Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized primarily by pancreatic β-cell dysfunction and insulin resistance.Beyond impaired glucose homeostasis,the glucotox-icity resulting from dysregulated glucose metabolism can lead to complications such as diabetic nephropa-thy,diabetic coronary heart disease,and diabetic cognitive dysfunction,posing severe threats to patients' health.Therefore,enhancing glucose metabolism and improving insulin resistance are critical strategies for T2DM prevention and treatment.Currently,the primary therapeutic approaches for T2DM include oral hypoglycemic agents and exogenous insulin injections.However,these methods face challenges such as unclear diagnostic markers,suboptimal therapeutic efficacy,and drug-related side effects.Consequently,the development of more precise and effective treatment strategies remains a top priority in clinical re-search.MicroRNA(miRNA)is a short non-coding RNA that regulates gene transcription.It has been reported to exhibit significant alterations even before the onset of overt pathological features like hypergly-cemia,suggesting their potential as early diagnostic biomarkers for T2DM to address current issues like delayed diagnosis and disease progression due to missed optimal treatment windows.Moreover,miRNAs can modulate the expression of pathways involved in glucose metabolism,thereby improving insulin resist-ance and maintaining glucose homeostasis while avoiding side effects associated with conventional thera-pies,such as reduced bone density and localized fat accumulation.This positions miRNAs as a promising avenue for precise and efficient T2DM management.This article systematically elucidates the molecular mechanisms by which miRNAs regulate glucose metabolism-related pathways,providing a theoretical foundation and reference for future clinical research.

Type 2 diabetes mellitus(T2DM)is a chronic metabolic disorder characterized primarily by pancreatic β-cell dysfunction and insulin resistance.Beyond impaired glucose homeostasis,the glucotox-icity resulting from dysregulated glucose metabolism can lead to complications such as diabetic nephropa-thy,diabetic coronary heart disease,and diabetic cognitive dysfunction,posing severe threats to patients' health.Therefore,enhancing glucose metabolism and improving insulin resistance are critical strategies for T2DM prevention and treatment.Currently,the primary therapeutic approaches for T2DM include oral hypoglycemic agents and exogenous insulin injections.However,these methods face challenges such as unclear diagnostic markers,suboptimal therapeutic efficacy,and drug-related side effects.Consequently,the development of more precise and effective treatment strategies remains a top priority in clinical re-search.MicroRNA(miRNA)is a short non-coding RNA that regulates gene transcription.It has been reported to exhibit significant alterations even before the onset of overt pathological features like hypergly-cemia,suggesting their potential as early diagnostic biomarkers for T2DM to address current issues like delayed diagnosis and disease progression due to missed optimal treatment windows.Moreover,miRNAs can modulate the expression of pathways involved in glucose metabolism,thereby improving insulin resist-ance and maintaining glucose homeostasis while avoiding side effects associated with conventional thera-pies,such as reduced bone density and localized fat accumulation.This positions miRNAs as a promising avenue for precise and efficient T2DM management.This article systematically elucidates the molecular mechanisms by which miRNAs regulate glucose metabolism-related pathways,providing a theoretical foundation and reference for future clinical research.

Objective The digital transformation of healthcare has made data-driven approaches critical for improving the quality and efficiency of medical services.This study aims to improve the quality of critical value management by a data-driv-en intervention.Methods This study built an advanced digital platform to precisely record the time-stamp of each step,from de-tection to solution.This platform also delivered real-time notifications of patient critical value information to doctors' mobile de-vices,thereby optimizing the critical value management.Data were collected via this platform.A cohort study was designed:March 2024 data(pre-go-live)served as the control group and May 2024 data(post-go-live)as the intervention group.Comple-tion rate,processing time,and the proportion of in-patient critical values which were entered into the electronic progress were compared.Results The critical-value completion rate rose from 97.1％to 100.0％,and the proportion of values processed within 30 min increased from 80.91％to 83.42％.Among alerts that required ≥30 min,median(IQR)processing time fell from 100.27(230.09)min in March 2024 to 91.07(169.73)min in May 2024.Median processing time shortened for both e-mergency and out-patient alerts,with the out-patient reduction being statistically significant(median-45 min,P=0.042).Conclusion The data-driven platform not only improved the critical-value management,but also enhanced the transparency and traceability,providing clinical decision support and enhancing patient safety.

Objective The digital transformation of healthcare has made data-driven approaches critical for improving the quality and efficiency of medical services.This study aims to improve the quality of critical value management by a data-driv-en intervention.Methods This study built an advanced digital platform to precisely record the time-stamp of each step,from de-tection to solution.This platform also delivered real-time notifications of patient critical value information to doctors' mobile de-vices,thereby optimizing the critical value management.Data were collected via this platform.A cohort study was designed:March 2024 data(pre-go-live)served as the control group and May 2024 data(post-go-live)as the intervention group.Comple-tion rate,processing time,and the proportion of in-patient critical values which were entered into the electronic progress were compared.Results The critical-value completion rate rose from 97.1％to 100.0％,and the proportion of values processed within 30 min increased from 80.91％to 83.42％.Among alerts that required ≥30 min,median(IQR)processing time fell from 100.27(230.09)min in March 2024 to 91.07(169.73)min in May 2024.Median processing time shortened for both e-mergency and out-patient alerts,with the out-patient reduction being statistically significant(median-45 min,P=0.042).Conclusion The data-driven platform not only improved the critical-value management,but also enhanced the transparency and traceability,providing clinical decision support and enhancing patient safety.

Objective:To analyze the epidemiological and clinical features of infectious diseases of the central nervous system (CNS).Methods:A cross-sectional study and analysis were conducted to summarize the epidemiological and clinical characteristics of 9 918 patients with CNS infectious diseases, who were diagnosed and treated at 29 hospitals across China from January 1, 2001 to December 31, 2020. Data collected included demographic data, clinical manifestations, health economic indicators, and prognostic outcomes.Results:Among the 9 918 collected cases of CNS infectious diseases, 5 559 were male (56.0%) and 4 359 were female (44.0%), with an onset age of 38 (25, 53) years. Education level: slightly more junior high school education (2 651 cases, 26.7%), and less elementary school education and below (2 181 cases, 22.0%) were found. Occupational distribution: farmers were found predominant (3 215 cases, 32.4%), followed by workers (1 826 cases, 18.4%) and students (1 633 cases, 16.5%). Clinical manifestations: headache (6 074 cases, 61.2%), fever (5 869 cases, 59.2%) and positive meningeal irritation signs (2 273 cases, 22.9%) were the 3 most common clinical manifestations, followed by nausea and (or) vomiting (2 095 cases, 21.1%), impaired consciousness (2 077 cases, 20.9%), psychiatric symptom (1 866 cases, 18.8%) and epilepsy (1 627 cases, 16.4%), etc., and cranial nerve involvement was found in 669 cases (6.7%). Major pathogens included viruses in 6 814 cases (68.7%), Mycobacterium tuberculosis in 1 677 cases (16.9%), common bacteria in 864 cases (8.7%), fungi in 254 cases (2.6%), spirochetes of syphilis in 183 cases (1.8%), parasites in 121 cases (1.2%), and rickettsiae in 5 cases (0.1%). Urban-rural distribution: slightly more cases were found in the countryside (5 418 cases, 54.6%) than in the towns (4 500 cases, 45.4%). Distribution of onset by season: 2 412 cases (24.3%) fell ill in spring, 2 835 cases (28.6%) in summer, 2 187 cases (22.1%) in fall, and 2 484 cases (25.0%) in winter. Health economics: the duration of hospitalization was 15 (8, 27) days, and the cost of hospitalization was 1.53 (0.91, 3.02)×10 000 yuan. Prognosis: 9 531 cases (96.1%) were cured or improved, and 92 cases (0.9%) died. Conclusions:The pathogens responsible for CNS infectious diseases are predominantly viruses. Although the incidence is slightly higher during the summer months, the overall seasonal pattern is not particularly pronounced. These infections are more commonly observed in young and middle-aged males and present with a diverse range of clinical manifestations, contributing to a significant disease burden.

Objective:To analyze the epidemiological and clinical features of infectious diseases of the central nervous system (CNS).Methods:A cross-sectional study and analysis were conducted to summarize the epidemiological and clinical characteristics of 9 918 patients with CNS infectious diseases, who were diagnosed and treated at 29 hospitals across China from January 1, 2001 to December 31, 2020. Data collected included demographic data, clinical manifestations, health economic indicators, and prognostic outcomes.Results:Among the 9 918 collected cases of CNS infectious diseases, 5 559 were male (56.0%) and 4 359 were female (44.0%), with an onset age of 38 (25, 53) years. Education level: slightly more junior high school education (2 651 cases, 26.7%), and less elementary school education and below (2 181 cases, 22.0%) were found. Occupational distribution: farmers were found predominant (3 215 cases, 32.4%), followed by workers (1 826 cases, 18.4%) and students (1 633 cases, 16.5%). Clinical manifestations: headache (6 074 cases, 61.2%), fever (5 869 cases, 59.2%) and positive meningeal irritation signs (2 273 cases, 22.9%) were the 3 most common clinical manifestations, followed by nausea and (or) vomiting (2 095 cases, 21.1%), impaired consciousness (2 077 cases, 20.9%), psychiatric symptom (1 866 cases, 18.8%) and epilepsy (1 627 cases, 16.4%), etc., and cranial nerve involvement was found in 669 cases (6.7%). Major pathogens included viruses in 6 814 cases (68.7%), Mycobacterium tuberculosis in 1 677 cases (16.9%), common bacteria in 864 cases (8.7%), fungi in 254 cases (2.6%), spirochetes of syphilis in 183 cases (1.8%), parasites in 121 cases (1.2%), and rickettsiae in 5 cases (0.1%). Urban-rural distribution: slightly more cases were found in the countryside (5 418 cases, 54.6%) than in the towns (4 500 cases, 45.4%). Distribution of onset by season: 2 412 cases (24.3%) fell ill in spring, 2 835 cases (28.6%) in summer, 2 187 cases (22.1%) in fall, and 2 484 cases (25.0%) in winter. Health economics: the duration of hospitalization was 15 (8, 27) days, and the cost of hospitalization was 1.53 (0.91, 3.02)×10 000 yuan. Prognosis: 9 531 cases (96.1%) were cured or improved, and 92 cases (0.9%) died. Conclusions:The pathogens responsible for CNS infectious diseases are predominantly viruses. Although the incidence is slightly higher during the summer months, the overall seasonal pattern is not particularly pronounced. These infections are more commonly observed in young and middle-aged males and present with a diverse range of clinical manifestations, contributing to a significant disease burden.

Objective To use network pharmacology to mine and predict the targets and related signaling pathways of Miaoyao Yiai Tang(Miao-Yi-Ai-Tang,MYAT)in the treatment of small cell lung cancer(SCLC).And animal experiments to verify its mechanism of action,to provide a theoretical basis for basic experiments and clinical applications.Methods The active ingredients of MYAT were obtained from the TCMSP database,combined with PubMed data,Swiss Target Prediction database and Uniprot database to obtain potential targets;SCLC-related genes were collected through the DrugBank database,Genecards database,OMIM database and TTD database,and the Venny 2.1 platform After obtaining the intersection genes of MYAT and SCLC,import them into the STRING database,construct a protein-protein interaction(PPI)network,use Cytoscape 3.9.1 software for visual analysis,and use Metascape database for GO enrichment analysis and KEGG pathway analysis,to predict the direct action target and signaling pathway of MYAT in the treatment of SCLC.Using AutoDock Tools 1.5.7 software for molecular docking to verify the close relationship between the two.For cytological experiment verification,the cultured cells were treated with MYAT and the expression of β-catenin,AXIN,c-myc was detected by qPCR,and the expression of β-catenin in the cells was detected by Western blot;animal experiments were established to establish a subcutaneous xenograft tumor model of lung cancer NCI-H446,to observe the effect of MYAT on tumor growth.Results A total of 65 effective components of MYAT,1368 SCLC genes,and 260 MYAT-SCLC intersection genes were obtained.Enrichment analysis showed that they were related to cancer pathways,PD-L1/PD-1 pathways,NF-κB pathways,Wnt and other signaling pathways.The results of molecular docking validation showed that the binding energies of active components and core target proteins were all<0 kJ·mol-1,which indicated that the protein could spontaneously bind to active components and be stable.Cell experiments showed that the expression levels of β-catenin,c-myc and AXIN mRNA were significantly down-regulated in the MYAT group(P<0.05).Animal experiments show that:MYAT can significantly inhibit the growth of tumors in vivo.Conclusion Miao-Yi-Ai-Tang can inhibit the proliferation of small cell lung cancer through Wnt/β-catenin signaling pathway.

Objective:To analyze the related literature of pulmonary rehabilitation research at home and abroad, understand its research focus and development trend, and provide a reference and basis for future pulmonary rehabilitation research.Methods:Literature related to pulmonary rehabilitation published in the database of Web of Science and China National Knowledge Infrastructure from January 2015 to February 2022 was retrieved, and the contents such as the number of articles published annually, authors, research institutions, and high-frequency keywords were visually analyzed by bibliometrics and CiteSpace software.Results:The number of articles published each year showed an obvious upward trend from 2015, and the number of Chinese documents was higher than that of English documents from 2019 to 2020. MARTIJN A SPRUIT was the author with the largest number of articles published in English, with a total of 65 articles published, with close cooperation among scholars. Che Guowei was the author with the largest number of articles published in Chinese literature, with 13 articles published in total. The cooperation among the authors was relatively lacking and scattered. The main research institutions abroad were universities, and the institution with the highest number of papers was Maastricht University in the Netherlands, with a total of 85 articles. The research institutions cooperated closely and formed a cooperation network. Hospitals were the main research institutions in China, and the thoracic surgery Department of West China Hospital of Sichuan University had the highest total number of publications, with 14 articles. The cooperation among institutions was not close, and there was a lack of cooperation with universities and scientific research institutions. Through keyword co-occurrence and clustering and timeline view analysis, it was concluded that the research hotspots in this field were pulmonary rehabilitation of patients with different chronic respiratory diseases, the influence of pulmonary rehabilitation on lung function and quality of life of patients with chronic obstructive pulmonary disease, and the intervention methods of pulmonary rehabilitation. The future trend was predicted as the clinical application value of pulmonary rehabilitation in the treatment of lung cancer.Conclusions:At present, pulmonary rehabilitation research is in a stable development period. However, the cooperation between domestic authors and institutions is not close enough compared with foreign countries. In the future, China should strengthen the communication and cooperation between research teams, and learn from foreign research results to further develop the application of pulmonary rehabilitation in lung cancer patients, to promote the development of pulmonary rehabilitation research in China.

Cancer cachexia is a complex metabolic syndrome which is characterized by muscle wasting,fat decomposition,unplanned weight loss,anorexia and immune dysfunction.Cachexia can significantly reduce the efficacy of antitumor therapies and increase treatment-related toxicity in cancer patients.It increases the symptom burden of patients,affects the quality of their life,ultimately shortens their survival time.This article reviews the research progress of diagnosis and treatment of cancer cachexia.

Objective: To evaluate the recognition of acute respiratory infection (ARI) by a pretrained model based on electronic medical records (EMRs). Methods: 38 581 EMRs were obtained from Chongqing University Three Gorges Hospital in December 2021. Bidirectional encoder representation from transformers (BERT) pretrained model was used to identify ARI in EMRs. The results of medical professionals were considered as the gold standard to calculate the sensitivity, specificity, Kappa value, and area under the curve of the receiver operating characteristic (AUC). Results: There were 3 817 EMRs in the test set, with 1 200 ARIs. A total of 1 205 cases were determined as ARI by the model, with a sensitivity of 92.67% (1 112/1 200) and a specificity of 96.45% (2 524/2 617). The model identified ARI with similar accuracy in males and females (AUCs 0.95 and 0.94, respectively), and was more accurate in identifying ARI cases in those aged less than 18 than in adults 18-59 and adults 60 and older (AUCs 0.94, 0.89 and 0.94, respectively). The current model had a better identification of ARIs in outpatient patients than that in hospitalized patients, with AUCs of 0.74 and 0.95, respectively. Conclusion: The use of the BERT pretrained model based on EMRs has a good performance in the recognition of ARI cases, especially for the outpatients and juveniles. It shows a great potential to be applied to the monitoring of ARI cases in medical institutions.
Adult ; Male ; Female ; Humans ; Electronic Health Records ; Respiratory Tract Infections/diagnosis* ; Outpatients