BACKGROUND: Hemorrhagic stroke (HS) is associated with significant disability and mortality. However, the relationship between meteorological factors and hemorrhagic stroke, as well as the potential moderating role of these factors, remains unclear. METHODS: Daily data on HS, air pollution, and meteorological conditions were collected from January 2015 to December 2021 in Ganzhou to analyze the relationship between meteorological factors and HS admissions. This analysis employed a time-stratified case-crossover design in conjunction with a distributional lag nonlinear model. Additionally, a bivariate response surface modelling was utilized to further investigate the interaction between meteorological factors and particulate matter. The study also stratified the analyses by gender and age. To investigate the potential impact of extreme weather conditions on HS, this study defined the 97.5th percentile as representing extremely high weather conditions, while the 2.5th percentile was classified as extremely low. RESULTS: In single-day lags, the risk of admissions for HS was significantly associated with extremely low temperature (lag 1-2 and lag 13-14), extremely low humidity (lag 1 and lag 9-12), and extremely high precipitation (lag 2-7). Females exhibited greater susceptibility to extremely low temperature than males within the single-day lag pattern in the subcomponent layer, with a maximum relative risk (RR) that was 7% higher. In the cumulative lag analysis, the risk of HS admissions was significantly associated with extremely high temperature (lag 0-8∼lag 0-14), extremely low humidity (lag 0-2∼lag 0-14), and extremely high precipitation (lag 0-4∼lag 0-14). Within the cumulative lag day structure of the subcomponent layer, both extremely low and extremely high temperature had a more pronounced effect on females and aged ≥65 years. The risk of HS admissions was positively associated with extremely high barometric pressure in the female subgroups (lag 0-1 and lag 0-2). The highest number of HS admissions occurred when high PM_2.5 concentrations coexisted with low precipitation. CONCLUSIONS Meteorological factors were significantly associated with the risk of hospital admissions for HS. Individuals who were female and aged ≥65 years were found to be more susceptible to these meteorological influences. Additionally, an interaction was observed between airborne particulate matter and meteorological factors. These findings contributed new evidence to the association between meteorological factors and HS.
China/epidemiology* ; Humans ; Female ; Male ; Aged ; Middle Aged ; Cross-Over Studies ; Hospitalization/statistics & numerical data* ; Adult ; Hemorrhagic Stroke/etiology* ; Meteorological Concepts ; Weather ; Particulate Matter/analysis* ; Air Pollution/adverse effects* ; Environmental Exposure/adverse effects* ; Aged, 80 and over ; Young Adult

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Infectious keratitis (IK) is a leading cause of blindness worldwide, primarily resulting from improper contact lens use, trauma, and a compromised immune response. The pathogenic microorganisms responsible for IK include bacteria, fungi, viruses, and Acanthamoeba. This review examines standard therapeutic agents for treating IK, including broad-spectrum empiric antibiotics for bacterial keratitis (BK), antifungals such as voriconazole and natamycin for fungal infections, and antiviral nucleoside analogues for viral keratitis (VK). Additionally, this review discusses therapeutic agents, such as polyhexamethylene biguanide (PHMB), for the treatment of Acanthamoeba keratitis (AK). The review also addresses emerging drugs and the challenges associated with their clinical application, including anti-biofilm agents that combat drug resistance and nuclear factor kappa-B (NF-κB) pathway-targeted therapies to mitigate inflammation. Furthermore, methods of Photodynamic Antimicrobial Therapy (PDAT) are explored. This review underscores the importance of integrating novel and traditional therapies to tackle drug resistance and enhance drug delivery, with the goal of advancing treatment strategies for IK.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

This paper explains the mechanism of the mutual switching between physiological sleep and wakefulness from the aspects of the sleep circadian system and the sleep homeostasis system. In the circadian rhythm system, with the suprachiasmatic nucleus as the core, the anatomical connections between the suprachiasmatic nucleusand various systems that affect sleep are summarized, starting from the suprachiasmatic nucleus, passing through the four pathways of the melatonin system, namely, subventricular area of the hypothalamus, the ventrolateral nucleus of the preoptic area, orexin neurons, and melatonin, then the related mechanisms of their regulation of sleep and wakefulness are expounded. In the sleep homeostasis system, with adenosine and prostaglandin D2 as targets, the role of hypnogen in sleep arousal mechanisms in regulation is also expounded.

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

Objective: To elucidate the biological basis of the heart qi deficiency (HQD) pattern, an in-depth understanding of which is essential for improving clinical herbal therapy. Methods: We predicted and characterized HQD pattern genes using the new strategy, TCM-HIN2Vec, which involves heterogeneous network embedding and transcriptomic experiments. First, a heterogeneous network of traditional Chinese medicine (TCM) patterns was constructed using public databases. Next, we predicted HQD pattern genes using a heterogeneous network-embedding algorithm. We then analyzed the functional characteristics of HQD pattern genes using gene enrichment analysis and examined gene expression levels using RNA-seq. Finally, we identified TCM herbs that demonstrated enriched interactions with HQD pattern genes via herbal enrichment analysis. Results: Our TCM-HIN2Vec strategy revealed that candidate genes associated with HQD pattern were significantly enriched in energy metabolism, signal transduction pathways, and immune processes. Moreover, we found that these candidate genes were significantly differentially expressed in the transcriptional profile of mice model with heart failure with a qi deficiency pattern. Furthermore, herbal enrichment analysis identified TCM herbs that demonstrated enriched interactions with the top 10 candidate genes and could potentially serve as drug candidates for treating HQD. Conclusion Our results suggested that TCM-HIN2Vec is capable of not only accurately identifying HQD pattern genes, but also deciphering the basis of HQD pattern. Furthermore our finding indicated that TCM-HIN2Vec may be further expanded to develop other patterns, leading to a new approach aimed at elucidating general TCM patterns and developing precision medicine.

Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies,and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs. Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells,with Spearman's rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results,facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets. Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm,four piv-otal genes were selected:coat protein(CP),kallikrein 3(KLK3),polymerase γ(POLG),and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation,maintenance of cellular metal ion balance,and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis,porphyrin metabolism,and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0,M1,M2,and resting dendritic cell were significantly different between groups,and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol,curcumin,and quercetin with KLK3 were 7,3,and 2,respectively.It shows that the interac-tions of resveratrol,curcumin,and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes. Conclusion Pivotal genes including CP,KLK3,POLG,and TRPV4,exhibited commendable significant prognostic value,and played a crucial role in the diagnostic assessment of OP.Resveratrol,curcumin,and quercetin,natural compounds found in TCM,showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.

Objective To explore the feasibility of harmonic waves analysis for observing morphological brain network changes in patients with depressive disorder(DD).Methods Whole brain 3D high resolution T1WI of 55 DD patients(DD group)and 46 normal controls(NC group)were acquired.Six kinds of morphological features brain network were constructed with FreeSurfer tool,including the number of brain region vertices,surface area,gray matter volume,average cortical thickness,Gaussian curvature and fold index.Laplace operator was applied to obtain common harmonic wave.The harmonic power of different morphological features and the gray matter volume in different brain regions were compared between groups.Results No significant difference of total harmonic energy was found between groups.The specific harmonic wave energies were significantly different between groups,including the number of brain region vertices corresponding to the 2nd,6th,15th,44th and 57th harmonic waves,surface area corresponding to the 2nd,6th,16th and 57th harmonic waves,gray matter volume corresponding to the 2nd,12th,13th,15th and 57th harmonic waves,average cortical thickness corresponding to the 2nd,19th,35th,36th and 44th harmonic waves,Gaussian curvature corresponding to the 34th,40th,54th and 57th harmonic waves,as well as fold index corresponding to the 5th,16th,21st and 57th harmonic waves.Gray matter volumes of transverse temporal gyrus in left hemisphere in DD group were significantly larger than that in NC group(t=2.900,P=0.004).Conclusion Harmonic waves analysis was feasible for observing morphological brain network changes in DD patients.

Objective:To explore the clinical application of Hisense Computer-Assisted Sur-gery System(CAS)in the perioperative period of hepatectomy for liver cancer.Methods:Clinical data of patients undergoing laparoscopic hepatectomy(LH)for liver cancer from January 2021 to December 2022 were collected.Patients were divided into three groups based on surgical difficulty(low,medium,high)and further stratified into CAS-assisted subgroup and control subgroup ac-cording to whether the CAS system was used.Demographic and perioperative data were com-pared among different groups.Results:A total of 317 patients'clinical data were collected,in-cluding 31 cases in the low difficulty group,132 cases in th medium difficulty group,and 154 cases in the high difficulty group,with 108 cases(34.1％)in the CAS-assisted subgroup and 209 cases(65.9％)in the control group.In the medium difficulty group,the CAS-assisted subgroup had shorter operation time,drainage tube duration,and postoperative hospital stay compared to the control group(P＜0.001),and the AFP levels at 1 month postoperatively in the CAS-assisted sub-group were lower than those in the control group(P＜0.001).In the high difficulty group,the CAS-assisted subgroup showed shorter operation time,drainage tube duration,and postoperative hospi-tal stay,less intraoperative blood loss,and lower AFP levels 1 month post-operation compared to the control group(P＜0.001 for all).Conclusion:Preoperative CAS in medium and high difficulty laparoscopic liver resections improves perioperative outcomes.Hisense CAS effectively assists general surgeons in accurately identifying the anatomical site of liver tumors,providing precise pre-operative simulation and intraoperative navigation,thereby optimizing surgical strategies for pa-tients.