ObjectiveTo explore the relationship between negative life events and depression severity in adolescent patients with depressive disorder， as well as the chain mediating role of insomnia symptoms and quality of life. Methods374 outpatient patients and hospitalized patients with adolescent depressive disorders were enrolled. The Adolescent Life Event Scale （ASLEC）， the Insomnia Severity Index （ISI）， the World Health Organization Quality of Life Questionnaire Short Form （WHOQOL-BREF）， and the Center for Epidemiology Depression Scale （CES-D） were used to evaluate the negative life event situation， insomnia symptoms， quality of life level and depression severity of the subjects， respectively. In addition， the PROCESS 4.0 macroprogram was used to analyze the chain mediating effect of insomnia symptoms and quality of life between negative life events and depression severity in patients with adolescent depressive disorder. ResultsThe results of correlation analysis showed that there was a significant correlation between negative life events and insomnia symptoms， quality of life， and depression severity （all P<0.05）. In addition， the results of chain mediation showed that negative life events had a significant direct effect on depression severity， with an effect size of 0.12 （P<0.001）. Insomnia symptoms and quality of life played a mediating role in the relationship between negative life events and depression severity in patients with adolescent depressive disorders， with indirect effect sizes of 0.062 （95%CI： 0.040-0.087） and 0.091 （95%CI： 0.059-0.123）， respectively. It could also play a chain mediation role， and the effect size was 0.039 （95%CI： 0.024-0.057）. ConclusionNegative life events experienced by patients with adolescent depressive disorder not only directly affect the severity of depressive symptoms， but may also indirectly exacerbate depression through insomnia symptoms and quality of life.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

Nucleotide analogues (NAs) and interferon are still the first-line drugs for the treatment of chronic hepatitis B (CHB), but they still cannot completely eliminate covalently closed circular DNA (cccDNA) within hepatocytes. The clinical cure, or the disappearance of HBsAg, is the ideal goal of antiviral therapy. Although interferon therapy has a significantly greater HBsAg clearance rate and seroconversion rate than NAs, combination or sequential treatment can improve the HBsAg clearance rate and seroconversion rate to a certain extent, and only a small proportion of CHB patients can achieve clinical cure. Therefore, finding indications that predict clinical cure before and during antiviral treatment is crucial for identifying patients who are more likely to achieve HBsAg clearance at an early stage, improving clinical cure rates, and reducing treatment costs. This article reviews the research progress on predictive indicators of clinical cure of chronic hepatitis B in the past five years, explores the value of each indicator in predicting clinical cure, and provides a reference for optimizing CHB treatment strategies.

Objective:To assess the efficacy and safety profile of antaitasvir phosphate combined with yiqibuvir in the treatment of chronic hepatitis C (CHC) of various genotypes, without cirrhosis or with compensated cirrhosis.Methods:394 cases with CHC from 22 centers were collected from October 2021 to April 2023. They were randomly assigned to receive either the experimental drugs (antaitasvir phosphate 100 mg+yiqibuvir 600 mg) or placebo treatment in a 3∶1 ratio. The patients were administered drugs once a day for 12 consecutive weeks, and then followed up for 24 weeks after treatment cessation. All subjects were unblinded at the four-week follow-up following drug discontinuation, with the experimental drug group continuing to complete subsequent post-discontinuation follow-up. The placebo group was switched to receive the experimental drugs for a repeated 12-week treatment period and followed up for another 24 weeks after discontinuation of the drug (placebo delayed treatment phase).The sustained virologic response rate (SVR12) was observed for subjects in the double-blind phase and the placebo delayed-treatment phase at 12 weeks after treatment cessation.Virological resistance analysis was performed on subjects who failed treatment. The primary efficacy endpoint was SVR12. The number and percentage of subjects who achieved "HCV RNA

In recent years, studies have found that the abnormal expression of rhythm genes is closely related to the risk of occurrence and the progression of the disease course of colorectal cancer. In addition, chronotherapy based on the circadian rhythm theory has shown certain effects in the clinical treatment of colorectal cancer, but there are still great limitations. Therefore, it is very important to clarify the mechanism of action of rhythm genes in the occurrence and development of colorectal cancer, which may provide a theoretical basis for the clinical application of chronotherapy.

Objective To investigate whether carotid artery stenting （CAS） is a protective factor against the progression of white matter hyperintensity （WMH） volume in patients with carotid artery stenosis. Methods A prospective study was conducted for the clinical， imaging， and follow-up data of patients with carotid artery stenosis who were treated in Zhejiang Provincial People's Hospital from January 2021 to June 2023. A total of 99 participants were included in this study， among whom 48 received CAS treatment （CAS group） and 51 did not receive CAS treatment （non-CAS group）. The two groups were analyzed in terms of baseline data and WMH volume during the 1-year follow-up. Results There were no significant differences in baseline data between the two groups （P>0.05）. There was no significant difference in overall WMH volume after follow-up between the two groups （P>0.05）， but compared with the non-CAS group， the CAS group showed a significantly lower degree of the progression of WMH volume within one year （-0.27 ml vs 2.82 ml， P<0.001）. There was a significant difference in the proportion of patients with new-onset stroke within one year between the CAS group and the non-CAS group （18.75% vs 37.25%， P=0.041）. The binary logistic regression analysis showed that CAS was an independent protective factor against the progression of WMH volume（OR=-0.37， 95%CI -0.78 to -0.03，P=0.046） and new-onset stroke within one year （OR=0.28， 95% CI 0.09 to 0.83， P=0.022）. Conclusion CAS is a protective factor against the progression of WMH volume and can effectively reduce the risk of stroke recurrence in patients with carotid artery stenosis.

Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.

Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.

Nucleotide analogues (NAs) and interferon are still the first-line drugs for the treatment of chronic hepatitis B (CHB), but they still cannot completely eliminate covalently closed circular DNA (cccDNA) within hepatocytes. The clinical cure, or the disappearance of HBsAg, is the ideal goal of antiviral therapy. Although interferon therapy has a significantly greater HBsAg clearance rate and seroconversion rate than NAs, combination or sequential treatment can improve the HBsAg clearance rate and seroconversion rate to a certain extent, and only a small proportion of CHB patients can achieve clinical cure. Therefore, finding indications that predict clinical cure before and during antiviral treatment is crucial for identifying patients who are more likely to achieve HBsAg clearance at an early stage, improving clinical cure rates, and reducing treatment costs. This article reviews the research progress on predictive indicators of clinical cure of chronic hepatitis B in the past five years, explores the value of each indicator in predicting clinical cure, and provides a reference for optimizing CHB treatment strategies.