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

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss, with few effective treatments currently available. The multifactorial nature of AD, shaped by genetic, environmental, and biological factors, complicates both research and clinical management. Recent advances in artificial intelligence (AI) and multi-omics technologies provide new opportunities to elucidate the molecular mechanisms of AD and identify early biomarkers for diagnosis and prognosis. AI-driven approaches such as machine learning, deep learning, and network-based models have enabled the integration of large-scale genomic, transcriptomic, proteomic, metabolomic, and microbiomic datasets. These efforts have facilitated the discovery of novel molecular signatures and therapeutic targets. Methods including deep belief networks and joint deep semi-non-negative matrix factorization have contributed to improvements in disease classification and patient stratification. However, ongoing challenges remain. These include data heterogeneity, limited interpretability of complex models, a lack of large and diverse datasets, and insufficient clinical validation. The absence of standardized multi-omics data processing methods further restricts progress. This review systematically summarizes recent advances in AI-driven multi-omics research in AD, highlighting achievements in early diagnosis and biomarker discovery while discussing limitations and future directions needed to advance these approaches toward clinical application.

Polysaccharides are the important material basis of traditional Chinese medicine（TCM）， and have various pharmacological activities such as immunomodulation， antitumor and anti-aging. Due to the large molecular weight of TCM polysaccharides， their structural analysis and oral absorption mechanism are facing technical challenges， and the current research on their structure-activity relationships has made some breakthroughs， while the research on their oral absorption mechanisms is relatively slow. In-depth study of the oral absorption mechanism of TCM polysaccharides is not only crucial for the interpretation of their action pathways and efficacy in vivo， but also helpful for the interpretation of their pharmacological effects， rational clinical applications and the discovery of new targets. In recent years， the application of fluorescent labeling and isotopic labeling methods has provided new technical means for the oral absorption studies of polysaccharides， which has promoted the development of oral absorption studies of TCM polysaccharides. In this paper， we reviewed the oral absorption pathways and labeling techniques of TCM polysaccharides， and concluded that they can be absorbed orally through transmembrane， cellular bypass， and M-cell-mediated transport， of which transmembrane pathway is the main absorption pathway， and summarized the labeling reactions of four fluorescent labeling and isotopic labeling methods with TCM polysaccharides， which can provide references for evaluating the absorption pathways of TCM polysaccharides， screening active TCM polysaccharides， establishing pharmacodynamic models and comprehensively elucidating the mechanism of TCM polysaccharides.

Objective:To investigate effects of mesalazine(MS)on proliferation,apoptosis and inflammatory injury of cell model of ulcerative colitis(UC)induced by lipopolysaccharide(LPS),as well as transforming growth factor-β1(TGF-β1)/Smad signaling pathway effect in this study.Methods:Human colonic epithelial cells NCM-460 cultured in vitro were induced UC model by LPS,and divided into Con group(no treatment),LPS group(1 mg/L LPS),MS group(0.1,0.2,0.4 mg/L MS+1 mg/L LPS)and inhibitor group(10 μmol/L TGF-β1/Smad signaling pathway inhibitor LY2109761+0.2 mg/L MS+1 mg/L LPS).Cell morphology,proliferation,apoptosis and levels of inflammatory factors and TGF-β1/Smad pathway-related markers were examined by inverted microscope,EdU assay,Hoechst 33258 staining,ELISA and Western blot.Results:LPS treatment highly induced cell proliferation rate and Smad7 pro-tein level compared with Con group,while apoptotic cells,inflammatory factors TNF-α and IL-6,soluble interleukin-2 receptor(sIL-2R)release,as well as TGF-β1,p-Smad2,p-Smad3 protein expressions were increased;the above effects induced by LPS was reversed by MS in a dose-dependent manner(P<0.05).Compared with 0.2 mg/L MS group,NCM-460 cells proliferation rate and Smad7 expression were increased,while apoptotic cells,TNF-α and IL-6,sIL-2R releases,and TGF-β1,p-Smad2,p-Smad3 protein expressions were decreased(P<0.05).Conclusion:MS can attenuate LPS-induced apoptosis and inflammatory injury in NCM-460 cells,and this protection was possibly through suppressing TGF-β1/Smad signaling pathway.

Objective To investigate the therapeutic effect of Qiwei Zhigan prescription on two classic animal models of non-alcoholic steatohepatitis(NASH).Methods Methionine-choline-deficient(MCD)rat model and choline-deficient,L-amino acid-defined,high-fat and high cholesterol diet(CDAHFHC)mouse model were used.48 rats and 96 mice were randomly divided into 6 groups:control group,model group,Qiwei Zhigan prescription group(low,medium and high dose group),positive drug group.After 2 weeks of modeling,the drugs were administrated continuously for 28 days.The efficacy of Qiwei Zhigan prescription in the treatment of non-alcoholic steatohepatitis was evaluated by detecting the serum liver function,blood lipid biochemical index and liver tissue lipid levels of each group of animals,as well as by evaluating the liver histopathological changes.Results The gross anatomical morphology of the liver was improved by Qiwei Zhigan after oral administration of clinical equivalent dose or higher doses in two experimental animal models.The liver weight and liver index of NASH mice were reduced by the prescription.The levels of ALT,ALP and LDH in serum of NASH rats were decreased,and the level of HDL was increased.The levels of ALT,AST,TBIL,ALP,LDH and TG in serum of NASH mice were decreased,and the content of TG in liver was also decreased.The pathological damage of liver tissue was ameliorated,the inflammation of liver tissue was reduced,as well as the degree of ballooning of liver cells and the NAS score of the liver,and there was a certain dose-effect relationship between the groups;the proliferation of collagen fibers in the hepatic lobules and around the portal area of NASH mice was significantly reduced;the density of positive cells labeled by F4/80 was decreased,and the activation of Kupffer cells was alleviated.Conclusion Qiwei Zhigan prescription could effectively ameliorate the progression of two classic NASH models,and decrease the development trend from liver inflammation to liver fibrosis in NASH.

Objective:To investigate the genetic and evolutionary characteristics of hemagglutinin (HA) and neuraminidase (NA) genes of influenza B/Victoria (BV) virus in Xi′an city from 2019 to 2023.Methods:Twenty-five BV strains isolated from the Xi′an influenza surveillance network laboratory between 2019 and 2023 were collected. The HA and NA genes were sequenced using MiniSeq high-throughput sequencing platform. An evolutionary tree was constructed using bioinformatics software to analyze homology and mutation sites, and to predict N-glycosylation sites online. The antigenicity of the strains was analyzed through hemagglutination inhibition tests.Results:The BV influenza in Xi′an exhibited a distinct seasonal transmission pattern from 2019 to 2023, with peak prevalence occurring during the winter and spring seasons. The evolutionary analysis of the HA genes shows that the strains from Xi′an in 2019 belong to the V1A.3 branch, and the strains from 2021 to 2023 belong to the V1A.3a.2 branch. Analysis of antigenic sites showed that there were variations in 6 sites of 3 antigenic determinants in the HA proteins of the BV strains from 2021-2022 compared to 2019, and 2 sites of 1 antigenic determinant changed in the HA proteins in 2023 compared to 2021-2022. The evolutionary analysis of the NA genes indicates that the BV strains from Xi′an in 2019 belong to the A. 1.1 branch. By 2021 and 2022, it had evolved into the A. 1.2 clade, and by 2023, it had further evolved into the B clade and its derivatives, with no strains showing mutations associated with resistance to NA inhibitors. Antigenic analysis indicated that the majority of BV strains in Xi′an were similar to the strains included in the vaccine composition. Furthermore, glycosylation analysis showed that the potential N-glycosylation sites in the HA proteins of BV strains from 2021-2023 were reduced by one compared to those from 2019, and only a few strains from 2023 displayed alterations in the potential N-glycosylation sites of the NA proteins.Conclusions:The HA and NA genes of the BV strains from 2019 to 2023 are continuously mutating and evolving into new branches. Since 2021, V1A.3a.2 has become the dominant evolutionary branch of the HA genes, while the evolutionary branches of the NA genes from 2019 to 2023 have been continuously changing.

Objective:To evaluate the diagnostic efficacy and practicality of the Jaundice color card (JCard) as a screening tool for neonatal jaundice.Methods:Following the standards for reporting of diagnostic accuracy studies (STARD) statement, a multicenter prospective study was conducted in 9 hospitals in China from October 2019 to September 2021. A total of 845 newborns who were admitted to the hospital or outpatient department for liver function testing due to their own diseases. The inclusion criteria were a gestational age of ≥35 weeks, a birth weight of ≥2 000 g, and an age of ≤28 days. The neonate′s parents used the JCard to measure jaundice at the neonate′s cheek. Within 2 hours of the JCard measurement, transcutaneous bilirubin (TcB) was measured with a JH20-1B device and total serum bilirubin (TSB) was detected. The Pearson′s correlation analysis, Bland-Altman plots and the receiver operating characteristic (ROC) curve were used for statistic analysis.Results:Out of the 854 newborns, 445 were male and 409 were female; 46 were born at 35-36 weeks of gestational age and 808 were born at ≥37 weeks of gestational age. Additionally, 432 cases were aged 0-3 days, 236 cases were aged 4-7 days, and 186 cases were aged 8-28 days. The TSB level was (227.4±89.6) μmol/L, with a range of 23.7-717.0 μmol/L. The JCard level was (221.4±77.0) μmol/L and the TcB level was (252.5±76.0) μmol/L. Both the JCard and TcB values showed good correlation ( r=0.77 and 0.80, respectively) and agreements (96.0% (820/854) and 95.2% (813/854) of samples fell within the 95% limits of agreement, respectively) with TSB. The JCard value of 12 had a sensitivity of 0.93 and specificity of 0.75 for identifying a TSB ≥205.2?μmol/L, and a sensitivity of 1.00 and specificity of 0.35 for identifying a TSB ≥342.0?μmol/L. The TcB value of 205.2?μmol/L had a sensitivity of 0.97 and specificity of 0.60 for identifying TSB levels of 205.2 μmol/L, and a sensitivity of 1.00 and specificity of 0.26 for identifying TSB levels of 342.0 μmol/L. The areas under the ROC curve (AUC) of JCard for identifying TSB levels of 153.9, 205.2, 256.5, and 342.0 μmol/L were 0.96, 0.92, 0.83, and 0.83, respectively. The AUC of TcB were 0.94, 0.91, 0.86, and 0.87, respectively. There were both no significant differences between the AUC of JCard and TcB in identifying TSB levels of 153.9 and 205.2 μmol/L (both P>0.05). However, the AUC of JCard were both lower than those of TcB in identifying TSB levels of 256.5 and 342.0 μmol/L (both P<0.05). Conclusions:JCard can be used to classify different levels of bilirubin, but its diagnostic efficacy decreases with increasing bilirubin levels. When TSB level are ≤205.2 μmol/L, its diagnostic efficacy is equivalent to that of the JH20-1B. To prevent the misdiagnosis of severe jaundice, it is recommended that parents use a low JCard score, such as 12, to identify severe hyperbilirubinemia (TSB ≥342.0 μmol/L).

Objective:To standardize the management of auditory hallucination symptoms in inpatients with mental illness and develop an expert consensus on the management of auditory hallucinations in hospitalized psychiatric patients.Methods:From March 2023 to July 2023, the Mental Health Committee of the Chinese Nursing Association focused on the key issues in the management of auditory hallucinations symptoms in inpatients with mental illness, based on clinical practice, using literature analysis combined with the work experience of mental health experts, and formed the first draft of the expert consensus on the management of auditory hallucinations in inpatients with mental illness (hereinafter referred to as the consensus). Through 3 rounds of expert consultation and 3 rounds of expert demonstration meeting, the draft was adjusted, revised, and improved.Results:37 experts were included in the Delphi expert consultation, 1 male and 36 females with 39-67(51.48 ± 6.61) years old. The positive coefficients of experts in 3 rounds of Delphi expert consultations were all 100%, and the degrees of expert authority were 0.924, 0.938 and 0.949, respectively. The average importance value of each item was higher than 4.00, the variation coefficient of each item was less than 0.25. The Kendall harmony coefficient of the experts were 0.179, 0.195 and 0.198, respectively (all P<0.05). There were 15, 12, 12 experts in the first, seeond, third rounds of expert demonstration meeting. Finally, a consensus was reached on the recommendation of 4 parts, included auditory hallucination assessment, management format, symptom management implementation, and precautions. Conclusions:The consensus covers all parts of the management of auditory hallucination symptoms in hospitalized patients with mental disorders, which is practical and scientific. It is helpful to guide mental health professionals to standardize the management of auditory hallucination symptoms, improve the quality of nursing and ensure the safety of patients.

Objective To explore the value of machine learning(ML)models based on non-contrast CT(NCCT)radiomics features for predicting the severity of acute phase traumatic brain injury(TBI).Methods Totally 600 TBI patients were retrospectively collected as observation group,other 65 TBI patients were taken as external validation set,while 50 TBI patients were prospectively enrolled as prospective validation set.Patients in observation group were divided into high-risk subgroup(n=240)and low-risk subgroup(n=360)according to Glasgow outcome scale(GOS)at discharge.The severity of acute phase TBI in observation group was assessed by doctor A and B with the same criteria,then an artificial model was established based on clinical and NCCT data at the time of first diagnosis using logistic regression(LR)method for predicting the severity of acute phase TBI.Patients in observation group were divided into training set(n=420,including 168 in high-risk subgroup and 252 in low-risk subgroup)and test set(n=180,including 72 in high-risk subgroup and 108 in low-risk subgroup)at the ratio of 7∶3.Based on NCCT of training set,radiomics features were extracted and selected,and LR,support vector machine(SVM),random forest(RF)and K-nearest neighbor(KNN)were used to establish 4 ML models.The efficacies of the above models were validated in test set,external validation set(including 34 cases of high-risk and 31 cases of low-risk TBI)and prospective validation set(including 21 cases of high-risk and 29 cases of low-risk TBI),respectively.Results The area under the curve(AUC)of doctor A and B for evaluating the severity of acute phase TBI in observation group was 0.606 and 0.771,respectively,of artificial model was 0.824.Based on NCCT in training set,6 optimal radiomics features were selected to construct LR,SVM,RF and KNN ML models,with AUC of 0.983,0.971,0.970 and 0.984 in test set,respectively,while the AUC of artificial model was 0.708.The AUC of LR,SVM,RF,KNN ML models and artificial model in external validation set was 0.879,0.881,0.984,0.863 and 0.733,while in prospective validation set was 0.984,0.873,0.982,0.897 and 0.704,respectively.Conclusion ML models based on CT radiomics could effectively predict the severity of acute phase TBI.