Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To evaluate the safety and efficacy of splenectomy with distal pancreatectomy during cytoreductive surgery in epithelial ovarian cancer(EOC).Methods A total of 17 patients from Zhongshan Hospital,Fudan University and the First Affiliated Hospital of University of Science and Technology of China(Anhui Provincial Hospital)received splenectomy with distal pancreatectomy during cytoreductive surgery in EOC were recruited.Their clinicopathological characteristics,postoperative complications and survival situation were retrospective analyzed.Results Of the 17 patients,there were 13 primary cases and 4 recurrent cases.Eleven cases(64.7%)had preoperative imaging finding with metastatic lesions in the splenic hilum,among whom 6 cases had distal pancreas metastasis during the operation.The drainage was placed in the splenic fossa for the measurement of amylase levels in drain fluid and was removed after 8(3-12)days.There were 4 patients had postoperative pancreatic fistula(POPF)of grade A,3 patients had POPF of grade B and no POPF of grade C occurred.The 2 patients with POPF of grade B improved after percutaneous drainage,and the rest recovered with somatostatin,antibiotic drugs and medicines without perioperative mortality.The interval between surgery to chemotherapy was 17.5(13-37)days.The median follow-up time was 14(4-64)months and the median progression-free survival was 10(5-32)months.Conclusion Splenectomy with distal pancreatectomy as part of cytoreduction surgery in EOC is needed for optimal resection,and the complication of pancreatic fistula could be managed conservatively.

Cryoablation therapy with explicit anti-tumor mechanisms and histopathological manifestations has a long history.A large number of clinical practice has shown that cryoablation therapy is safe and effective,making it an ideal tumor treatment method in theory.Previously,its efficacy and clinical application were constrained by the limitations of refrigerants and refrigeration equipment.With the development of the new generation of cryoablation equipment represented by argon helium knives,significant progress has been made in refrigeration efficien-cy,ablation range,and precise temperature measurement,greatly promoting the progression of tumor cryoablation technology.This consensus systematically summarizes the mechanism of cryoablation technology,indications for oral mucosal melanoma(OMM)cryotherapy,clinical treatment process,adverse reactions and management,cryotherapy combination therapy,etc.,aiming to provide reference for carrying out the standardized cryoablation therapy of OMM.

Nanozyme is novel nanoparticle with enzyme-like activity, which can be classified into peroxidase-like nanozyme, catalase-like nanozyme, superoxide dismutase-like nanozyme, oxidase-like nanozyme and hydrolase-like nanozyme according to the type of reaction they catalyze. Since researchers first discovered Fe₃O₄ nanoparticles with peroxidase-like activity in 2007, a variety of nanoparticles have been successively found to have catalytic activity and applied in bioassays, inflammation control, antioxidant damage and tumor therapy, playing a key role in disease diagnosis and treatment. We summarize the use of nanozymes with different classes of enzymatic activity in the diagnosis and treatment of diseases and describe the main factors influencing nanozyme activity. A Mn-based peroxidase-like nanozyme that induces the reduction of glutathione in tumors to produce glutathione disulfide and Mn²⁺, which induces the production of reative oxygen species (ROS) in tumor cells by breaking down H₂O₂ in physiological media through Fenton-like action, thereby inhibiting tumor cell growth. To address the limitation of tumor tissue hypoxia during photodynamic tumor therapy, the effect of photodynamic therapy is significantly enhanced by using hydrogen peroxide nanozymes to catalyze the production of oxygen from H₂O₂. In pathological states, where excess superoxide radicals are produced in the body, superoxide dismutase-like nanozymes are able to selectively regulate intracellular ROS levels, thereby protecting normal cells and slowing down the degradation of cellular function. Based on this principle, an engineered nanosponge has been designed to rapidly scavenge free radicals and deliver oxygen in time to save nerve cells before thrombolysis. Starvation therapy, in which glucose oxidase catalyzes the hydrolysis of glucose to gluconic acid and hydrogen peroxide in cancer cells with the involvement of oxygen, attenuates glycolysis and the production of intermediate metabolites such as nucleotides, lipids and amino acids, was used to synthesize an oxidase-like nanozyme that achieved effective inhibition of tumor growth. Furthermore, by fine-tuning the Lewis acidity of the metal cluster to improve the intrinsic activity of the hydrolase nanozyme and providing a shortened ligand length to increase the density of its active site, a hydrolase-like nanozyme was successfully synthesized that is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds and even biofilms with high efficiency in hydrolyzing the substrate. All these effects depend on the size, morphology, composition, surface modification and environmental media of the nanozyme, which are important aspects to consider in order to improve the catalytic efficiency of the nanozyme and have important implications for the development of nanozyme. Although some progress has been made in the research of nanozymes in disease treatment and diagnosis, there are still some problems, for example, the catalytic rate of nanozymes is still difficult to reach the level of natural enzymes in vivo, and the toxic effects of some heavy metal nanozymes material itself. Therefore, the construction of nanozyme systems with multiple functions, good biocompatibility and high targeting efficiency, and their large-scale application in diagnosis and treatment is still an urgent problem to be solved. (1) To improve the selectivity and specificity of nanozymes. By using antibody coupling, the nanoparticles are able to specifically bind to antigens that are overexpressed in certain cancer cells. It also significantly improves cellular internalization through antigen-mediated endocytosis and enhances the enrichment of nanozymes in target tissues, thereby improving targeting during tumor therapy. Some exogenous stimuli such as laser and ultrasound are used as triggers to control the activation of nanozymes and achieve specific activation of nanozyme. (2) To explore more practical and safer nanozymes and their catalytic mechanisms: biocompatible, clinically proven material molecules can be used for the synthesis of nanoparticles. (3) To solve the problem of its standardization and promote the large-scale clinical application of nanozymes in biomonitoring. Thus, it can go out of the laboratory and face the market to serve human health in more fields, which is one of the future trends of nanozyme development.

Objective To investigate the implementation of surveillance,prevention and control measures for healthcare-associated infection(HAI)in maternal and child healthcare(MCH)institutions,and provide policy evi-dence for optimizing HAI prevention and control in MCH institutions.Methods Stratified sampling was conducted among the MCH institutions at provincial,municipal and county levels in 8 provinces/autonomous regions.A uni-fied questionnaire was designed and the online survey was conducted through"Questionnaire Star".Results The data from 123 MCH institutions were included in the analysis.90.24％of the MCH institutions carried out compre-hensive surveillance on HAI.The ratios of MCH institutions which implemented targeted surveillance on HAI in neonatal intensive care unit(NICU),surgical site infection,multidrug-resistant organisms(MDROs)and HAI in intensive care units(non-NICU excluded)were 89.66％,85.96％,80.77％,and 74.19％,respectively.51.22％MCH institutions adopted information surveillance system on HAI cases.94.31％MCH institutions carried out surveillance on hand hygiene compliance.Over 90％MCH institutions carried out surveillance on environment hy-giene in high-risk departments.71.54％MCH institutions conducted centralized cleaning,disinfection,sterilization and supply for reusable medical instruments in the central sterile supply department(CSSD).Over 90％MCH insti-tutions established three-level pre-examination triage systems.86.18％set up transitional wards.MCH institutions generally adopted a management model with established effective communication,full appointment visits,and sepa-rate visits for special medical groups,such as registered pregnant women,high-risk newborns,healthcare groups,and long-term rehabilitation patients.However,the ratio of institutions conducting on-line follow-up visits was less than 50％.Conclusion MCH institutions have generally carried out comprehensive and targeted surveillance on HAI.Information surveillance need to be facilitated.Hand hygiene and environmental hygiene surveillance has been popularized to a certain extent at all levels of MCH institutions.The cleaning,disinfection,sterilization,and supply processes of reusable medical devices in a few MCH institutions are not standardized.Special medical populations get effective management.On-line healthcare is to be further promoted.

AIM: To investigate the efficacy of lacrimal duct laser dacryoplasty combined with intubation and postoperative meibomian gland treatment in patients with chronic dacryocystitis complicated by meibomian gland dysfunction.METHODS: Data were collected from 128 patients with chronic dacryocystitis complicated by meibomian gland dysfunction treated at Xi'an No.1 Hospital from March 2021 to December 2022. All patients underwent lacrimal duct laser dacryoplasty combined with intubation. Postoperatively, those patients were randomly divided into two groups: group A(64 cases, without meibomian gland treatment)and group B(64 cases, with meibomian gland treatment). The lacrimal intubation was removed at 3 mo after surgery to evaluate the patency rate of lacrimal irrigation. Additionally, changes in the ocular surface disease index(OSDI)score, non-invasive tear film break-up time, tear meniscus height, conjunctival hyperemia analysis, meibomian gland analysis, tear lipid layer thickness, tear ferning test, and conjunctival impression cytology were compared between the two groups.RESULTS: The lacrimal irrigation patency rates in the group A and group B were 78.1% and 81.2% respectively, with no statistically significant difference between the two groups(P>0.05); compared with the group A, group B showed a significant extension in non-invasive tear breakup time at 3 mo after surgery, and the OSDI score, conjunctival hyperemia analysis, tear ferning test and conjunctival impression cytology grading were all significantly decreased(all P<0.05), while there was no significant difference in tear meniscus height, tear lipid layer thickness and meibomian gland loss score between the two groups(all P>0.05).CONCLUSION: Comprehensive treatment for patients with chronic dacryocystitis combined with meibomian gland dysfunction have improved patients' comfort, tear film stability, and reduces local inflammatory response. It is important to simultaneously address ocular surface microenvironment abnormalities during surgical treatment to achieve satisfactory efficacy.