LncCat: An ORF attention model to identify LncRNA based on ensemble learning strategy and fused sequence information.

Background: Long non-coding RNA (lncRNA) is one of the most essential forms of transcripts, playing crucial regulatory roles in the development of cancers and diseases without protein-coding ability. It was assumed that short ORFs (sORFs) in lncRNA were weak to translate proteins. However, recent research has shown that sORFs can encode peptides, which increases the difficulty to identify lncRNA. Therefore, identifying lncRNAs with sORFs facilitates finding novel regulatory factors. Results: In this paper, we propose LncCat for identifying lncRNA based on category boosting (CatBoost) and ORF-attention features. LncCat combines five types of features to encode transcript sequences and employs CatBoost to build a prediction model. In addition, the visualization comparison reveals that the ORF-attention features between lncRNAs and protein-coding transcripts are significantly distinct. The comparison results show that LncCat outperforms competing methods on several benchmark datasets. For Matthew's Correlation Coefficient (MCC), LncCat achieves 0.9503, 0.9219, 0.8591, 0.8672, and 0.9047 on the human, mouse, zebrafish, wheat, and chicken datasets, with improvements ranging from 1.90% to 7.82%, 1.49-17.63%, 6.11-21.50%, 3.02-51.64% and 5.35-26.90%, respectively. Moreover, LncCat dramatically improves the MCC by at least 11.90%, 12.96% and 42.61% on sORF test datasets of human, mouse, and zebrafish, respectively. Conclusions: Experiments indicate that LncCat performs better both on long ORF and sORF datasets, and ORF-attention features show positive effects on predicting lncRNA. In brief, LncCat is a reliable method for identifying lncRNA. Additionally, a user-friendly web server is developed for academics at http://cczubio.top/lnccat.

Evaluation of Risk Factors for Chronic Obstructive Pulmonary Disease in the Middle-Aged and Elderly Rural Population of Northeast China Using Logistic Regression and Principal Component Analysis.

Purpose: To investigate the environmental, immune, and inflammatory factors associated with chronic obstructive pulmonary disease (COPD) in middle-aged and older Chinese individuals. Patients and Methods: A community-based case-control study was conducted among 471 patients with COPD and 485 controls. The information on COPD of the participants was collected through face-to-face interviews, and serum samples were measured at the laboratory. The main risk factors for COPD were analyzed using principal component analysis (PCA) and logistic regression. Results: Nine hundred and fifty-six respondents were included in the analysis. The results of the PCA-logistic regression analysis showed significant differences in the environmental factors, medical history, and serum C-reactive protein (CRP) levels between patients and controls. COPD was markedly more usual in those with smoking index >200 (OR, 1.42; 95% CI, 1.28-1.57); exposure to outdoor straw burning (OR, 1.64; 95% CI, 1.47-1.83); use of coal, wood, and straw indoors (OR, 2.31; 95% CI, 1.92-2.78); history of respiratory disease and coronary heart disease (OR, 3.58; 95% CI, 3.12-4.10), congestive heart failure (OR, 1.23; 95% CI, 1.09-1.38), and cerebrovascular disease (OR, 1.15; 95% CI,1.02-1.31); and higher serum level of CRP (OR, 1.20; 95% CI, 1.11-1.30). Compared to the logistic regression analysis, PCA logistic regression analysis identified more important risk factors for COPD. Conclusion: PCA-logistic regression analysis was first utilized to explore the influencing factors among rural residents in Northeast China Environmental aged 40 years and above, it was found that environmental factors, medical history, and serum CRP levels mainly affected the prevalence of COPD.

Effects of selenium deficiency and low protein intake on the apoptosis through a mitochondria-dependent pathway.

OBJECTIVE: Selenium(Se)is an important trace element for human health. Studies have shown that selenium deficiency and low protein(Pr) intake are the primary risk factors for Keshan disease.The relationship between the cardiac malfunction induced by these two risk factors and the mitochondria-mediated apoptotic pathway is poorly understood.This study aimed to determine the effect of selenium deficiency and low protein intake on the mitochondria-mediated apoptotic pathway. METHODS: In the present study, 120 weaning Wistar rats were randomly fed one of six different diets. The myocardial tissue sections were deparaffinized in water and subjected to hematoxylin-eosin staining. Mitochondrial changes in the myocardial tissue were observed and photographed using an H-7650 Hitachi transmission electron microscope. Levels of whole blood Se were measured using hydride generation atomic fluorescence spectrometry. Whole blood glutathione peroxidase (GSH-Px) activity was measured using a glutathione peroxidase cellular activity assay kit. Malondialdehyde (MDA), total-anti-oxidizing-capability(T-AOC)and reactive oxygen species(ROS)levels in serum and myocardial tissue were measured using MDA, T-AOC and ROS kits. Apoptosis was detected by immunohistochemistry. RESULTS: Experimental results showed that the selenium-deficient diet decreased serum selenium levels and GSH-PX activity, which caused severe cardiac dysfunction. Importantly, the levels of MDA and ROS in serum and myocardial tissue defects were significantly increased, where as total-anti-oxidizing-capability(T-AOC) levels were dramatically decreased as a result of the combination of selenium deficiency and low protein intake (P<0.05).The levels of cleaved caspase-9 and cleaved caspase-3 were enhanced, but the expression of B-cell lymphoma-2 (Bcl-2) was reduced (P<0.05). CONCLUSIONS: Our results suggest that selenium deficiency and low protein intake can cause oxidative stress in the myocardium and induce cell apoptosis via the mitochondria-mediated pathway.