Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

Objective:To explore the feasibility and preliminary efficacy of domestic single-port robotic surgical system in the surgical treatment of thyroid cancer. Methods:Thyroid cancer patients who underwent domestic single-port robotic surgery in the Department of Head and Neck Surgery of Sichuan Cancer Hospital from June 2024 to January 2025 were prospectively included. Clinical data, oncological characteristics, and perioperative indicators were systematically collected. Results:A total of 7 patients were included, including 3 males and 4 females, with an age of （34.57±10.26） years. All procedures were successfully completed without conversion to open surgery. Operative time was（180.00±30.41） minutes. Blood loss was（5.00[15.00 ]）mL. Postoperative drainage volume was （167.86±130.95） mL. The postoperative pathological results were all thyroid papillary carcinoma. There were no system failures, no device-related complications and adverse events were observed during the operation and perioperative period. No tumor recurrence or metastasis was observed during the follow-up period. Conclusion:Preliminary data indicate that the domestic single-port robotic surgical system is safe and feasible for the surgical treatment of thyroid cancer, providing a practical basis for subsequent multi-disease, multi-center, and large-sample studies.
Humans ; Thyroid Neoplasms/surgery* ; Robotic Surgical Procedures/instrumentation* ; Male ; Female ; Adult ; Thyroidectomy/methods* ; Operative Time ; Middle Aged ; Prospective Studies

Extensive evidence has demonstrated that glucagon-like peptide-1 receptor agonists (GLP-1RAs) can ameliorate obesity. Our previous studies revealed that (Ex-4)₂-Fc, a long-acting GLP-1RA we developed, depends on the leptin pathway to treat obesity. However, the mechanisms linking (Ex-4)₂-Fc and leptin resistance remain largely unclear. To address this question, we explored the mechanism of GLP-1RAs from the perspective of the gut microbiota, as increasing evidence indicates an important link between the gut microbiota and obesity. This study aimed to explore the potential role of the gut microbiota in the treatment of GLP-1RAs. We found that (Ex-4)₂-Fc treatment reshaped obesity-induced gut microbiota disturbances and substantially increased the abundance of Akkermansia muciniphila (Am). In addition, (Ex-4)₂-Fc did not respond well in antibiotic-treated (ATB) Obese mice. Subsequent studies have shown that this defect can be overcome by gavage with Am. In addition, we found that Am enhanced (Ex-4)₂-Fc therapy by producing the metabolite inosine. Inosine regulates the macrophage adenosine A2A receptor (A2A) pathway to indirectly reduce leptin levels in adipocytes Thus, elucidating the role of metabolites in regulating the leptin pathway will provide new insights into GLP-1RAs therapy and may lead to more effective strategies for guiding the clinical use of antidiabetic agents.

Bacillus velezensis DJ1 exhibits broad-spectrum antagonistic activity against diverse phytopathogenic fungi, while its biocontrol mechanisms against Fusarium graminearum, the causal agent of maize stalk rot, remain poorly characterized. In this study, we integrated genomics and transcriptomics to elucidate the antifungal mechanisms of strain DJ1. The results demonstrated that DJ1 inhibited F. graminearum with the efficacy of 64.4%, while its polyketide crude extract achieved the control efficacy of 55% in pot experiments against this disease. Whole-genome sequencing revealed a single circular chromosome (3 929 792 bp, GC content of 47%) harboring 12 biosynthetic gene clusters for secondary metabolites, six of which encoded known antimicrobial compounds (macrolactin H, bacillaene, difficidin, surfactin, fengycin, and bacilysin). Transcriptomic analysis identified 243 differentially expressed genes (152 upregulated and 91 downregulated, P < 0.05), which were potentially associated with the antagonistic activity against F. graminearum. KEGG enrichment analysis highlighted activation (P < 0.05) of cysteine/methionine metabolism, pentose phosphate pathway, and polyketide biosynthesis pathways, indicating that DJ1 employed synergistic strategies involving antimicrobial compound synthesis, energy metabolism enhancement, and nutrient competition to suppress pathogens. This study provides a theoretical foundation for developing novel microbial resources and application technologies to combat phytopathogenic fungi.
Fusarium/drug effects* ; Bacillus/metabolism* ; Plant Diseases/prevention & control* ; Antifungal Agents/pharmacology* ; Genomics ; Zea mays/microbiology* ; Transcriptome ; Gene Expression Profiling ; Antibiosis ; Multigene Family ; Multiomics

Objective To investigate the therapeutic mechanism of Dingkun Dan(DKD)in polycystic ovary syndrome(PCOS)by examining the effects of microRNA-30d-5p on ovarian granulosa cells(GCs).Methods A PCOS rat model was established using dehydroepiandrosterone(DHEA).Normal rat GCs and PCOS rat GCs were cultured in vitro and divided into four groups:blank control group,model group,low-dose DKD group,and high-dose DKD group.After grouping,GCs viability was assessed using the methyl thiazolyl tetrazolium(MTT)assay,GCs apoptosis was analyzed by flow cytometry,and the gene expression of transforming growth factor β1(TGF-β1),Smad2,Smad3,and microRNA-30d-5p in GCs was measured by real-time polymerase chain reaction(RT-PCR),protein expression of TGF-β1,Smad2,and Smad3 in GCs was detected by Western Blot.Results Compared with the blank control group,the model group exhibited significantly decreased GCs viability,increased GCs apoptosis,upregulated mRNA and protein expression of TGF-β1,Smad2,and Smad3,and downregulated microRNA-30d-5p expression,the differences were statistically significant(P＜0.01).Compared with the model group,both low-and high-dose DKD groups showed increased GCs viability,reduced GCs apoptosis,downregulated mRNA and protein levels of TGF-β1 Smad2 and Smad3,elevated microRNA-30d-5p expression,and the differences were statistically significant(P＜0.05 or P＜0.01).Conclusion DKD promotes GCs proliferation by targeting Smad2 via microRNA-30d-5p,suggesting a potential therapeutic role in PCOS-related ovulatory dysfunction.

Objective:To discuss the effect of downregulating the proline-rich protein 11(PRR11)expression on drug resistance of the esophageal cancer drug resistant cells,and to clarify the related mechanism.Methods:The drug resistant cells EC9706/cisplatin(DDP)were established by incrementally stimulating the human esophageal cancer EC9706 cells with the increasing concentrations of DDP.The drug sensitivity of the EC9706/DDP cells was detected by MTT assay;the expression levels of PRR11 mRNA and protein in the EC9706/DDP cells and their parent EC9706 cells were detected by real-time fluorescence quantitative PCR(RT-qPCR)and Western blotting methods.The EC9706/DDP cells were divided into control group,sh-NC group(infected with sh-NC),sh-PRR11 group(infected with sh-PRR11),sh-NC+DDP group(infected with sh-NC and treated with 4 mg·L-1 DDP),and sh-PRR11+DDP group(infected with sh-PRR11 and treated with 4 mg·L-1 DDP).The expression levels of PRR11 mRNA in the cells in various groups were detected by RT-qPCR method;the expression levels of PRR11,phosphoinositide 3-kinase(PI3K)p110α,protein kinase B(AKT),phosphorylated AKT(p-AKT),P-glycoprotein(P-gp),and multidrug resistance-associated protein 1(MRP1)proteins in the cells in various groups were detected by Western blotting method;the apoptotic rates of the cells in various groups were detected by flow cytometry.Results:The DDP-resistant cell line EC9706/DDP was successfully obtained,and the drug resistance index was 7.23±0.86.Compared with the EC9706 cells,the expression levels of PRR11 mRNA and protein in the EC9706/DDP cells were increased(P<0.05).Compared with control and sh-NC groups,the expression levels of PRR11 mRNA and protein in the cells in sh-PRR11 group were decreased(P<0.05),and the 50%inhibitory concentration(IC50)of DDP was decreased(P<0.05).Compared with sh-NC group,the expression levels of PI3K p110α,p-AKT,P-gp,and MRP1 proteins in the cells in sh-NC+DDP and sh-PRR11 groups were decreased(P<0.05),and the apoptotic rate of the cells was increased(P<0.05).Compared with sh-NC+DDP group and sh-PRR11 group,the expression levels of PI3K p110α,p-AKT,P-gp,and MRP1 proteins in the cells in sh-PRR11+ DDP group were increased(P<0.05),and the apoptotic rate of the cells was increased(P<0.05).Conclusion:Downregulating the expression of PRR11 gene in the drug resistant EC9706/DDP cells can inhibit the expressions of drug resistance-related proteins,reverse the resistance to DDP,and induce the apoptosis;its mechanism may be related to the inhibition of activation of the PI3K/AKT signaling pathway.

Objective To investigate the relationship between serum tumor necrosis factor α stimulated gene 6(TSG-6)and collagen ⅩⅥ(col-16)levels and severity of the illness and clinical outcome in patients with active ulcerative colitis(UC).Methods A total of 79 patients with active UC admitted to the department of gastroenterology in the hospital from January 2020 to January 2023 were selected as the active UC group,56 patients with UC in remission who were similar in gender and age to the active UC group were selected as the remission UC group,and 60 healthy subjects who underwent physical examination in the hospital during the same period were selected as the control group.Patients with active UC were divided into mild group(n=25),moderate group(n=34)and severe group(n=20)according to the modified Mayo score.Patients with active UC were divided into good prognosis group(n=58)and poor prognosis group(n=21)according to colonoscopy results after 2 months of treatment.Serum TSG-6 and col-16 levels in each group were detected by enzyme-linked immunosorbent assay,Spearman rank correlation analysis was used to analyze the relation-ship between serum TSG-6 and col-16 levels and severity of the illness,and the influence of serum TSG-6 and col-16 levels on clinical outcome was analyzed by multivariate Logistic regression.Receiver operating charac-teristic(ROC)curve was used to evaluate the predictive value of serum TSG-6 and col-16 for poor prognosis in patients with active UC.Results The serum TSG-6 and col-16 levels in active UC group and remission UC group were higher than those in control group,and the serum TSG-6 and col-16 levels in active UC group were higher than those in remission UC group,the difference was statistically significant(P＜0.05).Serum TSG-6 and col-16 levels in severe group and moderate group were higher than those in mild group,and serum TSG-6 and col-16 levels in severe group were higher than those in moderate group,with statistical significance(P＜0.05).By Spearman rank correlation analysis,serum TSG-6 and col-16 in active UC patients were positively correlated with modified Mayo scores(rs=0.695、0.627,P＜0.05).Multivariate Logistic regression analysis showed that compared with＜159.32 ng/mL,patients with serum TSG-6 interquartile interval of 289.15-413.55 ng/mL and＞413.55 ng/mL had a higher risk of poor prognosis.ROC curve analysis results showed that the area under the curve of TG-6 and col-16 in predicting poor prognosis was 0.776 and 0.764,respective-ly.The predictive value of serum TG-6 and col-16 combined detection was better than that of single index(Z=3.392,4.218,P＜0.05).Conclusion The serum TSG-6 and col-16 levels in active UC patients are ab-normally elevated,which is closely related to severity of the illness and clinical outcome.The levels of serum TSG-6 and col-16 can be used as potential biochemical indicators to judge the disease and predict the clinical outcome.

Objective:To investigate the correlation between gender, age, blood collection time, season and changes in cTnT concentration.Methods:In this study, 3548 patients (non-cardiovascular diseases) in Zhongshan Hospital of Fudan University were selected from 1 January to 31 December 2019. The basic data of the patients were collected, including gender, age, time of blood collection, medical history, clinical diagnosis, and results of cTnT testing. 1 840 males and 1 708 females were finally enrolled, with an age distribution of 65 (53, 75) years. The distribution of the data was assessed using the Kolmogorov-Smirnov (K-S) test, where non-normally distributed data were expressed as M( Q1, Q3). The Mann-Whitney U-test was used to compare cTnT concentrations between men and women, and to analyse the influence of gender on cTnT results. The Kruskal-Wallis test was used to compare cTnT levels between gender groups, to analyse the correlation between different times of blood collection, seasons, and other factors and cTnT concentrations. Result:cTnT concentrations increased with age in both males and females over the age of 60 years. cTnT levels were highest in individuals over the age of 90 years (0.028 ng/ml in males and 0.018 ng/ml in females). cTnT levels were higher in males (0.012 ng/ml) than in females (0.009 ng/ml) in all age groups ( H=6.340, P<0.01). The concentrations of cTnT varied at different time points of blood collection. In both males and females, cTnT concentrations reached a maximum at 8:00 and 13:00 (0.013 ng/ml and 0.012 ng/ml, respectively). Analysis of the physiological effect of season on cTnT secretion showed that cTnT levels were generally higher in spring and winter(0.012 ng/ml) than in summer and autumn(0.010 ng/ml). Conclusions:cTnT concentration is influenced by gender, age, time of blood collection and season. When analysing cTnT results in clinical practice, the gender and age of the individual should be taken into account, as well as the time point of blood collection and seasonal factors.

Objective:To investigate the molecular mechanisms of chronic rhinosinusitis (CRS), to identify key cell subgroups and genes, to construct effective diagnostic models, and to screen for potential therapeutic drugs.Methods:Key cell subgroups in CRS were identified through single-cell transcriptomic sequencing data. Essential genes associated with CRS were selected and diagnostic models were constructed by hdWGCNA (high dimensional weighted gene co-expression network analysis) and various machine learning algorithms. Causal inference analysis was performed using Mendelian randomization and colocalization analysis. Potential therapeutic drugs were identified using molecular docking technology, and the results of bioinformatics analysis were validated by immunofluorescence staining. Graphpad Prism, R, Python, and Adobe Illustrator software were used for data and image processing.Results:An increased proportion of basal and suprabasal cells was observed in CRS, especially in eosinophilic CRS with nasal polyps (ECRSwNP), with P=0.001. hdWGCNA revealed that the "yellow module" was closely related to basal and suprabasal cells in CRS. Univariate logistic regression and LASSO algorithm selected 13 key genes ( CTSC, LAMB3, CYP2S1, TRPV4, ARHGAP21, PTHLH, CDH26, MRPS6, TENM4, FAM110C, NCKAP5, SAMD3, and PTCHD4). Based on these 13 genes, an effective CRS diagnostic model was developed using various machine learning algorithms (AUC=0.958). Mendelian randomization analysis indicated a causal relationship between CTSC and CRS (inverse variance weighted: OR=1.06, P=0.006), and colocalization analysis confirmed shared genetic variants between CTSC and CRS (PPH4/PPH3>2). Molecular docking results showed that acetaminophen binded well with CTSC (binding energy:-5.638 kcal/mol). Immunofluorescence staining experiments indicated an increase in CTSC +cells in CRS. Conclusion:This study integrates various bioinformatics methods to identify key cell types and genes in CRS, constructs an effective diagnostic model, underscores the critical role of the CTSC gene in CRS pathogenesis, and provides new targets for the treatment of CRS.