Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.

Background In the context of the innovation-driven development strategy, occupational groups are facing increasing work pressure, and its impact on sleep quality and mental health deserves attention. Objective To explore potential mediating role of sleep quality between work stress and mental health status among occupational workers, and to provide a scientific basis for improving their mental health status. Methods Cluster sampling was used to select 2000 workers in Urumqi, Xinjiang Uygur Autonomous Region. They were divided into mental and physical worker groups according to their occupational types, and a questionnaire survey was conducted using General Information Survey Forms, Effort Reward Imbalance scale (ERI), Pittsburgh Sleep Quality Index (PSQI), and Symptom Check List-90 (SCL-90). Work stress level, sleep quality, and mental health were assessed and compared between mental and physical workers. Structural equation modelling was used to evaluate the relationship among work stress, sleep quality and mental health of the workers, and to explore the mediating effect of sleep quality. Results A total of 1979 survey questionnaires were collected, with a response rate of 99%, including 1500 (75.8%) mental workers and 479 (24.2%) physical workers. Linear correlations were confirmed between work stress, mental health, and sleep quality. The correlations of work stress with mental health and sleep quality scale scores were positive for both mental and physical workers (r=0.32, 0.31, P<0.01; r=0.25, 0.25, P<0.01), and sleep quality was also positively correlated with mental health (r=0.47, 0.56, P<0.01) . The final modified structural equation model showed that the coefficients of work stress on sleep quality for the mental and physical workers were 0.56 and 0.46 (P<0.001) respectively, and the coefficients of sleep quality on mental health were 0.52 and 0.80 (P<0.001) respectively. Sleep quality mediated the impact of work stress on mental health of the mental and physical workers, with mediating effect values of 0.29 and 0.37 respectively. The adaptability of both structural equation models is less than 3. Conclusion Occupational population's work stress and mental health may be mediated by sleep quality, and measures should be taken to reduce work stress and improve sleep quality and mental health.

We report a case of a male patient who developed persistent fever and central nervous system symptoms after eating raw snails for 10 days. The patient was diagnosed with Angiostrongyliasis depended on the clinical presentation, epidemiological history, and etiological results. The patient recovered after receiving albendazole anthelmintic and dexamethasone anti-inflammatory therapy. This article incorporates literature review to sort out the diagnosis and treatment of this patient, in order to provide feasible reference for clinicians.

Objective:To investigate the characteristics of neointimal hyperplasia (NIH) in patients with in-stent restenosis (ISR) over 5 years post-drug-eluting stent (DES) implantation based on optical coherence tomography (OCT).Methods:In this cross-sectional study, patients with DES-ISR who underwent OCT examination at PLA General Hospital between March 2010 and March 2022 were retrospectively included. All patients were divided into≤5 years DES-ISR group and>5 years DES-ISR group according to the time interval after DES implantation. Quantitative and qualitative analyses were conducted on OCT images to compare the clinical data and lesion characteristics of two patient groups. Furthermore, the independent clinical predictive factors of in-stent neoatherosclerosis (ISNA) were analyzed by multivariable logistic regression.Results:A total of 230 DES-ISR patients with 249 lesions were included, with an age of (63.1±10.4) years and 188 males (81.7%). The median interval after DES implantation was 6 (2, 9) years. There were 117 patients (122 ISR lesions) in the≤5 years DES-ISR group, and 113 patients (127 ISR lesions) in the>5 years DES-ISR group. Compared with≤5 years DES-ISR,>5 years DES-ISR showed more heterogeneous patterns (65.4% (83/127) vs. 48.4% (59/122), P=0.007), diffuse patterns (46.5% (59/127) vs. 31.2% (38/122), P=0.013), macrophage accumulations (44.1% (56/127) vs. 31.2% (38/122), P=0.035) in NIH and higher prevalence of ISNA (83.5% (106/127) vs. 72.1% (88/122), P=0.031). According to multivariable logistic regression, the independent predictive factor for ISNA was female ( OR=0.44, 95% CI 0.21-0.90, P=0.026). Female ( OR=0.48, 95% CI 0.23-0.99, P=0.046) and low-density lipoprotein cholesterol level ( OR=1.62, 95% CI 1.01-2.59, P=0.046) were independent predictive factors, respectively, for lipid ISNA. Calcified ISNA was independently associated with time interval of post-DES implantation ( OR=1.18, 95% CI 1.07-1.29, P=0.001). Conclusion:DES-ISR patients with a time interval of>5 years after stent implantation have a higher prevalence of ISNA and more complex lesions. Gender, the level of low-density lipoprotein cholesterol, and the time interval post-DES implantation are independently correlated with ISNA, lipid ISNA, and calcified ISNA.

Objective:To investigate the effect of Norcantharidin(NCTD)on the apoptosis of human ovarian cancer SKOV3 cells and its mechanism.Methods:Human ovarian cancer SKOV3 cells were cultured in vitro and treated with 52 μmol/L NCTD.The SKOV3 cells were divided into the control group and NCTD group(52 μmol/L).The morphological changes of SKOV3 cells were observed under an inverted microscope,and the changes of nucleus were observed under a fluorescence microscope.The changes of mitochondrial membrane potential were detected by flow cytometry after drug treatment for 24 h.Western blot was used to detect the expression levels of apoptosis-related proteins Bax,Bcl-2 and Wnt/β-catenin signaling pathway-related protein β-catenin in SKOV3 cells after drug treatment for 24 h.Result:Compared with that in the control group,NCTD inhibited the proliferation of SKOV3 cells,reduced mitochondrial membrane potential,induced apoptosis of SKOV3 cells,increased the expression of Bax protein,decreased the expression of Bcl-2 protein and β-catenin.Conclusion:NCTD-induced apoptosis of ovarian cancer SKOV3 cells may be related to the regulation of Wnt/β-catenin signaling pathway.

Objective To analyze the risk factors of unplanned reoperation and construct a nomogram-based risk prediction model to identify high-risk patients,so as to provide a basis for perioperative manage-ment to reduce the rate of reoperation.Methods A total of 880 patients with underwent unplanned reopera-tion between 2018 and 2021 were included as the unplanned reoperation group.Using propensity score matc-hing,2640 patients were matched in a 1∶3 ratio to form the control group.Potential risk factor indicators were collected and subjected to univariate analysis.Significant indicators were then selected for multivariable logistic regression analysis to construct the risk prediction model.The predictive value of the model was evalu-ated.Results For unplanned reoperation,The number of complications 3-5 (OR=1.84),the number of complications 6-10 (OR=2.94),combined with maligant tumor (OR=1.75),combined with end-stage renal disease (OR=1.92),major surgery grade 3 (OR=4.27),major surgery grade 4 (OR=7.26),and incision grade Ⅰ,Ⅱ,Ⅲ (OR=2.18,1.97,6.85) were independent factors (P<0.05).The model passed the calibra-tion degree test,and the area under ROC curve (AUC) was 0.715,indicating good model differentiation.Con-clusion A risk prediction model based on risk factors can help identify high-risk populations for unplanned reoperation and suggest corresponding measures for prevention.

Objective To propose strategies for developing clinical predictive models,aiming to assist researchers in conducting standardized clinical prediction model studies.Methods Literature review was conducted to summarize the operational steps and content for developing clinical predictive models.Then,a methodological framework was summarized and refined through expert consultation.Results The 11-step methodological framework for developing clinical predictive models was obtained by synthesizing the experience of 456 clinical predictive modeling studies and expert consultation,and the details were analyzed and elaborated.Conclusions This study presents methodological strategies and recommendations for the development of clinical predictive models,intended to serve as a guide for researchers.

We report a case of a male patient who developed persistent fever and central nervous system symptoms after eating raw snails for 10 days. The patient was diagnosed with Angiostrongyliasis depended on the clinical presentation, epidemiological history, and etiological results. The patient recovered after receiving albendazole anthelmintic and dexamethasone anti-inflammatory therapy. This article incorporates literature review to sort out the diagnosis and treatment of this patient, in order to provide feasible reference for clinicians.

Objective:To study the changes in serum small molecule metabolites after brucella infection in humans using untargeted metabolomics methods, and screening representative biomarkers. Methods:A total of 109 serum samples collected from January 2019 to December 2021 at the Brucellosis Clinic of the Baotou Center for Disease Control and Prevention were divided into acute phase group ( n = 40), chronic phase group ( n = 35) of brucellosis, and healthy group ( n = 34) based on clinical diagnosis. Ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry technology was used to test serum samples and screen for differential metabolites. Receiver operating characteristic curve was used to evaluate the predictive ability of differential metabolites for brucellosis. Enriched pathways were screened using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway to identify metabolic pathways significantly affected. Results:A total of 17 differential metabolites were screened between the acute phase group and the healthy group, and 12 differential metabolites were screened between the chronic phase group and the healthy group. There were a total of 5 differential metabolites (oleamide, linoleamide, stearamide, palmitoleic acid, α-linolenic acid) statistically significant among the three groups ( F = 16.84, 17.52, 14.31, 13.01, 20.76, P < 0.05). KEGG pathway analysis showed that the differential metabolites in the acute phase group were enriched in metabolic pathways such as ether lipid metabolism, glycerophosphate metabolism, sphingolipid signal and sphingolipid metabolism. The differential metabolites in the chronic phase group were enriched in metabolic pathways such as glycerophosphate metabolism, ether lipid metabolism, protein digestion and absorption metabolism. Conclusion:Untargeted metabolomics methods can screen out serum small molecule metabolites that undergo changes after brucella infection in the human body, including oleamide, linoleamide, stearamide, palmitoleic acid, α-linolenic acid can serve as potential biomarkers to distinguish brucellosis patients from healthy people.

OBJECTIVE To screen the potential drug targets and signaling pathways of Acanthopanax senticosus for the treatment of Alzheimer’s disease(AD) by bioinformatics and network pharmacology-based approach, and to preliminarily validate its efficacy. METHODS The ingredients of Acanthopanax senticosus were obtained through literature, the ingredients were screened by Swiss ADME, and potential targets were predicted by Swiss Target Prediction. AD’s differentially expressed genes were screened from the GSE28146 dataset. The target of Acanthopanax senticosus and AD target were mapped to construct a “drug-ingredients-potential target-disease” network and protein-protein interaction network. The DAVID database was used for GO and KEGG enrichment analysis. Autodock software was used to verify the molecular docking between key active ingredients and core targets. AD mice model was induced by D-galactose combined with aluminum chloride. Morris water maze test was performed to examine the learning memory ability of each group of mice and to observe the pathological changes in the hippocampus of mice. RESULTS Screened to obtain 24 active components and 74 potential targets of Acanthopanax senticosus for the treatment of AD. “Drug-ingredients-potential target-disease” network indicated that quercetin and kaempferol were the main components of Acanthopanax senticosus for the treatment of AD, and the protein-protein interaction network indicated that STAT3, MAPK1 and PIK3CA were the key targets. Obtained 366 GO enrichment entries(P<0.01) and 109 KEGG enrichment pathways(P<0.01). It mainly involved PI3K-AKT, AGE-RAGE, TNF and other pathways. The molecular docking results showed that the main active ingredients of Acanthopanax senticosus were able to bind well to the main targets. The in vivo pharmacological results showed that Acanthopanax senticosus could significantly improve the learning and memory ability of mice, reduce hippocampal tissue damage, and decrease the content of TNF-α, IL-6, and IL-1β in hippocampal tissue. CONCLUSION Acanthopanax senticosus may exert anti-AD effects by inhibiting the expression of inflammatory factors and reducing inflammatory damage.