Given that Cur has long been used, we suppose that Cur is a promising anticancer drug candidate with minimal side effects for human CRC therapy and can attenuate NNMT-induced resistance to 5-FU

The Presence of Ascites Affects the Predictive Value of HVPG on Early Rebleeding in Patients with Cirrhosis

Background and Aims. Gastroesophageal variceal bleeding is a serious complication of portal hypertension in cirrhotic patients and could be predicted by hepatic venous pressure gradient (HVPG). However, whether the presence of ascites affects the prognostic value of HVPG for patients with acute variceal bleeding is still unknown. This retrospective study is aimed at investigating the influence of ascites on predictive performance of HVPG for early rebleeding in cirrhotic patients with acute variceal bleeding. Methods. In this retrospective study, a total of 148 patients with cirrhosis hospitalized for acute variceal bleeding who underwent HVPG measurement and endoscopic variceal ligation (EVL) for the prevention of rebleeding were included. The receiver operating characteristic curve (ROC) and logistical regression method were employed to analyze the predictive performance of HVPG for early rebleeding. The locally weighted scatterplot smoothing approach was adopted to assess the monotonicity between bleeding risk and HVPG. Results. A significantly higher HVPG level was observed in patients with early rebleeding compared to patients without rebleeding in the nonascites cohort. When using HVPG to predict early rebleeding, there was a lower area under curve in the ascites cohort compared to the nonascites cohort. HVPG was recognized as a risk factor for early rebleeding by a logistic regression model only in the nonascites cohort. An overall monotonicity in the trend of change in HVPG and risk for early rebleeding was observed in the nonascites cohort solely. Conclusion. The predictive value of HVPG for early rebleeding in patients with cirrhosis that developed acute variceal bleeding is hindered by the presence of ascites