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.

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.

ObjectiveTo study the bioactive secondary metabolites of Talaromyces sp. TP21 and their bioactivities. MethodThe secondary metabolites of Talaromyces sp. TP21 were isolated by high performance liquid chromatography （HPLC）， normal phase and reversed phase column chromatography combined with molecular networking and bioassay-guided fractionation， and their structures were determined by nuclear magnetic resonance （NMR） and high resolution mass spectrometry （HR MS）. The inhibitory effects of the compounds on the growth of the lung cancer cell line A549 and the liver cancer cell line Hep G2 were measured by themethyl thiazolyl tetrazolium （MTT） method. The antimicrobial activities of the compounds were measured with Staphylococcus aureus and human oral cavity-derived Saccharomyces cerevisiae as the indicator microorganisms. ResultSeventeen compounds were isolated from the secondary metabolites of Talaromyces sp. TP21 and identified as ergochrome C （1）， daldiniaeschsone A （2）， seco-blennolide B （3）， penitholabene （4）， penicichrysogene A （5）， orsellinic acid （6）， griseofulvin （7）， isorhodoptilometrin （8）， （+）-5-chloromitorubrinic acid （9）， penicillixanthone A （10）， pentacecilide B （11）， pentacecilide C （12）， chrodrimanin C （13）， chrodrimanin E （14）， chrodrimanin H （15）， chrodrimanin F （16）， and 3-hydroxypentacecilide A （17）. ConclusionCompounds 1-5， 11-12， and 17 were isolated from Talaromyces for the first time. Among them， compounds 4， 7， and 10-12 exhibited inhibitory activities against the growth of A549 and Hep G2 cells， with the median inhibitory concentration below 50 μmol·L^-1. Furthermore， compounds 9 and 10 showed inhibitory activities against S. aureus and human oral cavity-derived S. cerevisiae， with the minimum inhibitory concentration of 8-128 mg·L^-1.

G protein-coupled receptor (GPR) 40, as one of GPRs family, plays a potential role in regulating glucose and lipid metabolism. To study the effect of GPR40 novel agonist SZZ15-11 on hyperglycemia and hyperlipidemia and its potential mechanism, spontaneous type 2 diabetic KKA^y mice, human hepatocellular carcinoma HepG2 cells and murine mature adipocyte 3T3-L1 cells were used. KKA^y mice were divided into four groups, vehicle group, TAK group, SZZ (50 mg·kg^-1) group and SZZ (100 mg·kg^-1) group, with oral gavage of 0.5% sodium carboxymethylcellulose (CMC), 50 mg·kg^-1 TAK875, 50 and 100 mg·kg^-1 SZZ15-11 respectively for 45 days. Fasting blood glucose, blood triglyceride (TG) and total cholesterol (TC), non-fasting blood glucose were tested. Oral glucose tolerance test and insulin tolerance test were executed. Blood insulin and glucagon were measured via enzyme-linked immunosorbent assay (ELISA). After mice′s execution, liver tissue was harvested to test TG and TC content. Then pathological morphology of liver was observed through hematoxylin-eosin (HE) staining, and the lipid metabolism relative signal pathway was analyzed by Western blot and RT-PCR. The experiments were approved by the Institutional Animal Care and Use Committee of the Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College. At the same time, Akt phosphorylation level in HepG2 cells and adiponectin in 3T3-L1 cells treated with TNFα were measured with Western blot. The results show that SZZ15-11 not only decreased blood glucose and lipid, improved insulin sensitivity, but also increased fasting blood glucagon and promoted insulin secretion after glucose loading in KKA^y mice. Additionally, SZZ15-11 alleviated hepatic steatosis and liver dysfunction in KKA^y mice. In liver tissue, SZZ15-11 increased AMPKα phosphorylation level and cholesterol metabolism relative gene Abcg8 transcription. In HepG2 cells, SZZ15-11 increased Akt phosphorylation level. In adipocyte 3T3-L1, SZZ15-11 recovered the decreased adiponectin expression by TNFα. This study proved that GPR40 agonist SZZ15-11 could be a candidate compound for regulating glucolipid metabolic disorder.

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.