Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Depression, a prevalent mental disorder with significant socioeconomic burdens, underscores the urgent need for safe and effective non-pharmacological interventions. Recent advances in microbiome research have revealed the pivotal role of gut microbiota dysbiosis in the pathogenesis of depression. Concurrently, exercise, as a cost-effective and accessible intervention, has demonstrated remarkable efficacy in alleviating depressive symptoms. This comprehensive review synthesizes current evidence on the interplay among exercise, gut microbiota modulation, and depression, elucidating the mechanistic pathways through which exercise ameliorates depressive symptoms via the microbiota-gut-brain (MGB) axis. Depression is characterized by gut microbiota alterations, including reduced alpha and beta diversity, depletion of beneficial taxa (e.g., Bifidobacterium, Lactobacillus, and Coprococcus), and overgrowth of pro-inflammatory and pathogenic bacteria (e.g., Morganella, Klebsiella, and Enterobacteriaceae). Metagenomic analyses reveal disrupted metabolic functions in depressive patients, such as diminished synthesis of short-chain fatty acids (SCFAs), impaired tryptophan metabolism, and dysregulated bile acid conversion. For instance, Bifidobacterium longum deficiency correlates with reduced synthesis of neuroactive metabolites like homovanillic acid, while decreased Coprococcus abundance limits butyrate production, exacerbating neuroinflammation. Furthermore, elevated levels of indole derivatives from Clostridium species inhibit serotonin (5-HT) synthesis, contributing to depressive phenotypes. These dysbiotic profiles disrupt the MGB axis, triggering systemic inflammation, neurotransmitter imbalances, and hypothalamic-pituitary-adrenal (HPA) axis hyperactivity. Exercise exerts profound effects on gut microbiota composition, diversity, and metabolic activity. Longitudinal studies demonstrate that sustained aerobic exercise increases alpha diversity, enriches SCFA-producing genera (e.g., Faecalibacterium prausnitzii, Roseburia, and Akkermansia), and suppresses pathobionts (e.g., Desulfovibrio and Streptococcus). For example, a meta-analysis of 25 trials involving 1 044 participants confirmed that exercise enhances microbial richness and restores the Firmicutes/Bacteroidetes ratio, a biomarker of metabolic health. Notably, endurance training promotes Veillonella proliferation, which converts lactate into propionate, enhancing energy metabolism and delaying fatigue. Exercise also strengthens intestinal barrier integrity by upregulating tight junction proteins (e.g., ZO-1, occludin), thereby reducing lipopolysaccharide (LPS) translocation and systemic inflammation. However, excessive exercise may paradoxically diminish microbial diversity and exacerbate intestinal permeability, highlighting the importance of moderate intensity and duration. Exercise ameliorates depressive symptoms through multifaceted interactions with the gut microbiota, primarily via 4 interconnected pathways. First, exercise mitigates neuroinflammation by elevating anti-inflammatory SCFAs such as butyrate, which suppresses NF-κB signaling to attenuate microglial activation and oxidative stress in the hippocampus. Animal studies demonstrate that voluntary wheel running reduces hippocampal TNF‑α and IL-17 levels in stress-induced depression models, while fecal microbiota transplantation (FMT) from exercised mice reverses depressive behaviors by modulating the TLR4/NF‑κB pathway. Second, exercise regulates neurotransmitter dynamics by enriching GABA-producing Lactobacillus and Bifidobacterium, thereby counteracting neuronal hyperexcitability. Aerobic exercise also enhances the abundance of Lactobacillus plantarum and Streptococcus thermophilus, which facilitate 5-HT and dopamine synthesis. Clinical trials reveal that 12 weeks of moderate exercise increases fecal Coprococcus and Blautia abundance, correlating with improved 5-HT bioavailability and reduced depression scores. Third, exercise normalizes HPA axis hyperactivity by reducing cortisol levels and restoring glucocorticoid receptor sensitivity. In rodent models, chronic stress-induced corticosterone elevation is reversed by probiotic supplementation (e.g., Lactobacillus), which enhances endocannabinoid signaling and hippocampal neurogenesis. Furthermore, exercise upregulates brain-derived neurotrophic factor (BDNF) via microbial metabolites like butyrate, promoting histone acetylation and synaptic plasticity. FMT experiments confirm that exercise-induced microbiota elevates prefrontal BDNF expression, reversing stress-induced neuronal atrophy. Fourth, exercise reshapes microbial metabolic crosstalk, diverting tryptophan metabolism toward 5-HT synthesis instead of neurotoxic kynurenine derivatives. Butyrate inhibits indoleamine 2,3-dioxygenase (IDO), a key enzyme in the kynurenine pathway linked to depression. Concurrently, exercise-induced Akkermansia enrichment enhances mucin production, fortifies the gut barrier, and reduces LPS-driven neuroinflammation. Collectively, these mechanisms underscore exercise as a potent modulator of the microbiota-gut-brain axis, offering a holistic approach to alleviating depression through microbial and neurophysiological synergy. Current evidence supports exercise as a potent adjunct therapy for depression, with personalized regimens (e.g., aerobic, resistance, or yoga) tailored to individual microbiota profiles. However, challenges remain in optimizing exercise prescriptions (intensity, duration, and type) and integrating them with probiotics, prebiotics, or FMT for synergistic effects. Future research should prioritize large-scale randomized controlled trials to validate causality, multi-omics approaches to decipher MGB axis dynamics, and mechanistic studies exploring microbial metabolites as therapeutic targets. The authors advocate for a paradigm shift toward microbiota-centric interventions, emphasizing the bidirectional relationship between physical activity and gut ecosystem resilience in mental health management. In conclusion, this review underscores exercise as a multifaceted modulator of the gut-brain axis, offering novel insights into non-pharmacological strategies for depression. By bridging microbial ecology, neuroimmunology, and exercise physiology, this work lays a foundation for precision medicine approaches targeting the gut microbiota to alleviate depressive disorders.

Objective: To construct a quality control evaluation indicator system for the surveillance of common diseases among students, so as to provide a reference for the quality control of surveillance projects. Methods: Based on literature review and expert interviews, a preliminary framework and candidate indicators were developed from June to August in 2024. Twenty domain experts participated in two rounds of Delphi consultations conducted via email, providing importance ratings, judgment basis, familiarity levels, and feasibility assessments for each indicator. And a quality control evaluation indicator system for the surveillance of common diseases among students was ultimately constructed. Results: The consulted experts aged 33-53, with an average age of (45.25±5.03) years, were from government health administration departments( n =1), centers for disease control and prevention at different levels( n =16), academic and research institutions( n =3). Their work experience in school health related fields ranged from 6 to 33 years, with an average of (16.70±8.25) years. The activeness of experts in both rounds of consultation was 100%, the mean expert authority coefficient was 0.90, and the mean feasibility evaluation was 0.75. Kendall s W test showed that the expert coordination coefficient for the first round was 0.26, and for the second round, it was 0.33 ( P <0.01). After two rounds of expert consultation, a set of quality control evaluation indicators for the surveillance of common diseases among students was ultimately constructed, including 6 first level indicators, 19 second level indicators, and 37 third level indicators. Conclusion The scientifically developed evaluation indicator system facilitates high quality implementation of student common disease surveillance programs.

Acupuncture, a therapeutic treatment defined as the insertion of needles into the body at specific points (ie, acupoints), has growing in popularity world-wide to treat various diseases effectively, especially acute and chronic pain. In parallel, interest in the physiological mechanisms underlying acupuncture analgesia, particularly the neural mechanisms have been increasing. Over the past decades, our understanding of how the central nervous system and peripheral nervous system process signals induced by acupuncture has developed rapidly by using electrophysiological methods. However, with the development of neuroscience, electrophysiology is being challenged by calcium imaging in view field, neuron population and visualization in vivo. Owing to the outstanding spatial resolution, the novel imaging approaches provide opportunities to enrich our knowledge about the neurophysiological mechanisms of acupuncture analgesia at subcellular, cellular, and circuit levels in combination with new labeling, genetic and circuit tracing techniques. Therefore, this review will introduce the principle and the method of calcium imaging applied to acupuncture research. We will also review the current findings in pain research using calcium imaging from in vitro to in vivo experiments and discuss the potential methodological considerations in studying acupuncture analgesia.
Calcium ; Acupuncture Therapy ; Acupuncture ; Acupuncture Analgesia/methods* ; Acupuncture Points ; Technology

Aim To analyze the differences in plasma biomarkers and metabolic pathways between Atractylodes chinensis and Atractylodes coreana after intervention in spleen deficiency rats, and discuss the spleen strengthening mechanism of the two from a non targeted metabolomics perspective. Methods A spleen deficiency model was established in SD rats using a composite factor method of improper diet, excessive fatigue, and bitter cold diarrhea. To determine the content of gastrointestinal and immunological indicators, UHPLC-QE-MS technology was used, combined with principal component analysis (PC A) and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) methods to search for biomarkers in plasma of spleen deficiency rats, and metabolic pathways were induced using the Pathway database. Results After administration of Atractylodes chinensis and Atractylodes coreana, various indicators in plasma of spleen deficiency rats showed varying degrees of regression. Metabolomics analysis showed that Atractylodes chinensis and Atractylodes coreana respectively recalled 70 and 82 plasma differential metabolites. Atractylodes chinensis mainly regulated two metabolic pathways : "Glycine, serine, and threonine metabolism, and "Thiamine metabolism". Atractylodes coreana mainly regulated five metabolic pathways, "Glycine, serine, and threonine metabolism", "Thiamine metabolism, "Pyrimidine metabolism", "Butanoate metabolism", and "Riboflavin metabolism". Conclusions Both Atractylodes chinensis and Atractylodes coreana have certain regulatory effects on spleen deficiency rats, and their mechanism of action may be related to regulating metabolic pathways such as "Glycine, serine, and threonine metabolism, and "Thiamine metabolism"in spleen deficiency.

Aim To investigate the molecular mechanism by which quercetin inhibits the malignant behavior of breast cancer cells. Methods Breast cancer cell lines MCF-7 and MB231 were used as the research models. Lentiviral transfection was employed to establish tumor cells with high expression of ERa and MAL-AT-1. The expression of MALAT-1 was assessed using RT-qPCR,and ERa expression was determined through Western blot. Subsequently, CCK-8 assay and colony formation assay were conducted to evaluate cell proliferation. PI staining and adenovirus transfection were performed to observe the inhibitory effects of quercetin on breast cancer cell proliferation. Results 17|3-es-tradiol ( E2 ) promoted the proliferation of MCF-7 breast cancer cells, while 5 jjunol L quercetin reversed the promoting effect of E2 on proliferation ( P 0. 05 ) . Quercetin had no effect on MB231 breast cancer cells. Overexpression of ERa significantly inhibited the pro-proliferative effect of E2 on MB231-ERa cells, and quercetin further suppressed this effect. Additionally , quercetin inhibited the expression of MALAT-1. However,this inhibitory effect was reversed by overexpression of MALAT-1, leading to enhanced cell proliferation , cell cycle progression, and clonal formation a-bility. Conclusions Quercetin exerts its anti-tumor effects on breast cancer cells by regulating MALAT-1, dependent on the presence of estrogen receptor. Quercetin shows potential as a therapeutic drug for breast cancer targeting the estrogen receptor.

Objective To investigate the relationship between nuclear factor(NF)-κB signaling pathway and gender differences in alcoholic liver fibrosis. Methods C57BL/6 N mice at 7-8 weeks of age were randomly divided into: male normal group, male model group, female normal group and female model group of 20 mice each. The normal group was fed with control liquid diet for 8 weeks, and the model group was fed with alcoholic liquid diet for 8 weeks combined with 31.5% ethanol gavage (5g/kg twice a week) to establish an alcoholic liver fibrosis model. The mice were executed at the end of 8 weekends, and the alanine aminotransferase (ALT), aspartate aminotransferase (AST) activity, estradiol (E

Octapeptin has strong antibacterial activity against Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii, while it also has activity against some Gram-positive bacteria. This study used natural octapeptin A3 and B3 as lead compounds for structural modification. Twenty-one peptide derivatives (including A3 and B3) containing eight amino acid residues were prepared by solid-phase synthesis, and evaluated for antibacterial activity and renal cytotoxicity. Among them, three compounds 6, 7 and 17 exhibited broad-spectrum antibacterial activity and significantly enhanced the activity for Gram-positive bacteria while maintaining the activity of Gram-negative bacteria. Several compounds improved the activity for Pseudomonas aeruginosa. Compound 7 was active against all test strains and had relatively low renal cytotoxicity. The results provide a basis for the further development of novel polypeptide antibiotics.

Objective To study the construction of risk prediction model for postoperative recurrence of ad-vanced epithelial ovarian cancer based on serum human epididymis protein 4(HE4),platelet count/lymphocyte count ratio(PLR),relaxin(RLX),karyopherin α2(KPNA2).Methods 124 patients with advanced epithelial o-varian cancer diagnosed and treated in Suzhou Municipal Hospital(East District)from January 2016 to January 2019 were selected as the study objects,patients with advanced epithelial ovarian cancer were divided into re-currence group and the non-recurrence group based on whether they had recurred or not.The level of HE4 was detected by electrochemical luminescence immunoassay,PLR was calculated according to the blood routine re-sults,and RLX and KPNA2 levels were detected by enzyme-related immunosorbent assay.Multivariate Logis-tic regression analysis was used to analyze the influencing factors of postoperative recurrence in patients with advanced epithelial ovarian cancer,and establish a risk prediction model for postoperative recurrence of ad-vanced epithelial ovarian cancer.Receiver operating characteristic(ROC)curve was used to evaluate the pre-dictive efficacy of the model for postoperative recurrence of advanced epithelial ovarian cancer,and Hosmer-Lemeshow test was used to analyze the fitting of recurrence risk prediction model for patients with advanced epithelial ovarian cancer.Results There was a statistically significant difference in International Federation of Gynecology and Obstetrics(FIGO)staging and serum levels of carbohydrate antigen 125,HE4,PLR,RLX and KPNA2 between the recurrence group and the non-recurrence group(P＜0.05).FIGO staging Ⅳ of cancer and elevated serum HE4,PLR,RLX and KPNA2 were risk factors for postoperative recurrence in patients with advanced epithelial ovarian cancer(P＜0.05).ROC curve analysis showed that,the area under the curve of the recurrence risk prediction model for postoperative recurrence risk of advanced epithelial ovarian cancer was 0.859,which was significantly higher than that single indicator detected by HE4,PLR,RLX and KP-NA2.Hosmer-Lemeshow test showed that the recurrence risk prediction model of advanced epithelial ovarian cancer had a good fitting(x2=7.869,P=0.437).Conclusion The risk prediction model for postoperative re-currence of advanced epithelial ovarian cancer based on serum HE4,PLR,RLX,KPNA2 and FIGO staging of cancer has high predictive value for evaluating postoperative recurrence of advanced epithelial ovarian cancer,and deserves clinical attention.