Objective To analyze the clinical manifestations of patients over 60 years old with acute respiratory infection in Pudong New Area of Shanghai and the risk factors of positive detection of novel coronavirus, and to provide reference for improving prevention and control strategies and measures. Methods General conditions, clinical features, basic complications and respiratory samples of inpatients over 60 years old with acute respiratory infection from eight hospitals in Pudong New Area of Shanghai from January to October 2023 were collected, and SARS-CoV-2 detection was carried out. Chi-square test and binary logistics regression were used for data analysis. Results A total of 604 patients over 60 years old were collected, including 356 (58.945) males with a median age of 77 (IQR:70-85) years. Of the 604 cases, 264 were detected positive for SARS-CoV-2, with a positive detection rate of 43.71%. The results of univariate analysis showed that there were significant differences in the detection rates of SARS-CoV-2 among different age groups (χ²=10.60, P=0.01) and different months (χ²=87.15, P=0.00), and among those with cough (χ²=5.28, P=0.02), sputum (χ²=4.19, P=0.04), sore throat (χ²=3.93, P=0.04), and hypertension (χ²=7.63, P=0.01). In the binary logistics regression analysis, month (P=0.00, OR=2.93, 95% CI=1.49-5.78) and age (P=0.00, OR=2.60, 95% CI=1.55-4.37) were independent risk factors for positive detection of SARS-CoV-2. Conclusion The majority of hospitalized cases of acute respiratory infection over 60 years old are male, and the risk factors for positive detection of novel coronavirus are age 80~89 years old and time between May and June.

Diabetic kidney disease（DKD） is a chronic kidney structural and functional disorder caused by diabetes. With the global prevalence of diabetes continuing to rise， DKD has gradually become a major cause of chronic kidney disease and end-stage renal disease（ESRD）， posing a serious threat to patients' quality of life and long-term health outcomes. Studies have shown that apoptosis plays a pivotal role in the development and progression of DKD， with its mechanisms involving abnormal activation of multiple signaling pathways such as Toll-like receptor 4（TLR4）/nuclear transcription factor-κB（NF-κB）/B-cell lymphoma-2（Bcl-2）/cysteinyl aspartate-specific proteinase（Caspase）-3， protein kinase R-like endoplasmic reticulum kinase（PERK）/eukaryotic initiation factor 2α（eIF2α）/activating transcript factor 4（ATF4）/CCAAT enhancer-binding protein homologous protein（CHOP）， phosphatidylinositol 3-kinase（PI3K）/protein kinase B（Akt）/glycogen synthase kinase-3β（GSK-3β）， Janus kinase 2（JAK2）/signal transducer and activator of transcription 3（STAT3）， adenosine monophosphate-activated protein kinase（AMPK）/mammalian target of rapamycin（mTOR） and silent information regulator 1（SIRT1）/tumor suppressor protein 53（p53）， thereby accelerating renal pathological damage in DKD. Extensive evidence-based medical studies have confirmed that traditional Chinese medicine（TCM）， leveraging its unique therapeutic advantages of multi-target， multi-component and multi-pathway approaches， has demonstrated remarkable efficacy and favorable safety profiles in treating DKD. Recent studies have demonstrated that active components of TCM can specifically target and modulate key effectors in apoptotic signaling pathways. Meanwhile， traditional compound formulations exert synergistic effects through multiple approaches such as replenishing deficiency and activating blood circulation， detoxifying and dredging collaterals， tonifying kidney essence， and removing stasis and purging turbidity， thereby comprehensively regulating critical pathological processes including endoplasmic reticulum stress and mitochondrial apoptosis pathways. This combined therapeutic approach of molecular targeting and holistic regulation provides novel strategies for delaying the progression of DKD. Based on this， this paper provides an in-depth analysis of key apoptotic signaling pathways and their regulatory mechanisms， while systematically summarizing recent research advances regarding the therapeutic effects of TCM active components， compound formulations， and proprietary Chinese medicines on DKD through modulation of these pathways， with particular emphasis on their underlying molecular mechanisms. These findings not only elucidate the modern scientific connotation and theoretical basis of TCM in treating DKD but also establish a solid theoretical and practical foundation for promoting the wider clinical application and further research of TCM in the field of DKD treatment.

Abstract Recently, the Ministry of Education issued Guiding Opinions on Comprehensively Promoting the Construction of Healthy Schools hereinafter referred to as the Guiding Opinions, which systematically established the goal system, key tasks, critical measures, and safeguard mechanisms for the construction of healthy schools in the new era. Against the backdrop, comprehensively promoting the construction of healthy schools has become a core project for implementing the concept of "Health First", carrying out joint prevention and control of multiple diseases, and responding to national action plans. Based on a systematic analysis of the internal logic between healthy school construction and the "education powerhouse strategy", the study deeply expounds on its core mission as a "foundational project for talent cultivation" and a "hub for the integration of five educations". Combining the eight key tasks and three critical measures clarified in the Guiding Opinions, it constructs a multi dimensional, systematic, and operable implementation path from the aspects of concept leadership and practice internalization, data monitoring and closed loop management, team support and environmental optimization, literacy promotion and evaluation innovation, innovation drive and characteristic development,digital empowerment and smart governance. The study provides a forward looking and strategic comprehensive solution for improving the collective health literacy of students and building a comprehensive prevention and control system for common campus diseases in the new era.

Idiopathic pulmonary fibrosis (IPF), a chronic interstitial lung disease, is characterized by aberrant wound healing, excessive scarring and the formation of myofibroblastic foci. Although the role of alternative splicing (AS) in the pathogenesis of organ fibrosis has garnered increasing attention, its specific contribution to pulmonary fibrosis remains incompletely understood. In this study, we identified an up-regulation of serine/arginine-rich splicing factor 7 (SRSF7) in lung fibroblasts derived from IPF patients and a bleomycin (BLM)-induced mouse model, and further characterized its functional role in both human fetal lung fibroblasts and mice. We demonstrated that enhanced expression of Srsf7 in mice spontaneously induced alveolar collagen accumulation. Mechanistically, we investigated alternative splicing events and revealed that SRSF7 modulates the alternative splicing of pyruvate kinase (PKM), leading to metabolic dysregulation and fibroblast activation. In vivo studies showed that fibroblast-specific knockout of Srsf7 in conditional knockout mice conferred resistance to bleomycin-induced pulmonary fibrosis. Importantly, through drug screening, we identified lomitapide as a novel modulator of SRSF7, which effectively mitigated experimental pulmonary fibrosis. Collectively, our findings elucidate a molecular pathway by which SRSF7 drives fibroblast metabolic dysregulation and propose a potential therapeutic strategy for pulmonary fibrosis.

The coinfection of respiratory viruses and bacteria is a major cause of morbidity and mortality worldwide, despite the development of vaccines and powerful antibiotics. As a macromolecule that is difficult to absorb in the gastrointestinal tract, a homogeneous polysaccharide from Houttuynia cordata (HCPM) has been reported to exhibit anti-complement properties and alleviate influenza A virus (H1N1)-induced lung injury; however, the effects of HCPM without in vitro antiviral and antibacterial activities on more complicated pulmonary diseases resulting from viral-bacterial coinfection remains unclear. This study established a representative coinfection murine pneumonia model infected with H1N1 (0.2 LD₅₀) and methicillin-resistant Staphylococcus aureus (MRSA, 10⁷ CFU). HCPM significantly improved survival rate and weight loss, and ameliorated gut-lung damage and inflammatory cytokine production. Interestingly, the therapeutic effect of HCPM on intestinal damage preceded that in the lungs. Mechanistically, HCPM inhibited the overactivation of the intestinal complement (C3a and C5a) and suppressed the activation of the NLR family pyrin domain-containing 3 (NLRP3) pathway, which contributes to the regulation of the Treg/Th17 cell balance in the gut-lung axis. The results indicate the beneficial effects of an anti-complement polysaccharide against viral-bacterial coinfection pneumonia by modulating crosstalk between multiple immune regulatory networks.

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Objective: To explore the relationship between related factors of non-suicidal self-injury behavior (NSSI) among middle school students in Guizhou Province, so as to provide the evidence for preventing high risk behaviors in adolescents. Methods: A stratified cluster random sampling method was used to select 1 034 junior and senior middle school students from Zunyi City, Qiannan Prefecture and Tongren City in Guizhou Province from April to October in 2023. Questionnaire survey was conducted to collect information including Adolescent Self injury Scale and Family Assessment Device. The R 4.4.1 software was employed for network analysis visualization, centrality indicators, and result stability assessment. Results: The detection rate of NSSI behavior among middle school students in Guizhou province was 29.6%, with a detection rate of 25.5% for boys and 33.1% for girls, showing a statistically significant difference ( χ 2=7.07, P <0.05). There were statistically significant differences in scores of emotional communication, egoism, family rules, positive communication, problem solving, expression of positive emotions and management of negative emotions self-efficacy, and bullying victimization in various dimensions between middle school students with and without NSSI ( Z =-13.66 to -7.05, P <0.01). NSSI among middle school students was positively correlated with social/relational bullying, depression and anxiety, and there were relatively close connections in the network ( r =0.35, 0.43, 0.42, P <0.01). Centrality indicators showed that the highest in strength and closeness centrality were stress ( Z =1.29, 1.58), the highest in betweenness centrality was for emotional communication ( Z =1.91), and the highest in expected influence index was for physical bullying ( Z =1.44)( P < 0.05). Conclusions Stress, emotional communication and physical bullying have significant impacts in the network of factors related to NSSI. Social/relational bullying, depression and anxiety have strong direct correlations with NSSI behavior among middle school students.

Objective To screen ferroptosis genes related to the prognosis of cervical cancer and to construct a prognosis model. Methods Ferroptosis genes were obtained from FerrDb database, and cervical cancer related data were obtained from The Genome-Wide Association Study Catalog database and The Cancer Genome Atlas database. Transcriptome-Wide Association Study, colocalization analysis and differential expression analysis were conducted to screen out candidate ferroptosis genes; Gene Ontology functional and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were conducted on candidate genes. Univariate Cox regression analysis was used to further screen out genes related to the prognosis of cervical cancer. Kaplan-Meier method was used to analyze the relationship between genes and the overall survival of patients. The expression levels of genes in pan-cancer were analyzed through the TIMER database. Two prognostic models were conducted, Model 1 included age and tumor stage, while Model 2 incorporated age, tumor stage, and prognostic genes. The predictive capabilities of the two models were compared. Results A total of 91 candidate genes related to ferroptosis were obtained. Univariate Cox regression analysis showed that 15 genes were associated with the prognosis of cervical cancer. CA9, SCD, TFRC, QSOX1 and CDO1 were risk factors affecting the prognosis of cervical cancer patients (P＜0.05), while PTPN6, ALOXE3, HELLS, IFNG, MIOX, ALOX12B, DUOX1, ALOX15, AQP3 and IDO1 were protective factors (P＜0.05). The mRNA expression levels of the 15 genes showed significant upregulation or downregulation in at least 7 types of cancers, among which TFRC was associated with the largest number of cancer types. Kaplan-Meier analysis showed that HELLS, DUOX1 and ALOXE3 were associated with poor prognosis in cervical cancer. The AUC of the model 1 for predicting 1-year and 3-year overall survival rates of cervical cancer patients was 0.455 and 0.478, and the AUC of Model 2 was 0.854 and 0.595. Model 2 (C-index = 0.727) had better predictive ability than Model 1 (C-index = 0.502). Conclusion The prognostic model composed of 15 prognostic-related genes selected based on bioinformatics has better predictive performance for the survival outcomes of cervical cancer patients, providing important reference value for the prognostic assessment of cervical cancer patients.