Objective: To explore the impact of sleep quality, experience of childhood maltreatment, and their interaction on depressive symptoms among middle school students, so as to provide the reference for early intervention of depressive symptoms among middle school students. Methods: From September to December 2023, a questionnaire survey was conducted among 1 231 students from two secondary schools in Harbin, Heilongjiang Province by a convenient sampling method. The survey included general demographic information, Childhood Trauma Questionnaire Short Form, Pittsburgh Sleep Quality Index and Short Version of Center for Epidemiological Studies Depression Scale. The Chi square test was used to analyze the differences in depressive symptom, sleep quality and childhood maltreatment among students with different demographic characteristics. Correlation analysis was conducted using Logistic regression, and interaction analysis was performed by both additive and multiplicative interaction models. Results: The detection rate of depressive symptoms among middle school students was 22.7%, and the rate for high school students (35.2%) was significantly higher than that for middle school students (17.0%) ( χ 2=50.35, P <0.01). The detection rates of depressive symptoms among middle school students with a history of childhood maltreatment and poor sleep quality were 45.8% and 44.0%, respectively. Multivariate Logistic regression analysis showed that compared to students without a history of childhood maltreatment, students with a history of childhood maltreatment had a higher risk of depressive symptoms ( OR =4.49，95% CI =3.31~ 6.09 , P <0.01);students with poor sleep quality had a higher risk of depressive symptoms than students with good sleep quality ( OR = 5.99，95% CI =4.37~8.22, P <0.01).The interaction results showed that the presence of childhood maltreatment and poor sleep quality had an additive interaction on the occurrence of depression in middle school students. Compared with students without childhood maltreatment and having good sleep quality, students with childhood maltreatment and poor sleep quality had a 22.49 times higher risk of developing depression ( OR =22.49，95% CI =14.22~35.59, P <0.01). Conclusion Depressive symptoms among middle school students are associated with childhood maltreatment and poor sleep quality, and there is an additive interaction between childhood maltreatment and poor sleep quality on the impact of depressive symptoms.

Emerging evidence suggests that dysbiosis of the gut microbiota is associated with the pathogenesis of Parkinson's disease (PD), a prevalent neurodegenerative disorder. The microbiota-gut-brain axis plays a crucial role in the development and progression of PD, and numerous studies have demonstrated the potential therapeutic benefits of modulations in the intestinal microbiota. This review provides insights into the characterization of the gut microbiota in patients with PD and highlights associations with clinical symptoms and underlying mechanisms. The discussion underscores the increased influence of the gut microbiota in the pathogenesis of PD. While the relationship is not fully elucidated, existing research demonstrates a strong correlation between changes in the composition of gut microbiota and disease development, and further investigation is warranted to explain the specific underlying mechanisms.
Humans ; Parkinson Disease/microbiology* ; Gastrointestinal Microbiome/physiology* ; Dysbiosis/microbiology*

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

Hypercholesterolemia is a significant risk factor for the development of atherosclerosis. 2',3',5'-Tri-O-acetyl-N ⁶-(3-hydroxyphenyl) adenosine (IMM-H007), a novel AMPK agonist, has shown protective effects in metabolic diseases. However, its impact on cholesterol and triglyceride metabolism in hypercholesterolemia remains unclear. In this study, we aimed to elucidate the effects and specific mechanisms by which IMM-H007 regulates cholesterol and triglyceride metabolism. To achieve this goal, we used Apoe ^-/- and Ldlr ^-/- mice to establish a hypercholesterolemia/atherosclerosis model. Additionally, hepatocyte-specific Ampka1/2 knockout mice were subjected to a 5-week high-cholesterol diet to establish hypercholesterolemia, while atherosclerosis was induced via AAV-PCSK9 injection combined with a 16-week high-cholesterol diet. Our results demonstrated that IMM-H007 improved cholesterol and triglyceride metabolism in mice with hypercholesterolemia. Mechanistically, IMM-H007 modulated the AMPKα1/2-LDLR signaling pathway, increasing cholesterol uptake in the liver. Furthermore, IMM-H007 activated the AMPKα1-FXR pathway, promoting the conversion of hepatic cholesterol to bile acids. Additionally, IMM-H007 prevented hepatic steatosis by activating the AMPKα1/2-ATGL pathway. In conclusion, our study suggests that IMM-H007 is a promising therapeutic agent for improving hypercholesterolemia and atherosclerosis through the activation of AMPKα.

Hippo signaling is a highly conserved pathway central to diverse cellular processes. Dysregulation of this pathway not only leads to developmental abnormalities but is also closely related to the occurrence and progression of various cancers. Recent studies have uncovered that, in addition to the classical signaling cascade regulation, biomolecular condensates formed via phase separation play a key role in the spatiotemporal regulation of Hippo signaling. In this review, we provide a summary of the latest research progress on the regulation of the Hippo signaling pathway by phase separation, with a particular focus on transcriptional activation mediated by Yes-associated protein (YAP)/transcriptional coactivator with post-synaptic density-95, disks-large, and zonula occludens-1 (PDZ)-binding domain (TAZ) condensates. Furthermore, we discuss the utility of chemical crosslinking combined with mass spectrometry to analyze the TAZ condensate interactome and examine the role of the protein fused in sarcoma (FUS) in modulating the biophysical properties of TAZ condensates, which in turn influence their transcriptional activity and pro-tumorigenic functions. These insights not only advance our understanding of Hippo signaling but also offer new perspectives for therapeutic interventions targeting diseases linked to dysregulated YAP/TAZ activity.
Humans ; Signal Transduction ; Hippo Signaling Pathway ; Protein Serine-Threonine Kinases/physiology* ; Animals ; Biomolecular Condensates/metabolism* ; Transcription Factors/metabolism* ; YAP-Signaling Proteins ; Adaptor Proteins, Signal Transducing/metabolism* ; Neoplasms ; Transcriptional Activation ; Intracellular Signaling Peptides and Proteins/metabolism*

ObjectiveTo provide technical support for the molecular surveillance of pathogenic bacteria strains carrying mobile colistin resistance-1 （mcr⁃1） gene isolate from inlet of wastewater treatment plants （WWTP）. MethodsThe Enterobacteriaceae strains carrying mcr⁃1 resistance gene isolate from inlet of WWTP during April 1 to June 30， 2023 in Shanghai were cultured on blood-rich and SS culture medium and were identified using a mass spectrometry analyzer. The mcr⁃1 gene and copy number were detected by real-time fluorescence quantitative PCR. Drug susceptibility test was performed by microbroth dilution method. The copy numbers of Escherichia coli carrying mcr⁃1 gene isolated from wastewater and human fecel were statistically analyzed by SPSS 25.0. ResultsA total of 14 strains carrying the mcr⁃1 gene were isolated from 49 WWTP samples， and the positive isolation rate was 28.6%， including 12 non-diarrheal E. coli strains and 2 Klebsiella pneumoniae strains. The drug susceptibility results showed that all 14 strains were multi-drug resistant bacteria. They were all sensitive to imipenem and tigecycline， but were ampicillin- and cefazolin-resistant. There was no significant difference in the copy number between human-sourced diarrheal E. coli and wastewater-sourced non-diarrheal E. coli （t=0.647， P>0.05）. ConclusionThe isolation and identification of strains carrying the mcr⁃1 gene from inlet of WWTP samples were firstly established in Shanghai. The multi-drug resistance among the isolated strains is severe. To effectively prevent and control the spread of colistin-resistant bacteria， more attention should be paid to the surveillance of mcr⁃1 gene.

Astrocytes are the largest glial population in the mammalian brain. However, we have a minimal understanding of astrocyte development, especially fate specification in different regions of the brain. Through lineage tracing of the progenitors of the third ventricle (3V) wall via in-utero electroporation in the embryonic mouse brain, we show the fate specification and migration pattern of astrocytes derived from radial glia along the 3V wall. Unexpectedly, radial glia located in different regions along the 3V wall of the diencephalon produce distinct cell types: radial glia in the upper region produce astrocytes and those in the lower region produce neurons in the diencephalon. With genetic fate mapping analysis, we reveal that the first population of astrocytes appears along the zona incerta in the diencephalon. Astrogenesis occurs at an early time point in the dorsal region relative to that in the ventral region of the developing diencephalon. With transcriptomic analysis of the region-specific 3V wall and lateral ventricle (LV) wall, we identified cohorts of differentially-expressed genes in the dorsal 3V wall compared to the ventral 3V wall and LV wall that may regulate astrogenesis in the dorsal diencephalon. Together, these results demonstrate that the generation of astrocytes shows a spatiotemporal pattern in the developing mouse diencephalon.
Mice ; Animals ; Astrocytes ; Neuroglia/physiology* ; Diencephalon ; Brain ; Neurons ; Mammals

Objective:To understand the infection status, epidemiological characteristics and drug resistance of Diarrheagenic Escherichia coli (DEC) in Shanghai and provide evidence for the disease surveillance. Methods:The epidemiological data of diarrhea cases in Shanghai from 2016 to 2022 were collected from Shanghai Diarrhea Comprehensive Surveillance System, and stool samples were collected from the cases for DEC detection. The drug resistance data was obtained from Chinese Pathogen Identification Network. Statistical analysis was conducted by using χ2 and fisher test. Results:In 24 883 diarrhea cases detected during 2016-2022, the DEC positive rate was 9.13% (2 271/24 883), the single DEC positive rate was 8.83% (2 197/24 883) and the mixed DEC positive rate was 0.30% (74/24 883). The main type of DEC was Enterotoxigenic Escherichia coli (ETEC) [4.33% (1 077/24 883)]. The DEC positive rate was highest in people aged ≤5 years 18.48% (22/119). The annual peak of DEC positive rate was observed during July - September [5.91% (1 470/24 883)]. The DEC positive rate were 9.47% (554/5 847) and 9.02% (1 717/19 036) in urban area and in suburbs, respectively, Enteroaggregative Escherichia coli (EAEC) [3.98% (233/5 847)] and ETEC [4.56% (868/19 036)] were mainly detected. From 2016 to 2019, the DEC positive rate was 9.42% (1 821/19 330), while it was 8.10% (450/5 553) from 2020 to 2022, the main DEC types were ETEC (4.87%, 941/19 330) and EAEC (4.70%, 261/5 553). The multi-drug resistance rate was 40.21% (618/1 537). The top three antibiotics with high drug resistance rates were ampicillin [64.74% (995/1 537)], nalidixic acid [58.49% (899/1 537)] and tetracycline [45.09% (693/1 537)]. Conclusions:Compared with 2016- 2019, a decrease in DEC detection rate was observed during 2020-2022, and the main type of DEC detected shifted from ETEC to EAEC. The prevalence of multi-drug resistance was severe. Therefore, it is necessary to further strengthen the surveillance for DEC drug resistance and standardize the use of clinical antibiotics.

Objective This study analyzes the omics data resources in human-infecting coronavirus animal models collected from various public databases,focusing on data distribution,dataset quantity,data types,species,strains,and research content.It aims to enhance our understanding of biological characteristics and pathogenic mechanisms of coronaviruses,thereby providing a solid foundation for devising effective therapeutic strategies and preventive measures.Methods Query strategies,including specific virus names,time ranges,and inclusion and exclusion criteria,were defined to retrieve data from major public omics databases such as GEO and ArrayExpress.Secondary filtering was performed based on different field types to obtain a more accurate data list.An omics data text database was established for bibliometric analysis.Co-occurrence networks were constructed for the analysis of the correlation strengths between different research themes,technical methods,and involved species.The cell types,organs,and biological pathways involved in studies were examined to further elucidate the pathogenic interplay between pathogens and hosts.Results About twenty public databases containing coronavirus-related omics data were identified,with a primary focus on novel coronavirus infection.Commonly used species include humans,mice,hamsters,and monkeys,while the commonly used virus strains are Wuhan-Hu-1 and USA-WA1/2020.Lung tissues are primarily used in animal models such as mice,macaques,and ferrets,while airway epithelial cells and Calu-3 cells are predominantly employed in human-related studies.Expression profiling data indicate that gene pathways involved in inflammation,cytokine response,complement pathway,cell damage,proliferation,and differentiation are significantly upregulated after infection.Proteomics studies reveal significant changes in phosphoproteome,ubiquitinome,and total proteome of patient samples at different infection stages.Specific protein categories,including viral receptors and proteases,transcription factors,cytokines,proteins associated with coagulation system,angiogenesis-related proteins,and fibrosis markers,show alterations after coronavirus infection.In addition,metabolomics data suggest that phosphocholine,phosphoethanolamine,arachidonic acid,and oleic acid could serve as potential metabolic markers.Epigenomics research indicates m6A methylation plays a role in SARS-CoV-2 replication,infection,and transmission,affecting host cell-virus interactions.Among these,N,S,and non-structural proteins 2 and 3 exhibit the most significant ubiquitination.Trends in microbiomics research suggest that microbial communities in the gut and wastewater are emerging as new research focuses.Conclusion The data types of coronavirus omics are diverse,with a wide variety of models and cell types used.The selection of species and technical methods for modelling varies based on the characteristics of different viruses.Multi-omics data from animal models of coronavirus infection can reveal key interactions between hosts and pathogens,identifying biomarkers and potential therapeutic targets,and provide valuable information for a deeper understanding of biological characteristics and infection mechanisms of coronaviruses.