Immune checkpoint inhibitors (ICIs) are widely used in the treatment of malignant tumors, and their related immune-related adverse events (irAEs) have attracted increasing attention. This study reports the diagnosis and treatment process of a case of immune cystitis in a patient with hepatobiliary tract malignant tumor after treatment with pembrolizumab. The patient was admitted to the hospital due to frequent urination, urgency of urination and dysuria for 1 month. Previous repeated anti-infection treatments were ineffective. Combined with medical history, laboratory tests, imaging findings, cystoscopy and pathological results, the patient was clinically diagnosed with ICIs-associated immune cystitis (Pembrolizumab) ultimately. The patient's symptoms significantly improved after treatment with glucocorticoids. This case reindicates that clinicians need to improve awareness of ICI-related urinary system irAEs. Early identification and timely intervention can significantly improve patient prognosis.

Objective: To understand the awareness of chikungunya fever knowledge and its related factors among medical college students in Baise City, so as to provide a scientific basis to offer relevant courses and special education. Methods: From July to August 2025, 7 286 enrolled medical students were selected by a sampling method from a medical college in Baise City to participate in the questionnaire survey. The questionnaire covered epidemiological characteristics, clinical symptoms, and prevention/control knowledge of chikungunya fever. Statistical analyses including the Chi quare test and multivariate Logistic regression models were performed. Results: The overall awareness rate of chikungunya fever knowledge among the medical students was 18.89%. Among the knowledge items, the awareness rate of "the high incidence season" was the highest (84.05%), while that of "the infectious period" was the lowest (17.80%). Multivariate Logistic regression analysis showed that medical students with female (a OR= 1.37 , 95%CI =1.20- 1.57 ), the age for over 25 years old (a OR=1.76, 95%CI =1.05-2.93), whose father had a middle school educational level (a OR=1.18, 95%CI =1.05-1.31), and majored in preventive medicine (a OR=1.54, 95%CI =1.10-1.67) had relatively higher awareness rates of chikungunya fever knowledge (all P <0.05). In contrast, students of Zhuang ethnicity (a OR= 0.87 , 95%CI =0.76-0.98) and majoring in nursing (a OR=0.74, 95%CI =0.61-0.91) or pharmacy (a OR=0.70, 95%CI =0.52-0.95) had relatively lower awareness rates (all P <0.05). Conclusions The awareness rate of chikungunya fever related knowledge among medical college students in Baise City is relatively low. Schools should take targeted publicity measures to improve medical students awareness.

Objective: The cross sectional study aimed to identify predominant co-occurrence patterns among six common mental health issues in college students, so as to provide empirical basis for designing targeted interventions. Methods: From October 2024, a total of 9 837 students from 4 universities in Xiangtan City, Hunan Province, participated in the current study by multistage random cluster sampling method. Participants completed self report measures, including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7 item Scale (GAD-7), Young s Internet Addiction Diagnostic Questionnaire, the Adolescent Insomnia Symptom Self rating Scale, the Ottawa Self injury Inventory, and the Brief Community Assessment of Psychic Experiences Questionnaire. Demographic and co-occurrence characteristics were first compared using Chi square or trend Chi-square tests, followed by application of the Apriori algorithm to mine association rules for primary co-occurrence patterns. Results: The detection rate of co-occuring the common mental health issues was 46.44%. The detection rate was significantly higher in female than in male students (50.42%, 43.61%; χ 2=44.46) and in students from rural versus urban areas (47.22%, 44.60%; χ 2=5.67) (both P <0.05). Significant differences were observed among freshmen, sophomores, juniors, and seniors (46.63%, 48.35%, 45.05% , 43.66%, respectively; χ 2=9.22, P <0.05), although no statistically significant trend was detected ( χ 2 trend =3.75, P = 0.05 ). Association rule mining identified “anxiety + depression” “anxiety + psychotic experiences + depression” and “anxiety + sleep disorder + depression” as the combinations with the highest support. In addition, “anxiety+depression+Internet addiction+psychotic experiences =>sleep disorder (>= refered to the occurrence of the latter item under the condition that the former item occurs)” and “anxiety + depression+Internet addiction=>sleep disorder” were combinations with relatively high confidence. Conclusions Co-occurrence of these mental health issues among college students is high and exhibits diverse patterns. Strategies to address this burden should prioritize integrated interventions that target these specific combinations of factors.

Objective To identify immune cell-related biomarkers in lung adenocarcinoma (LUAD) using weighted gene co-expression network analysis (WGCNA). Methods Based on data from The Cancer Genome Atlas (TCGA) database, a gene co-expression network was constructed for the TCGA-LUAD dataset using the "WGCNA" R package, and genes were clustered into different modules. Concurrently, the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm was applied to the tumor samples in the TCGA-LUAD dataset. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to evaluate the biological functions of genes within the most significantly correlated module. Candidate hub genes from the key module were intersected with a protein-protein interaction (PPI) network to identify the final hub genes. The prognostic performance of these hub genes and their correlation with immune cell infiltration were validated using Kaplan-Meier curves and the Tumor IMmune Estimation Resource (TIMER) algorithm. Finally, a multivariate Cox regression analysis was conducted on the identified hub genes to construct a prognostic risk model. Results In the co-expression network, the brown module was found to be highly correlated with the ImmuneScore, StromalScore, and ESTIMATE Score. Five immune-related hub genes were identified: CD53, PLEK, SPI1, IL10RA, and C3AR1. Enrichment analysis of the brown module revealed that its genes were primarily enriched in GO terms such as "regulation of innate immune response" and KEGG pathways like the "NF-kappa B signaling pathway". Furthermore, the expression levels of these five hub genes were significantly and positively correlated with the infiltration abundance of various immune cells. The immune relevance of the model was validated by the Immunophenoscore (IPS) and the Tumor Immune Dysfunction and Exclusion (TIDE) score. Moreover, the established RiskScore demonstrated significant potential in predicting the response to immunotherapy. Conclusion These five immune-related key genes may serve as novel and effective potential therapeutic targets for LUAD immunotherapy, facilitating the development of personalized diagnosis and treatment strategies for patients with LUAD.

On the occasion of celebrating the 110th anniversary of the Chinese Medical Association, the authors take the Chinese Journal of Digestive Surgery, a leading Chinese journal under the excellent action plan for Chinese scientific and technological journals, as the research subject to systematically analyze practices in academic exchange and scientific innovation develop-ment models advocated by the Chinese Medical Association. Through establishing a pyramid-shaped academic ecosystem, implementing strategic guidance with standard outputs, and building collabo-rative empowerment mechanisms, the journal has achieved breakthrough improvements in academic influence and communication efficacy. The study reveals that Chinese scientific journals can effec-tively overcome traditional development constraints by deeply integrating with national strategies, reconstructing academic value chains, and innovating knowledge service models, thereby providing China-specific solutions for constructing world-class scientific journals.

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.

BACKGROUND:It is urgent to improve the study on the molecular mechanism of Ban's Culuan Zhuyun Decoction improving oocyte quality in polycystic ovary syndrome.OBJECTIVE:To observe the effects of Ban's Culuan Zhuyun Decoction on oocyte quality in a mouse model of polycystic ovary syndrome and to explore the underlying mechanisms of its intervention in polycystic ovary syndrome.METHODS:Subcutaneous injection of dehydroepiandrosterone sulfate was used to establish the polycystic ovary syndrome model in 21-day-old female Kunming mice,and the treatment was conducted for 21 consecutive days.The estrous cycle and pregnancy was recorded.ELISA was used to detect serum sex hormone levels.The rate of apoptosis in oocytes was detected using Annexin V staining.The level of reactive oxygen species in oocytes was detected using dichlorodihydrofluorescein diacetate.The condition of spindle bodies and chromosomes in oocytes were detected using the immunofluorescence method.Network pharmacology and molecular docking were used to verify the binding properties of Ban's Culuan Zhuyun Decoction core active components and oocyte maturation-related factors(growth differentiation factor 9 and bone morphogenetic protein 15).Real-time fluorescence quantitative PCR and western blot were used to detect the mRNA and protein expression levels of growth differentiation factor 9 and bone morphogenetic protein 15 in oocytes,respectively.RESULTS AND CONCLUSION:(1)Ban's Culuan Zhuyun Decoction core active components(quercetin,kaempferol,and β-sitosterol)showed good binding activities with growth differentiation factor 9 and bone morphogenetic protein 15.(2)Ban's Culuan Zhuyun Decoction ameliorated the estrous cycle,regulated serum hormone,increased the pregnancy,decreased the rate of apoptosis,declined the level of reactive oxygen species,diminished the rate of abnormal spindle assembly and chromosome loss(P<0.01,P<0.05);and promoted the mRNA and protein expression of growth differentiation factor 9 and bone morphogenetic protein 15(P<0.05).Therefore,Ban's Culuan Zhuyun Decoction may improve the oocyte quality and increase the fertility of polycystic ovary syndrome mice by regulating the gene expression of growth differentiation factor 9 and bone morphogenetic protein 15.

Elemene is widely recognized as an effective anti-cancer compound and is routinely administered in Chinese clinical settings for the management of several solid tumors,including non-small cell lung cancer(NSCLC).However,its detailed molecular mechanism has not been adequately demonstrated.In this research,it was demonstrated that elemene effectively curtailed NSCLC growth in the patient-derived xenograft(PDX)model.Mechanistically,employing high-throughput screening techniques and subsequent biochemical validations such as microscale thermophoresis(MST),microRNA-145-5p(miR-145-5p)was pinpointed as a critical target through which elemene exerts its anti-tumor effects.Inter-estingly,elemene serves as a binding stabilizer for miR-145-5p,demonstrating a strong binding affinity(dissociation constant(KD)=0.39±0.17 μg/mL)and preventing its degradation both in vitro and in vivo,while not interfering with the synthesis of the primary microRNA transcripts(pri-miRNAs)and precursor miRNAs(pre-miRNAs).The stabilization of miR-145-5p by elemene resulted in an increased level of this miRNA,subsequently suppressing NSCLC progression through the miR-145-5p/mitogen-activated pro-tein kinase kinase kinase 3(MAP3K3)/nuclear factor kappaB(NF-κB)pathway.Our findings provide a new perspective on revealing the interaction patterns between clinical anti-tumor drugs and miRNAs.

OBJECTIVE: To analyze the diversity of Duffy blood group gene among ethnic Hui population from Henan Province using PacBio long-read sequencing technique. METHODS: Randomly select 30 individuals with three generations of Hui ancestry from Henan as the study subjects. Full-length sequences of the Duffy blood group gene were obtained through PacBio long-read sequencing. Distribution of the predicted phenotype and genotype frequency were determined, and the linkage between Duffy haplotypes and variation sites was analyzed. Genetic diversity, natural selection pressure, and population genetic characteristics were evaluated. This study was approved by the Second Affiliated Hospital of Zhengzhou University (Ethics No. 2022223). RESULTS: The predicted Duffy blood group phenotype in the Henan Hui population was predominantly Fy(a+b-). Three novel SNPs in the FY*01 allele were identified, with a total frequency of 13.33%, among which FY*01.NEW1 (c.199C>T) was the most common. A total of 32 variant sites were identified, with 28 located in intronic regions, indicating that genetic diversity was primarily concentrated in introns. The Duffy blood group gene was under negative selection pressure (dN/dS < 1, Tajima's D, Fu and Li's D* and F* significantly deviated from 0), suggesting overall conservation. The allele frequencies of Duffy blood group in the Henan Hui population was similar to that of the Xinjiang Hui, Xinjiang Kazakh, Inner Mongolia Mongolian, and Yuncheng Han populations, but significantly different from those of most Han and other ethnic groups (P < 0.05). CONCLUSION This study revealed the characteristics of the Duffy blood group gene among the Henan Hui population and demonstrated the significant advantages of PacBio long-read sequencing technique in haplotype analysis, genetic diversity study, and novel mutation identification.
Female ; Humans ; Male ; Asian People/ethnology* ; China/ethnology* ; Duffy Blood-Group System/genetics* ; Ethnicity/genetics* ; Gene Frequency ; Genetic Variation ; Haplotypes ; Polymorphism, Single Nucleotide

Objective:To develop an artificial intelligence (AI)-based automatic scoring model for magnetic resonance imaging-detected extramural vascular invasion (AI-mrEMVI) and evaluate its performance and prognostic value in patients with rectal cancer.Methods:In this multicenter retrospective cohort study, a total of 2 501 rectal cancer patients from seven centers between November 2012 and December 2020 were included and divided into completely independent training ( n=1 830) and validation ( n=671) cohorts. A nnUNet-based AI-mrEMVI scoring model was constructed. Manual mrEMVI scores assigned by two radiologists served as the reference standard for accessing the accuracy of the AI-mrEMVI scoring. Kaplan-Meier survival analysis and Cox regression were used to evaluate the prognostic stratification ability of the AI-mrEMVI scores. The concordance index (C-index) was calculated to evaluate prognostic performance. Results:In the validation cohort, the manual mrEMVI scores were 0-2 in 425 patients (63.3%), 3 in 89 (13.4%), and 4 in 157 (23.4%). The AI-mrEMVI model identified 0-2 in 375 patients (55.9%), 3 in 95 (14.2%), and 4 in 201 (30.0%), with an overall accuracy of 81.1% (544/671, 95% CI 77.9%-84.0%). The 3-year disease-free survival (DFS) rates for patients with AI-mrEMVI scores of 0-2, 3, and 4 were 85.2%, 70.0%, and 58.2%, respectively, and the 5-year overall survival (OS) rates were 87.2%, 81.6%, and 62.6%, respectively (DFS: χ2=48.74, P<0.001; OS: χ2=30.04, P<0.001). Multivariable Cox regression showed that for DFS, AI-mrEMVI scores of 3 and 4 were associated with hazard ratios ( HR) of 1.75 (95% CI 1.11-2.77, P=0.016) and 2.65 (95% CI 1.86-3.78, P<0.001), respectively. For OS, an AI-mrEMVI score of 4 was associated with an HR of 2.56 (95% CI 1.62-4.03, P<0.001). The C-index values of the AI-mrEMVI scoring model for predicting DFS and OS were 0.647 (95% CI 0.608-0.686) and 0.650 (95% CI 0.598-0.702), respectively. Conclusion:The proposed AI-mrEMVI automatic scoring model demonstrated high diagnostic accuracy and performed favorably in predicting DFS and OS prognostic risk in patients with rectal cancer.