ObjectiveTo observe the effect of Yifei Jianpi prescription on the of signal transducer and activator of transcription protein 1 （STAT1）/interferon regulatory factor 3 （IRF3） signaling pathway in a pneumonia model induced by lipopolysaccharide （LPS） and to explore the mechanism of Yifei Jianpi prescription in improving lung immune and inflammatory responses. MethodsSixty male SPF SD rats were used in this study. Ten rats were randomly assigned to the normal control group， and the remaining 50 were instilled with LPS in the trachea to establish a pneumonia model. After successful modeling， the rats were randomly divided into the model group， dexamethasone group （0.5 mg·kg^-1）， and Yifei Jianpi prescription high-dose （12 mg·kg^-1）， medium-dose （6 mg·kg^-1）， and low-dose （3 mg·kg^-1） groups， with 10 rats in each group. Treatment was administered once daily， and the normal control and model groups received the same volume of normal saline. After 14 days， flow cytometry was used to detect the classification of whole blood lymphocytes. Enzyme-linked immunosorbent assay （ELISA） was used to measure serum levels of immunoglobulin G （IgG）， immunoglobulin A （IgA）， immunoglobulin M （IgM）， and the content of tumor necrosis factor-α （TNF-α）， interleukin-8 （IL-8）， interleukin-6 （IL-6）， and interleukin-10 （IL-10） in alveolar lavage fluid （BALF）. Hematoxylin-eosin （HE） staining was used to observe lung tissue pathology and score the damage. Thymus weight， spleen weight， and wet-to-dry weight ratio （W/D） were recorded. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of STAT1， IRF3， IL-6， and interferon-alpha （IFN-α） in lung tissues， while Western blot was performed to assess the protein expression of STAT1， IRF3， IL-6， and IFN-α. ResultsCompared with the normal control group， the model group showed significantly increased proportion of B lymphocytes in peripheral blood， decreased proportions of NK cells and CD4⁺/CD8⁺ （P<0.05， P<0.01）， decreased serum levels of IgG and IgA， significantly increased IgM levels （P<0.01）， significantly elevated content of TNF-α， IL-6， and IL-8 in BALF， and significantly decreased IL-10 levels （P<0.01）. Lung tissue damage was evident， with significant increases in thymus and spleen weights and a higher W/D ratio （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly upregulated （P<0.05，P<0.01）. Compared with the model group， the Yifei Jianpi prescription groups showed significantly reduced proportions of B lymphocytes in peripheral blood， increased proportions of NK cells and CD4⁺/CD8⁺ ratios （P<0.05， P<0.01）， significantly increased serum levels of IgG and IgA， significantly decreased IgM levels （P<0.05， P<0.01）， significantly reduced levels of TNF-α， IL-6， and IL-8 in BALF， and significantly increased IL-10 levels （P<0.01）. Lung tissue damage was alleviated， thymus and spleen weights were significantly reduced， and the W/D ratio was markedly decreased （P<0.01）. The mRNA and protein expression of STAT1， IRF3， IFN-α， and IL-6 in lung tissues was significantly downregulated （P<0.05， P<0.01）. ConclusionYifei Jianpi prescription can alleviate lung tissue damage and improve immune and inflammatory responses in LPS-induced pneumonia rats. The mechanism may be related to the inhibition of STAT1/IRF3 signaling pathway activation.

Objective: To explore the influencing factors and network structure of aggressive behaviors among college students based on propensity score matching (PSM), so as to provide precise targeted interventions for the prevention and improvement of aggressive behaviors among college students. Methods: A total of 2 652 college students were selected by convenient sampling method from three colleges in Wuhan, Hubei Province in June 2023. Questionnaire surveys were carried out by using the Buss-Warren Aggression Questionnaire (BWAQ), Ruminative Responses Scale (RRS), Cognitive Emotion Regulation Questionnaire-Chinese Version (CERQ-C), Family APGAR Index (APGAR) ,Brief Fear of Negative Evaluation Scale (BFNES).By bias score matching (PSM) for 1∶1 matching, univariate and multivariate Logistic regression analysis, and network analysis were conducted on the college students. Results: College students with higher levels of ruminant thinking，non adaptive emotional regulation and fear of negative appraisal were more likely to have highly aggressive behaviors（ OR =1.14，1.18，1.06），and those with higher adaptive emotional regulation and family care index were more likely to have highly aggressive behaviors ( OR =0.88，0.82)( P < 0.01 ). Network structure was significantly different between the two groups ( M =0.27, P <0.05). The core affective factors of college students with high levels of aggressive behavior were brooding reflective pondering and symptom rumination( EI =3.50, 3.49, 3.48 )，low aggressive behavior college students core affective factors were adaptive emotion regulation growth and non adaptive emotion regulation( EI =4.37, 4.12, 4.08). Conclusion Factors affecting Chinese college students aggressive behaviors are of different characteristics on different behaviour types, and targeted interventions should be adopted to reduce aggressive behaviors of college students.

AIM: To investigate the changes in serum levels of trefoil factor 1(Tff1)and bone morphogenetic protein 4(BMP4)in patients with diabetic retinopathy, and to evaluate their diagnostic value for diabetic retinopathy.METHODS: From January 2022 to January 2024, 186 patients with type 2 diabetes were selected as the study group and divided into a retinopathy subgroup(52 cases)and a non-retinopathy subgroup(134 cases)based on the presence of retinopathy. Another 186 healthy volunteers who underwent physical examinations during the same period were chosen as the control group. Serum Tff1 and BMP4 levels were measured using the enzyme-linked immunosorbent assay(ELISA). Pearson analysis was used to assess the correlation between serum Tff1, BMP4 levels, and clinical data. Multivariate Logistic regression analysis was performed to identify factors influencing the development of retinopathy in type 2 diabetic patients. Receiver operating characteristic(ROC)curve analysis was conducted to evaluate the diagnostic value of serum Tff1 and BMP4 levels for retinopathy in type 2 diabetic patients.RESULTS: Compared to the control group, serum Tff1 levels were lower and BMP4 levels were higher in both retinopathy and non-retinopathy subgroups(all P<0.05). Specifically, serum Tff1 levels were lower and BMP4 levels were higher in the retinopathy subgroup than in the non-retinopathy subgroup(all P<0.05). Pearson analysis revealed that Tff1 levels in type 2 diabetes patients were negatively correlated with disease duration, glycated hemoglobin levels, and triglyceride levels, while BMP4 levels were positively correlated(all P<0.05). Multivariate Logistic regression analysis identified type 2 diabetes duration, glycated hemoglobin, triglycerides, Tff1, and BMP4 as influencing factors for retinopathy development in type 2 diabetes patients(all P<0.05). ROC curve analysis showed that the combined diagnosis of serum Tff1 and BMP4 had an area under the curve(AUC)of 0.901, which was significantly higher than that of Tff1 alone(Z=2.069, P=0.039)and BMP4 alone(Z=2.072, P=0.038).CONCLUSION: Serum Tff1 levels are decreased and BMP4 levels are increased in patients with diabetic retinopathy, and the combined detection of these two markers offers high diagnostic value for diabetic retinopathy.

This paper aims to discuss the construction and promotion strategy of medical care capacity framework based on the core literacy of palliative care， combining domestic and foreign research and clinical status. The research results show that it is particularly important to construct a framework of medical care competence based on palliative care. The core competencies required for palliative care include the ability to comprehensively evaluate and formulate personalized programs， effective communication skills， interdisciplinary teamwork skills， and the ability to continuously learn and improve themselves. The quality of care can be further improved if the above abilities are incorporated into the framework of medical care ability based on palliative care. However， there are a series of problems in the process of constructing the framework of palliative medical care capacity， such as difficult implementation of policy support， poor professionalism of talent team， single and irregular service model， low social acceptance， and difficult interdisciplinary cooperation and resource integration. After a detailed analysis of the problems， this paper puts forward the countermeasures to construct the framework of caring ability literacy based on palliative care. Effective countermeasures such as increasing policy support， cultivating comprehensive talents， developing diversified palliative care models， improving social recognition， and strengthening interdisciplinary cooperation and resource integration can effectively improve the core literacy and professional ability of medical care personnel， and then promote the development and improvement of palliative care services. In-depth discussion of the above contents can provide scientific reference for building a care model and literacy framework with palliative care as the core.

Objective: To analyze the influencing factors of aggressive behaviors in high school students, rank the importance of relevant variables with visual presentation, so as to provide new references for developing intervention strategies. Methods: In December 2024, a convenience sampling method was used to select 5 330 students from 5 high schools in Wuhan for an online questionnaire survey. The survey included the Buss-Perry Aggression Questionnaire (BPAQ), Interaction Anxiety Scale (IAS), Emotion Regulation Ability Scale, Inventory of Parent and Peer Attachment (IPPA), and a self designed general information questionnaire. Variables were screened using LASSO regression, followed by multivariate Logistic regression analysis. The Random Forest model was then employed to rank and visualize variable importance. Results: Univariate analysis and LASSO regression results indicated that gender, emotion regulation capability, paternal attachment quality, maternal attachment quality, maternal parenting style, paternal parenting style, parenting consistency, monthly household income per capita, school climate, relationship with classmates, interaction anxiety, and academic ranking were all significant variables (all P <0.01). Multivariate Logistic regression analysis identified the following as influencing factors of aggressive behaviors in high school students: emotional management ability ( OR=0.38, 95%CI =0.34-0.43), gender ( OR=0.83, 95%CI =0.75-0.93), mother attachment quality ( OR=0.89, 95%CI = 0.74 -1.07), father attachment quality ( OR=0.76, 95%CI = 0.66- 0.87), interaction anxiousness ( OR=1.58, 95%CI =1.40- 1.78 ), consistency of parenting styles of parents ( OR=1.40, 95%CI =1.21-1.62), school atmosphere ( OR=1.50, 95%CI =1.14-1.98), academic performance ranking (upper middle: OR=0.76, 95%CI =0.61-0.93; middle: OR=0.70, 95%CI =0.57-0.86) were the influencing factors of aggressive behavior in high school students (all P <0.05). The results of Random Forest showed that emotional management ability was the most important factor affecting aggressive behavior in high school students. Conclusion Emotion regulation capability is identified as the core predictor of adolescent aggressive behaviors, which can significantly reduce the incidence of aggressive behaviors through enhanced emotion management.

Objective: To analyze the factors associated with high level fear of negative evaluation (FNE) among junior high school students and to construct a nomogram risk prediction model, so as to provide scientific tools for psychological health intervention for junior high school students. Methods: A convenience sampling combined with cluster random sampling method was used to select 5 485 junior high school students from 4 cities (Wuhan, Huanggang, Xianning and Xiaogan) for an online questionnaire survey in March 2025. The total sample was randomly split into a training set ( n =3 839) and a validation set ( n =1 646). Univariate analysis was performed in the training set using Chi-square test and t-test. Variables with statistical significance were subsequently included in multivariate Logistic regression to identify independent predictors and to construct a nomogram based risk prediction model. The discriminative ability and clinical utility of the model were evaluated in the validation set using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: There were 1 649 junior high school students with low level FNE and 2 190 with high level FNE in the training set. The self control ability of junior high school students with lowlevel and high level FNE showed a statistically significant difference (23.96±3.96, 21.48±3.37, t=25.15, P < 0.01 ). Statistically significant differences in the detection rate of high level FNE were observed among junior high school students with different genders, family types, parenting styles, academic rankings, psychological flexibility, mobile phone addiction tendencies, emotional management training, exercise frequency, left behind experiences, and places of origin ( χ 2=82.01- 1 126.68 , all P <0.01). The results of Logistic regression analysis revealed that, the following factors were identified as significant factors influencing high level FNE among junior high school students:exercise frequency ( OR=0.21, 95%CI =0.17-0.26); parenting style ( OR=0.48, 95%CI =0.40-0.58); left behind experience ( OR=3.88, 95%CI =3.27-4.61); smartphone addiction proneness ( OR=2.19, 95%CI =0.89-0.93); self-control ability ( OR=0.91, 95%CI =0.89-0.93); and psychological flexibility ( OR=0.16, 95%CI =0.10-0.28) (all P <0.05). The AUC for the training and validation set were 0.88 (95% CI =0.87-0.89) and 0.87 (95% CI =0.85-0.89), respectively. The Hosmer-Lemeshow goodness of fit test yielded χ 2=8.57, 15.20 (both P >0.05). Conclusion The risk prediction model with high level FNE demonstrates good accuracy and can assist educators and parents in timely screening of junior high school students with high level FNE, thereby providing a basis for implementing targeted interventions.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective The aim of this study was to explore the natural history of Alzheimer's disease(AD)based on the multi-state Markov model and to provide methodological reference for the chronic diseases.Methods Based on the American public database ADNI,we constructed a three states Markov model to estimate the transition intensity,transition probability,influencing factors and sojourn time of different states.Survival curves and goodness of fit was obtained.Results Gender,age,FAQ,MMSE,CDRSB,ADAS13 and TMT-B-Time were important influencing factors in the natural history of AD.The mean sojourn time of NC and MCI was 7.502 and 11.621 years,respectively.Model fit can be accepted.Conclusion Multi-state Markov model has a good application value for the outcome prediction of multi-state chronic diseases such as AD.

Objective The shared random-effect model(SREM)was applied to study the reversion of mild cognitive impairment(MCI)to normal cognition(NC),to compare the predictive performance of different longitudinal cognitive markers for the reversion,and to evaluate the covariate effects of predictors.Methods The SREM model consisted of two sub-models:the longitudinal sub-model adopted linear mixed model to describe different longitudinal cognitive markers trajectories;and the survival sub-model used proportional risk model to fit the survival process.Goodness of fit was based on the log-likelihood value,and information criterion.AUC(area under the curve)was used to evaluate the predictive performance of different longitudinal cognitive markers,including MMSE,CDRSB,FAQ,ADAS11,ADAS13 and ADASQ4.Results There were 72(8.54%)of 843 patients with MCI reversed to NC at the end of follow-up.The log-likelihood value of the SREM model based on spline-PH-GH parameter distribution was the largest,and AIC and BIC were the smallest;the SREM model based on CDRSB score as longitudinal cognitive marker had the best fitting performance,with high AUC values at different times ranging from 0.797 to 0.852,and the lowest prediction error,ranging from 0.0427 to 0.0429.Age,gender,education level,marital status and APOEε4 gene affected the cognitive function and daily activity function.Six different longitudinal cognitive markers influenced the reversion.Conclusion CDR score was the best predictor of cognitive function and the reversion in MCI patients.Cognitive function and daily activity function can be used as dynamic monitoring indicators of MCI reversion.

To analyze the trends in disease burden and risk factors of depression among the elderly population in China from 1990 to 2021, and to provide a theoretical basis for the prevention, treatment, and policy-making of geriatric depression in China.