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.

Hepatocellular carcinoma (HCC) is an aggressive primary liver malignancy often diagnosed at an advanced stage, resulting in a poor prognosis. Accurate risk stratification and early detection of HCC are critical unmet needs for improving outcomes. Several blood-based biomarkers and imaging tests are available for early detection, prediction, and monitoring of HCC. However, serum protein biomarkers such as alpha-fetoprotein have shown relatively low sensitivity, leading to inaccurate performance. Imaging studies also face limitations related to suboptimal accuracy, high cost, and limited implementation. Recently, liquid biopsy techniques have gained attention for addressing these unmet needs. Liquid biopsy is non-invasive and provides more objective readouts, requiring less reliance on healthcare professional’s skills compared to imaging. Circulating tumor cells, cell-free DNA, and extracellular vesicles are targeted in liquid biopsies as novel biomarkers for HCC. Despite their potential, there are debates regarding the role of these novel biomarkers in the HCC care continuum. This review article aims to discuss the technical challenges, recent technical advancements, advantages and disadvantages of these liquid biopsies, as well as their current clinical application and future directions of liquid biopsy in HCC.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Depression is a heterogeneous mental disorder in which the interaction between genetic susceptibility and environ-mental factors plays a key role in its pathogenesis.Although the specific mechanisms of the disease still need to be thoroughly studied and elucidated,there is now a broad consensus that epi-genetic markers have a central influence on its mechanism of ac-tion.DNA methylation of brain-derived neurotrophic factor(BD-NF)is not only regarded as a promising epigenetic biomarker of pathology,but may also help predict the efficacy of antidepres-sants.In this paper we reviewed the gene structure of BDNF and its DNA methylation regulation mechanism,and also analyzed the changes of DNA methylation of this factor in depression pa-tients and animal models,aiming to provide new ideas and theo-retical support for clinical research.

Aim To explore the therapeutic effect and mechanism of Qingjie Huagong decoction in modulating PI3K/AKT/NF-κB signaling pathway in inflammatory response of acute pancreatitis(AP)mice.Methods Twenty-four mice were randomly divided into Blank group,Model group,Ustekin group,and Qingjie Hua-gong decoction group,with six mice in each group.The AP model was prepared by using rain frogin.Serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α lev-els were detected by ELISA;the pancreatic pathology was detected by HE staining;the expressions of PI3K,AKT,and NF-κB-related proteins and mRNAs were de-tected by immunohistochemistry,Western blot,and RT-qPCR.Results Compared with the blank group,the model group showed obvious pathological damage to the pancreas,with significantly higher serum α-AMS,PN-LP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels(P＜0.01),and significantly higher levels of PI3K,AKT,and NF-κB-related proteins and mRNA expression(P＜0.01).Compared with the model group,both the Qingjie Huagong decoction group and the ustekin group improved the histopathological changes in the pancreas of AP mice,decreased the serum α-AMS,PNLP,IL-1β,IL-6,IL-8,IL-18,and TNF-α levels,and down-reg-ulated the expression levels of pancreatic PI3K,AKT,NF-κB-related proteins and mRNA(P＜0.05 or P＜0.01).Conclusion Qingjie Huagong decoction may inhibit the inflammatory response and protect pancreat-ic tissues by regulating the expression of PI3K/AKT/NF-κB signaling pathway.

Objective:To explore the effect of social cognition and interaction training (SCIT) combined with transcranial magnetic stimulation (TMS) on intrinsic motivation and social cognition in patients with schizophrenia.Methods:Forty-two stable schizophrenia patients were randomly divided into the SCIT + TMS group( n=22) and the SCIT group( n=20). All the subjects received 20 sessions of SCIT treatment, and the SCIT+ TMS group simultaneously received 15 sessions of intermittent theta burst stimulation(iTBS) over the left dorsolateral prefrontal cortex(DLPFC). All the subjects were assessed by intrinsic motivation inventory for schizophrenia research(IMI-SR), Chinese version of the ambiguous intentions hostility questionnaire(AIHQ-C), theory of mind-picture sequencing task(ToM-PST), mentalization scale (MentS), Chinese version of interpersonal reactivity index (IRI-C) and positive and negative syndrome scale (PANSS) before and after intervention. SPSS 26.0 software was used for data analysis.Wilcoxon signed-rank test was used for intra-group comparison before and after treatment, while Mann-Whitney U test and covariance analysis were used for inter-group comparison.Spearman correlation analysis and Logistic regression analyses were used to explore the association between the intrinsic motivation and social cognition. Results:There were no significant differences on IMI-SR scores before and after treatment between the two groups(all P>0.05). In the SCIT+ TMS group, the total score of hostility bias (HB), HB scores in ambiguous scenes, HB scores in intentional scenes, and aggressive bias (AB) scores in ambiguous scenes of AIHQ-C scale after treatment were lower than those befor treatment( Z=-2.044--3.112, all P<0.05), while the total score of ToM-PST(18.50(16.00, 21.00) vs 15.50(11.75, 18.00), Z=-2.598, P=0.009) and IRI-C imagination score (12.18±3.79, 14.41±4.73, t=-2.694, P=0.014) were higher than those before treatment.In the SCIT group, the total score of ToM-PST after treatment was higher than that before treatment(21.00(20.00, 22.00) vs 17.00(14.50, 20.75), Z=-2.518, P=0.012).There was no significant statistical difference in MentS scores between after treatment and before treatment ( P>0.05). The difference in AIHQ-C intentional scenario AB score before and after treatment was higher in the SCIT+ TMS group than in the SCIT group ( Z=-1.996, P=0.046), while there was no statistically significant difference in the difference before and after treatment in social cognitive scores between the two groups (all P>0.05).In the combined two samples, Spearman correlation analysis showed that the total score of IMI-SR before treatment was positively correlated with the primary belief score of ToM-PST understanding, reciprocity score, MentS total score, other person mentalization score, motivation mentalization score, IRI-C total score, viewpoint taking score, and empathy concern score after treatment( r=0.341-0.509, all P<0.05), while negatively correlated with AIHQ-C total score and factor scores ( r=-0.434--0.645, P<0.05).Logistic regression analysis showed that the total score of IMI-SR had negative impact on AIHQ-C total HB score( B=-0.047, OR=0.954, 95% CI=0.917-0.993).The value score had a positive impact on the total score of MentS ( B=0.143, OR=1.154, 95% CI=1.043-1.277), other person mentalization score( B=0.166, OR=1.181, 95% CI=1.058-1.318), motivation mentalization score( B=0.111, OR=1.117, 95% CI=1.021-1.223), IRI-C total score ( B=0.138, OR=1.148, 95% CI=1.038-1.270), and viewpoint taking score( B=0.194, OR=1.214, 95% CI=1.076-1.369). Interest score had a positive impact on IRI-C empathy concern score ( B=0.098, OR=1.103, 95% CI=0.998-1.218) and ToM-PST understanding primary belief score( B=0.130, OR=1.138, 95% CI=1.010-1.283) and reciprocity score( B=0.189, OR=1.208, 95% CI=1.057-1.380). Conclusion:The research results did not confirm the effect of TMS over the DLPFC on enhancing intrinsic motivation, as well as the synergistic effect of SCIT treatment on social cognition. But the correlation results indicates that improving schizophrenia patients' intrinsic motivation level in cognitive training is meaningful for promoting social cognition.

AIM To study the chemical constituents from the branches and leaves of Michelia yunnanensis Franch.ex Finet & Gagnep.and their anti-inflammatory activities.METHODS The methanol extract was isolated and purified by silica gel,MCI,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Twenty compounds were isolated and identified as dihydrodehydrodiconifenyl alcohol(1),8-hydroxypinoresinol(2),lariciresinol(3),isolariciresinol(4),(7S,8R)-4-hydroxy-3,3',5'-trimethoxy-8',9'-dinor-8,4'-oxyneoligna-7,9-diol-7'-aldehyde(5),thero-2,3-bis-(4-hydroxy-3-methoxypheyl)-3-methoxy-propanol(6),evofolin B(7),(E)-p-coumaryl alcohol γ-O-methyl ether(8),ω-hydroxypropioguaiacone(9),sinapaldehyde(10),isoscopoletin(11),6-hydroxy-5,7-dimethoxycoumarin(12),2α,3α-dihydroxy-2-methylbutyrolactone(13),6-hydroxy-3(1-hydroxy-1-methylethyl)-6-methyl-2-cyclohexen-1-one(14),benzofuran-2-carboxaldehyde(15),3,4-dihydroxy-5-methoxybenzaldehyde(16),3,5-dimethoxy-4-hydroxybenzaldehyde(17),3,4-dihydroxybenzaldehyde(18),3,4-dihydroxybenzoic methyl ester(19),vanillic acid(20).The inhibition rate of compound 1 on NO was 45.39％±0.32％.CONCLUSION Compounds 1-16,18-20 are first isolated from this plant.Compound 1 has anti-inflammatory activity.

Objective To explore the correlation between fasting blood glucose(FBG)level and fractional flow reserve(FFR)in patients with borderline coronary artery disease,and to clarify its potential influence on FFR measurement.Methods From August 2020 to August 2023,the data of 135 patients with coronary atherosclerotic heart disease who received coronary angiography and FFR evaluation in the Fourth Affiliated Hospital of Harbin Medical University were retrospectively collected.According to the exclusion and inclusion criteria,85 cases of borderline diseased vessels of single coronary artery with stenosis degree of 50％-80％were screened out,and they were divided into FBG≥6.1 mmol/L group(47 cases)and FBG＜6.1 mmol/L group(38 cases).The baseline data,angiographic and functional indexes of the two groups were compared,and the correlation between FBG and FFR was analyzed.Results Compared with the FBG＜6.1 mmol/L group,the FBG≥6.1 mmol/L group had a higher proportion of FFR negative results(72.3％vs.23.7％,P＜0.001),and the FFR measurement values were generally increased[0.84(0.80,0.90)vs.0.75(0.68,0.80),P＜0.001],with statistically significant differences.Pearson correlation analysis was performed on all lesions,and FFR＞0.80(negative result)was positively correlated with FBG≥6.1 mmol/L(r=0.484,P＜0.001).Conclusions Among the patients with borderline coronary artery disease(50％-80％stenosis)included in this study,FBG≥6.1 mmol/L is significantly correlated with FFR＞0.80.For patients with borderline coronary lesions with elevated FBG,the influence of blood glucose factors should be carefully considered in clinical interpretation of FFR results.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.