With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

Ulcerative colitis （UC）， which is characterized by a complex and multifactorial etiology， remains one of the challenging disorders in the international field of digestive system diseases. In recent years， rectal administration preparations have made rapid progress in UC therapeutic applications. This study systematically reviews the dosage forms， mechanisms of action， and clinical applications of rectally-administered preparations for the treatment of UC. It is found that suppositories are the most commonly used dosage forms for rectal administration. The newer suppositories have the advantages of high bioavailability and good stability. Enemas can retain the drug in the intestine as much as possible to achieve the effects of diluting intestinal toxins， cleansing the bowel， and reducing inflammation. Gels can achieve a drug-sustained-release effect and effectively improve intestinal mucosal damage. The mechanism of action of this type of preparation is mainly to inhibit inflammatory cell infiltration， regulate intestinal microbial homeostasis， and increase the expression of tight-junction proteins， so as to play anti-inflammatory， regulate the intestinal bacterial flora， repair the intestinal mucosa， and other efficacies. The diversity of rectal administration forms provides a wide range of choices for the clinical treatment of UC， such as Mesalazine suppositories， Lianshao enemas， and temperature- sensitive gels loaded with drugs for UC.

OBJECTIVE: Angiogenesis is a critical target for hepatocellular carcinoma (HCC) treatment. The previous studies indicated that Jiedu Fang (JDF) could inhibit hypoxia-induced angiogenesis through interleukin-8 (IL-8). Therefore, the present study further explores the mechanisms behind JDF's inhibition of HCC angiogenesis. METHODS: Angiogenesis was assessed with the capillary-like tube formation assay in vitro and the matrigel plug angiogenesis assay in vivo. A liver cancer-related gene set and genes associated with angiogenesis and the hypoxic microenvironment were analyzed using a bioinformatics platform. Real-time reverse transcription-polymerase chain reaction and Western blotting assays were used to assess the targeted mRNA and protein levels, respectively. The Transwell assay was used to assess the migration and invasion potential of EA.hy 926 cells. The orthotopic tumor xenograft model was established, and immunohistochemistry and immunofluorescence assays were used to detect cluster of differentiation 31 and angiopoietin 2 expression, while an enzyme-linked immunosorbent assay was used to detect vascular endothelial growth factor and IL-8 protein levels. RESULTS: In vitro and in vivo assays showed that IL-8 promoted angiogenesis, and JDF could antagonize this effect. Bioinformatics analysis indicated that aurora kinase A (Aurora A) was an important candidate, which can promote IL-8 expression through activation of signal transducer and activator of transcription 3 (STAT3). The overexpression of Aurora A increased IL-8 secretion and promoted HCC migration, invasion, and angiogenesis, which was partly inhibited by JDF. Such effects were validated by in vivo assays. Further validation using the STAT3 inhibitor S3I-201 demonstrated that STAT3 was regulated by Aurora A. CONCLUSION JDF exhibits efficacy in reducing hypoxia-induced angiogenesis in HCC through a mechanism involving the Aurora A/STAT3/IL-8 signaling pathway. Therefore, JDF holds promise as a potential therapeutic approach for targeting HCC angiogenesis. Please cite this article as: Zhong MF, Luo YJ, Guo YY, Xiang S, Lin WF. Jiedu Fang inhibits hypoxia-induced angiogenesis in hepatocellular carcinoma by targeting Aurora A/STAT3/IL-8 signaling pathway. J Integr Med. 2025; 23(6):683-693.
Carcinoma, Hepatocellular/blood supply* ; Humans ; STAT3 Transcription Factor/metabolism* ; Interleukin-8/metabolism* ; Liver Neoplasms/blood supply* ; Aurora Kinase A/metabolism* ; Neovascularization, Pathologic/drug therapy* ; Animals ; Signal Transduction/drug effects* ; Mice ; Drugs, Chinese Herbal/therapeutic use* ; Cell Line, Tumor ; Mice, Inbred BALB C ; Mice, Nude ; Angiogenesis

PURPOSE: The rate of complications among patients undergoing surgery has increased due to infection with SARS-CoV-2 and other variants of concern. However, Omicron has shown decreased pathogenicity, raising questions about the risk of postoperative complications among patients who are infected with this variant. This study aimed to investigate complications and related factors among patients with recent Omicron infection prior to undergoing orthopedic surgery. METHODS: A historical control study was conducted. Data were collected from all patients who underwent surgery during 2 distinct periods: (1) between Dec 12, 2022 and Jan 31, 2023 (COVID-19 positive group), (2) between Dec 12, 2021 and Jan 31, 2022 (COVID-19 negative control group). The patients were at least 18 years old. Patients who received conservative treatment after admission or had high-risk diseases or special circumstances (use of anticoagulants before surgery) were excluded from the study. The study outcomes were the total complication rate and related factors. Binary logistic regression analysis was used to identify related factors, and odds ratio (OR) and 95% confidence interval (CI) were calculated to assess the impact of COVID-19 infection on complications. RESULTS: In the analysis, a total of 847 patients who underwent surgery were included, with 275 of these patients testing positive for COVID-19 and 572 testing negative. The COVID-19-positive group had a significantly higher rate of total complications (11.27%) than the control group (4.90%, p < 0.001). After adjusting for relevant factors, the OR was 3.08 (95% CI: 1.45-6.53). Patients who were diagnosed with COVID-19 at 3-4 weeks (OR = 0.20 (95% CI: 0.06-0.59), p = 0.005), 5-6 weeks (OR = 0.16 (95% CI: 0.04-0.59), p = 0.010), or ≥7 weeks (OR = 0.26 (95% CI: 0.06-1.02), p = 0.069) prior to surgery had a lower risk of complications than those who were diagnosed at 0-2 weeks prior to surgery. Seven factors (age, indications for surgery, time of operation, time of COVID-19 diagnosis prior to surgery, C-reactive protein levels, alanine transaminase levels, and aspartate aminotransferase levels) were found to be associated with complications; thus, these factors were used to create a nomogram. CONCLUSION Omicron continues to be a significant factor in the incidence of postoperative complications among patients undergoing orthopedic surgery. By identifying the factors associated with these complications, we can determine the optimal surgical timing, provide more accurate prognostic information, and offer appropriate consultation for orthopedic surgery patients who have been infected with Omicron.
Humans ; COVID-19/complications* ; Male ; Female ; Middle Aged ; Postoperative Complications/epidemiology* ; SARS-CoV-2 ; Orthopedic Procedures/adverse effects* ; Aged ; Nomograms ; Adult ; Retrospective Studies ; Risk Factors

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective: To explore the mechanism by which icariin alleviates viral myocarditis. Methods: CVB3-induced cardiomyocytes were used as an in vitro model of viral myocarditis to assess the effects of icariin treatment on cell viability, inflammation, and apoptosis. Moreover, the effects of icariin on ferroptosis and TLR4 signaling were assessed. After AC16 cells were transfected with TLR4 overexpression plasmids, the role of TLR4 in mediating the regulatory effect of icariin in viral myocarditis was investigated. Results: Icariin significantly elevated cell viability and reduced inflammatory factors TNF-α, IL-1β, IL-6, and IL-18. Flow cytometry revealed that icariin decreased apoptosis rate, and the protein expression of Bax and cleaved caspase 3 and 9 in CVB3-induced cardiomyocytes. Additionally, it suppressed ferroptosis including lipid peroxidation and ferrous ion, as well as the TLR4 signaling. However, TLR4 overexpression abrogated the modulatory effects of icariin. Conclusions: Icariin mitigates CVB3-induced myocardial injury by inhibiting TLR4-mediated ferroptosis. Further animal study is needed to verify its efficacy.

This study was aimed at analyzing the Salmonella infection rate,serotype distribution,and drug resistance rate among children with foodborne diseases in Wuhan,to provide evidence for the prevention and control of foodborne diseases in children.We collected pediatric cases of foodborne diseases and fecal specimens in Wuhan from 2017 to 2022,and conducted statistical analysis in SPSS 22.0.A total of 1 180 cases of foodborne diseases in children were monitored,and 281 strains of Salmonella were detected.Salmonella was distributed across 27 serotypes,primarily Salmonella enteritidis(138 strains,ac-counting for 49.11％)and Salmonella typhimurium(37 strains,accounting for 13.17％).The Salmonella-positive cases in-cluded more boys than girls(1.58∶1 ratio),and the age group with the highest detection rate was 7-18 years(34.48％).The proportion of positive patients gradually decreased,and the detection rate gradually increased,with increasing age.Milk and dairy products,fruits and fruit products,and grain and grain products were the main suspected food exposures with high Sal-monella detection rates.The Salmonella detection rate was highest in the third quarter(44.64％),and significant differences were observed in the positivity rates of Salmonella samples across seasons(x2=178.483,P＜0.05).The main clinical mani-festations of children with Salmonella infection were fever(87.19％)and diarrhea(96.44％),primarily watery stool(51.96％).Salmonella showed different degrees of resistance to 14 antibiotics(1.08％-75.99％),primarily ampicillin(75.99％),tetracycline(68.10％),and cefazolin(50.18％).A significant seasonal pattern was observed in the detection of Sal-monella in foodborne diseases among children in Wuhan,and in various suspected food exposures.The serotype composition was polymorphic,and the Salmonella resistance rate was relatively high.Therefore,active monitoring of foodborne diseases and Salmonella resistance surveillance must continue to be strengthened.

OBJECTIVE: To explore the immunological mechanisms underlying spermatogenetic malfunction in patients with non-obstructive azoospermia (NOA) based on bioinformatics and machine learning, and to screen out the key genes associated with spermatogenesis failure. METHODS: NOA-related datasets were obtained from the GEO database, and the differentially expressed genes identified by differential analysis and weighted gene co-expression network analysis (WGCNA). A model of spermatogenesis scoring was established for analysis of the immunological microenvironment and cell interaction networks related to spermatogenesis failure. The key genes were screened out by machine learning, followed by analysis of their correlation with T cells and macrophages. An NOA mouse model was constructed for validation of transcriptome sequencing. RESULTS: Seventy-five differentially expressed genes were identified for the establishment of the spermatogenesis scoring model. The low spermatogenesis score group showed a higher infiltration of the immune cells, with an increased proportion of T cells and macrophages and a correlation of cell interaction signals with immunity. SOX30, KCTD19, ASRGL1 and DRC7 were identified by machine learning as the key genes related to spermatogenesis, with down-regulated expressions in the NOA group, and their expression levels negatively correlated with the infiltration of T cells and macrophages. The accuracy of the spermatogenesis scoring and machine learning models, as well as the trend of the expression levels of the key genes, was successfully validated with the transcriptome sequencing data on the NOA mouse testis. CONCLUSION The development of NOA is closely associated with enhanced immunological microenvironment in the testis. T cells and macrophages may play important roles in spermatogenesis failure. SOX30, KCTD19, ASRGL1 and DRC7 are potential biomarkers for the diagnosis and treatment of NOA.
Male ; Azoospermia/genetics* ; Machine Learning ; Animals ; Computational Biology ; Mice ; Humans ; Spermatogenesis/genetics* ; Gene Expression Profiling ; Macrophages/immunology* ; Gene Regulatory Networks ; T-Lymphocytes/immunology* ; Transcriptome