Objective: Mild cognitive impairment (MCI) is a preclinical and transitional stage between healthy ageing and dementia. The purpose of our study was to investigate the recent pooled global prevalence of MCI.Methods: This meta-analysis was in line with the recommendations of Cochrane’s Handbook and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020. We conducted a comprehensive search using the PubMed, Embase, Web of Science, CNKI, WFD, VIP, and CBM from their inception to March 1, 2023. Quality assessment was guided by the Agency for Healthcare Research and Quality (AHRQ) methodology checklist. The pooled global prevalence of MCI was synthesized using meta-analysis via random effect model. Subgroup analyses were performed to examine considered factors potentially associated with MCI prevalence.Results: We identified 233 studies involving 676,974 individuals aged above 50 years. All the studies rated as moderated-to-high quality. The overall prevalence of MCI was 19.7% [95% confidence interval (95% CI): 18.3–21.1%]. Subgroup analyses revealed that the global prevalence of MCI increased over time, with a significant rise [32.1% (95% CI: 22.6–41.6%)] after 2019. Additionally, MCI prevalence in hospitals [34.0% (95% CI: 22.2–45.7%)] was higher than in nursing homes [22.6% (95% CI: 15.5–29.8%)] and communities [17.9% (95% CI: 16.6–19.2%)], particularly after the epidemic of coronavirus disease 2019 (COVID-19).Conclusion: The global prevalence of MCI was 19.7% and mainly correlated with beginning year of survey and sample source. The MCI prevalence increased largely in hospitals after 2019 may be related to the outbreak of COVID-19. Further attention to MCI is necessary in the future to inform allocation of health resources for at-risk populations.

The study focuses on the long-term prognosis of myocardial infarction (MI) influenced by neutrophil extracellular traps (NETs). It also aims to analyze and validate relative hub genes in this process, in order to further explore new therapeutic targets that can improve the prognosis of MI. We established a MI model in mice by ligating the left anterior descending branch (LAD) and conducted an 8-week continuous observation to study the dynamic changes in the structure and function of the heart in these mice. Meanwhile, we administered Apocynin, an inhibitor of NADPH Oxidase, which has also been shown to inhibit the formation of NETs, to mice undergoing MI surgery in order to compare. This study employed hematoxylin-eosin (HE) staining, echocardiography, immunofluorescence, and real-time quantitative PCR (RT-qPCR) to examine the impact of NETs on the long-term prognosis of MI. Next, datasets related to MI and NETs were downloaded from the GEO database, respectively. The Limma package of R software was used to identify differentially expressed genes (DEGs). After analyzing the "Robust Rank Aggregation (RRA)" package, we conducted a screening for robust differentially expressed genes (DEGs) and performed pathway enrichment analysis using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to determine the functional roles of these robust DEGs. The protein-protein interaction (PPI) network was visualized and hub genes were filtered using Cytoscape. Immunofluorescence and qPCR results showed an increase in the expression of Myeloperoxidase (MPO) at week 1 and week 8 in the hearts of mice after MI. HE staining reveals a series of pathological manifestations in the heart of the MI group during 8 weeks, including enlarged size, disordered arrangement of cardiomyocytes, infiltration of inflammatory cells, and excessive deposition of collagen fibers, among others. The utilization of Apocynin could significantly improve these poor performances. The echocardiography displayed the cardiac function of the heart in mice. The MI group has a reduced range of heart movement and decreased ejection ability. Moreover, the ventricular systolic movement was found to be abnormal, and its wall thickening rate decreased over time, indicating a progressive worsening of myocardial ischemia. The Apocynin group, on the contrary, showed fewer abnormal changes in the aforementioned aspects. A total of 81 DEGs and 4 hub genes (FOS, EGR1, PTGS2, and HIST1H4H) were obtained. The results of RT-qPCR demonstrated abnormal expression of these four genes in the MI group, which could be reversed by treatment of Apocynin. The NETs formation could be highly related to MI and the long-term prognosis of MI can be significantly influenced by the NETs formation. Four hub genes, namely FOS, EGR1, PTGS2, and HIST1H4H, have the potential to be key genes related to this process. They could also serve as biomarkers for predicting MI prognosis and as targets for gene therapy.

High-quality code comment is important to help developer review and comprehend source code. Inspired by the effectiveness of deep learning techniques in the NLP field, many studies focus on using the machine translation algorithm to automatically generate comment for the source code. Most of the current studies typically involve in collecting a large number of dataset regarding the function-comment pairs, and then encode the information (e.g., AST) from the whole function for training a generation model. Most of current studies indistinguishably encode every statement in a function, which may not be the best strategy for comment generation because each statement in a function plays different roles, and the non-core code statements may have no effect or even a negative effect on the comment generation. In this paper, we propose a flexible encoding strategy that highlights the most informative statements from the function, called beacon statements, for code comment generation. Specifically, the beacon statements are detected from the function according to their roles when human understanding program, and then a pre-training model is proposed to encode the knowledge of the beacon statements. At last, the knowledge of the beacon statements is transferring to a basic model for comment generation by sharing the training parameters. The encouraging experimental results demonstrate the feasibility and effectiveness of our comment generation model.