Objective: To analyze the epidemiological characteristics of pulmonary tuberculosis (PTB) among college students in Yangzhou from 2020 to 2024, so as to provide a scientific basis for developing prevention and control strategies. Methods: An epidemiological investigation was conducted among 162 college students with PTB, and 7 134 of their contacts were screened. Data were obtained from the tuberculosis information management system and on campus screening records. Using descriptive epidemiological methods, trends in incidence, seasonal distribution, and bacteriological characteristics were analyzed. Results: From 2020 to 2024, the annual average incidence of pulmonary tuberculosis among college students in Yangzhou was 29.42 per 100 000, showing an overall fluctuating downward trend ( χ 2=12.36, P <0.01). Cases were mainly concentrated in summer and autumn, with the highest proportion in autumn (41.36%, 67/162), followed by summer (23.46%, 38/162). The proportion of etiologically positive cases increased from 37.21% in 2020 to 71.43% in 2024; among positive cases, the proportion of latent tuberculosis infection (LTBI) decreased from 66.67% (10/15) to 26.67% (4/15). The etiological positive rate was higher in females than in males ( χ 2= 11.76 , P <0.01). Comparison of screening methods showed that among index cases, the LTBI detection rate of the recombinant Mycobacterium tuberculosis fusion protein skin test (C-TST) was higher than that of the tuberculin skin test (TST), but the difference was not statistically significant ( χ 2=0.65, P =0.42); among close contacts, the detection rate of TST was higher than that of C-TST (15.1%,10.1%; χ 2=5.23, P <0.05). Conclusion From 2020 to 2024, the annual average incidence of pulmonary tuberculosis among college students in Yangzhou showed an overall fluctuating downward trend, with differences in TB infection screening methods and gender.

ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease （COPD） under disease-syndrome combination， thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations （≥2 times/year） and infrequent acute exacerbations （<2 times/year） according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression， and a nomogram model was constructed. The model performance was assessed based on the area under the curve （AUC）， calibration curves， and decision curve analysis （DCA）. ResultsThe differences in baseline characteristics between the frequent acute exacerbations group （1 196 cases） and infrequent acute exacerbations group （833 cases） were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors： body mass index （BMI）， hospitalization days， number of smoking years， place of residence， use of noninvasive ventilators， oxygen-demanding therapy， liver cirrhosis， use of systemic glucocorticosteroids， and traditional Chinese medicine syndrome （phlegm and stasis obstructing the lung）. The nomogram model showed good discrimination and calibration in both the training set （AUC=0.748） and validation set （AUC=0.774）. ConclusionThe risk prediction model for frequent acute exacerbations of COPD， integrating traditional Chinese medicine syndrome， constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.

OBJECTIVE: To screen factors affecting the prognosis of chronic myeloid leukemia (CML) patients, and construct a nomogram model for event-free survival (EFS). METHODS: To screen out meaningful variables by univariate and multivariate Cox regression analysis in CML patients, and construct a nomogram model using R software. The nomogram was validated using consistency index (C-index), receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), calibration curve, decision curve analysis (DCA), and risk stratification analysis. RESULTS: This study analyzed data from 116 CML patients. Univariate and multivariate Cox regression analysis demonstrated that age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and red blood cell distribution width (RDW) were independent prognostic factors of EFS. Subsequently, a nomogram was constructed based on the above predictors. The C-index of the nomogram was 0.733(95%CI : 0.676-0.790). The AUC values for predicting 1-, 3-, and 5-year EFS rate were 0.765, 0.855, and 0.827, respectively. The results of the calibration curve and DCA curve showed that the predictive model had good consistency, as well as strong clinical utility. The patients were stratified into high-risk group and low-risk group based on the total score of the model, there was a significant difference in EFS between the two groups (P < 0.001). CONCLUSION Age, peripheral blood basophil percentage, BCR-ABL1 ^IS at 3 months, and RDW were associated with the prognosis of CML patients. The nomogram model constructed in this study can accurately predict the prognostic status of CML patients, but its widespread application still requires external and prospective validation.
Nomograms ; Leukemia, Myelogenous, Chronic, BCR-ABL Positive/mortality* ; Proportional Hazards Models ; Erythrocyte Indices ; Risk Assessment/methods* ; Fusion Proteins, bcr-abl/genetics* ; Basophils ; Leukocyte Count ; Humans

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life

OBJECTIVE: To investigate the effect and mechanism of Shuangshi Tonglin Capsules (SSTL) in the treatment of prostate fibrosis (PF). METHODS: Human prostate stromal cells (WPMY-1) were used for in vitro experiments to establish PF cell models induced with estradiol (E₂). The cell proliferation, migration and clonogenic capacity were determined by cell counting kit-8, scratch assay, and crystal violet staining, respectively. Sprague-Dawley rats were used for in vivo experiments. The changes in histomorphology and organ index of rat prostate by SSTL were determined. Pathologic changes and collagen deposition changes in rat prostate were observed by haematoxylin and eosin (HE) and Masson staining. Enzyme-linked immunosorbent assay kits were used to determine changes in rat PF markers fibroblast growth factor-23 (FGF-23), E₂ and prostate specific antigen (PSA). Mechanistically, changes in oxidative stress indicators by SSTL were determined in WPMY-1 cells and PF rats. Then the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) and transforming growth factor-β1 (TGF-β1)/Smad pathway-related proteins as well as Nrf2 and TGF-β1 mRNA were further detected by Western blot or quantitative real-time polymerase chain reaction both in vivo and in vitro. RESULTS: In the efficacy study, SSTL significantly reduced the proliferation, migration, and clonogenic ability of cells, improved the morphology of the glandular tissue, significantly reduced the prostate index, reduced glandular fibrous tissue and collagen deposition, and resulted in a significant decrease in the levels of FGF-23, E₂ and PSA (P<0.01 or P<0.05). In the mechanistic study, SSTL ameliorated oxidative stress by significantly increasing superoxide dismutase and glutathione peroxidase levels and decreasing malondialdehyde level in WPMY-1 cells and rats (P<0.01 or P<0.05). SSTL significantly elevated the expressions of Nrf2, HO-1, NAD(P)H quinone oxidoreductase 1 (NQO-1), and Smad7 proteins in both cells and rats, and significantly decreased the expressions of TGF-β1, collagen I, α-smooth muscle actin and Smad4 proteins (P<0.01 or P<0.05). SSTL also elevated the content of Nrf2 mRNA and decreased the content of TGF-β1 mRNA in cells and rats (P<0.01 or P<0.05). The Nrf2 inhibitor ML385 was added in in vitro experiments to further validate the pathway relevance. CONCLUSION SSTL was effective in improving PF in vivo and in vitro, and its mechanism of action may function through the Nrf2/TGF-β1 signaling pathway.
Male ; NF-E2-Related Factor 2/metabolism* ; Animals ; Drugs, Chinese Herbal/therapeutic use* ; Signal Transduction/drug effects* ; Transforming Growth Factor beta1/metabolism* ; Rats, Sprague-Dawley ; Humans ; Fibrosis ; Prostate/drug effects* ; Cell Proliferation/drug effects* ; Capsules ; Cell Movement/drug effects* ; Oxidative Stress/drug effects* ; Rats

Early-life stress (ES) leads to cognitive dysfunction in female adolescents, but the underlying neural mechanisms remain elusive. Recent evidence suggests that the cell adhesion molecules NECTIN1 and NECTIN3 play a role in cognition and ES-related cognitive deficits in male rodents. In this study, we aimed to investigate whether and how nectins contribute to ES-induced cognitive dysfunction in female adolescents. Applying the well-established limited bedding and nesting material paradigm, we found that ES impairs recognition memory, suppresses prefrontal NECTIN1 and hippocampal NECTIN3 expression, and upregulates corticotropin-releasing hormone (Crh) and its receptor 1 (Crhr1) mRNA levels in the hippocampus of adolescent female mice. Genetic experiments revealed that the reduction of dorsal CA1 (dCA1) NECTIN3 mediates ES-induced object recognition memory deficits, as knocking down dCA1 NECTIN3 impaired animals' performance in the novel object recognition task, while overexpression of dCA1 NECTIN3 successfully reversed the ES-induced deficits. Notably, prefrontal NECTIN1 knockdown did not result in significant cognitive impairments. Furthermore, acute systemic administration of antalarmin, a CRHR1 antagonist, upregulated hippocampal NECTIN3 levels and rescued object and spatial memory deficits in stressed mice. Our findings underscore the critical role of dCA1 NECTIN3 in mediating ES-induced object recognition memory deficits in adolescent female mice, highlighting it as a potential therapeutic target for stress-related psychiatric disorders in women.
Animals ; Female ; Mice ; CA1 Region, Hippocampal/metabolism* ; Cell Adhesion Molecules/metabolism* ; CRF Receptor, Type 1/metabolism* ; Memory Disorders/etiology* ; Mice, Inbred C57BL ; Nectins/genetics* ; Receptors, Corticotropin-Releasing Hormone/antagonists & inhibitors* ; Recognition, Psychology/physiology* ; Stress, Psychological/complications*

Pyroptosis is an identified programmed cell death that has been highly linked to endoplasmic reticulum (ER) dynamics. However, the crucial proteins for modulating dynamic ER membrane curvature change that trigger pyroptosis are currently not well understood. In this study, a biotin-labeled chemical probe of potent pyroptosis inducer α-mangostin (α-MG) was synthesized. Through protein microarray analysis, reticulon-4 (RTN4/Nogo), a crucial regulator of ER membrane curvature, was identified as a target of α-MG. We observed that chemically induced proteasome degradation of RTN4 by α-MG through recruiting E3 ligase UBR5 significantly enhances the pyroptosis phenotype in cancer cells. Interestingly, the downregulation of RTN4 expression significantly facilitated a dynamic remodeling of ER membrane curvature through a transition from tubules to sheets, consequently leading to rapid fusion of the ER with the cell plasma membrane. In particular, the ER-to-plasma membrane fusion process is supported by the observed translocation of several crucial ER markers to the "bubble" structures of pyroptotic cells. Furthermore, α-MG-induced RTN4 knockdown leads to pyruvate kinase M2 (PKM2)-dependent conventional caspase-3/gasdermin E (GSDME) cleavages for pyroptosis progression. In vivo, we observed that chemical or genetic RTN4 knockdown significantly inhibited cancer cells growth, which further exhibited an antitumor immune response with anti-programmed death-1 (anti-PD-1). In translational research, RTN4 high expression was closely correlated with the tumor metastasis and death of patients. Taken together, RTN4 plays a fundamental role in inducing pyroptosis through the modulation of ER membrane curvature remodeling, thus representing a prospective druggable target for anticancer immunotherapy.
Pyroptosis/immunology* ; Humans ; Endoplasmic Reticulum/immunology* ; Animals ; Nogo Proteins/antagonists & inhibitors* ; Mice ; Cell Line, Tumor ; Xanthones/pharmacology* ; Neoplasms/pathology* ; Mice, Nude

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.