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 evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

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 evaluate the diagnostic performance of the minimum-cost-path-based CT angiography-derived fractional flow reserve(MCP-FFR)and the deep learning-driven CT angiography-derived fractional flow reserve(DeepCL-FFR),and to particularly explore the potential value of the DeepCL algorithm in improving diagnostic accuracy within the"gray zone."Methods A retrospective analysis was conducted on 151 coronary vessels from 109 patients with coronary artery disease,who were hospitalized at the General Hospital of the People's Liberation Army between January 2020 and June 2021.Pearson correlation and Bland-Altman plots were employed to assess the correlation and agreement of the two CT-FFR methods with invasive FFR.A CT-FFR range of 0.70-0.80 was defined as the diagnostic"gray zone."The accuracy,sensitivity,specificity,positive predictive value,and negative predictive value for detecting hemodynamic abnormalities were calculated and analyzed.The DeLong test was used to compare the areas under the receiver operating characteristic curves(AUC)between the two CT-FFR calculation methods.Results Both CT-FFR methods exhibited a positive correlation with invasive FFR(MCP-FFR:r=0.75,P＜0.001;DeepCL-FFR:r=0.86,P＜0.001)and showed good agreement(MCP-FFR:mean difference=0.010,P=0.351;DeepCL-FFR:mean difference=-0.003,P=0.772).Both DeepCL-FFR(AUC 0.97,95％CI 0.94-0.99)and MCP-FFR(AUC 0.92,95％CI 0.88-0.97)demonstrated favorable diagnostic performance for detecting hemodynamic abnormalities(P=0.122).In the"gray zone"for hemodynamic abnormality,the diagnostic accuracy of MCP-FFR was 68.8％,whereas DeepCL-FFR increased it to 89.7％.DeepCL-FFR also exhibited superior diagnostic performance(AUC 0.89,95％CI 0.73-0.99)within the"gray zone,"which was significantly higher than that of MCP-FFR(AUC 0.71,95％CI 0.54-0.87)(P＜0.001).Conclusions The deep learning-driven coronary centerline extraction algorithm,DeepCL,demonstrates superior diagnostic performance in CT-FFR for detecting hemodynamic abnormalities,particularly by significantly improving diagnostic accuracy in the"gray zone."

Public health is a public service that is related to the health of the general public in a country or region.This article traces back to 1911-2023 and summarizes the major public health events during multiple periods,inclu-ding the beginning of public health during the Yale period,the initial establishment of Xiangya,and the establish-ment of the Faculty of Health of Hunan Medical College.It is the first systematic compilation of the history of Xiangya public health discipline.The milestones in the history of Xiangya public health discipline are as follows:(1)Dr.Yan Fuqing was the founder of health and public health around the establishment of Xiangya,and is the first person to propose the term'public health'.(2)The course of Health and Public Health in Xiangya began in 1916 and was offered in the academic year of 1918-1919.(3)Until the establishment of the Faculty of Health in 1975,the course of Health and Public Health was compulsory for Xiangya students.(4)In 1988,the Faculty of Health was renamed as the Faculty of Preventive Medicine,and the Institute of Preventive Medicine was established;In 1995,it was renamed as the School of Public Health of Hunan Medical University.In April 2000,after the merger and es-tablishment of Central South University,it was renamed as the School of Public Health of Central South University;In 2015,it was renamed as Xiangya School of Public Health of Central South University.Xiangya Public Health has been involved in almost all major public health work in China since its beginning,adhering to the principle of preven-tion first,promoting and serving people's health.

Objective:To explore the relationship between risk perception and health promoting lifestyle profile in population with cardiovascular disease (CVD), and construct a prediction model for clinical screening and targeted intervention.Methods:A cross-sectional survey method was used to select 272 people at moderate and high risk of CVD from the Second Affiliated Hospital of Zhejiang University School of Medicine from March to August 2022. The general information questionnaire, Chinese version of Attitude and Beliefs about Cardiovascular Disease Knowledge and Risk Questionnaire (ABCD-C), and Health Promoting Lifestyle Profile-II (HPLP Ⅱ) were used. Based on multiple regression analysis, a nomogram model for health promoting lifestyle in high-risk CVD population was constructed.Results:Among 272 participants, male 150 cases, female 122 cases, aged (60.58 ± 10.64) years old. The total ABCD-C score was (56.57 ± 5.69), and the total HPLP Ⅱ score was (111.92 ± 12.47). ABCD-C score was significantly positively correlated with HPLP Ⅱ score ( r=0.556, P<0.01). The median of HPLP Ⅱ total score (111 points) was used as the cut-off point for low level of health-promoting lifestyle (≤111 points) and high level of health-promoting lifestyle (>111 points), and used it as the dependent variable, smoking ( OR=0.215, 95% CI 0.104-0.446) was a barrier factor for participants to adopt healthy lifestyle; being married ( OR=14.237, 95% CI 1.963-103.238), having a family average monthly income higher than 5 000 yuan ( OR=4.101, 95% CI 1.369-12.288), higher score of CVD prevention knowledge ( OR=1.660, 95% CI 1.373-2.007), perceived benefits and intention to change physical activity ( OR=1.445, 95% CI 1.255-1.663), perceived benefits and intention to change healthy diet ( OR=1.322, 95% CI 1.058-1.654) were promoting factors. Conclusions:The health-promoting lifestyle of populations at risk for CVD is above-average, influenced by factors such as smoking, marital and economic status, risk attitudes, and beliefs. Utilizing the nomogram model for early screening and targeted risk communication among key populations may contribute to improving their health behavior.

Redirecting immune cells to the tumor cells and enhancing its anti-tumor immune response is a very promising cancer treatment strategy. AS1411 aptamers have high affinity for malignant tumors with high nucleolin expression, and cytotoxic T lymphocyte associated protein 4 (CTLA-4) aptamers can specifically bind to CTLA-4, which is expressed by T cells. In this study, a dual-affinity aptamer targeted liposome (Dat. Lipo) was constructed based on AS1411 aptamer and CTLA-4 aptamer, and its immunotherapeutic effect on T cells was studied. After the aptamer was modified with cholesterol, Dat. Lipo was prepared by instillation method; its effect of redirecting T cells was determined by confocal micrographs; its T cell immunotherapy effect was evaluated by cell counting kit-8 (CCK8) and T cell penetration was evaluated by tumor spheroids. The results showed that compared with liposomes loaded with one type aptamer, Dat. Lipo could effectively promote the redirection of T cells to tumor cells; Dat. Lipo had good biosafety and immunotherapeutic effect on MCF-7 and HepG2 cells in a concentration-dependent manner; Dat. Lipo could also promote T cells to infiltrate into the tumor spheroids and enhance the immunotherapy effect of T cells in different dimensions. In summary, Dat. Lipo can use the high affinity of aptamers to redirect T cells to tumor cells, enhance the effect of immunotherapy, and has a promising application prospect in tumor therapy. This study was approved by the Examination Committee of Cancer Hospital of Xiangya School of Medicine, Central South University, Hunan Cancer Hospital.

OBJECTIVE: To explore the mechanism that mediates the effect of soybean isoflavones (SI) against cerebral ischemia/reperfusion (I/R) injury in light of the regulation of regional cerebral blood flow (rCBF), ferroptosis, inflammatory response and blood-brain barrier (BBB) permeability. METHODS: A total of 120 male SD rats were equally randomized into sham-operated group (Sham group), cerebral I/R injury group and SI pretreatment group (SI group). Focal cerebral I/R injury was induced in the latter two groups using a modified monofilament occlusion technique, and the intraoperative changes of real-time cerebral cortex blood flow were monitored using a laser Doppler flowmeter (LDF). The postoperative changes of cerebral pathological morphology and the ultrastructure of the neurons and the BBB were observed with optical and transmission electron microscopy. The neurological deficits of the rats was assessed, and the severities of cerebral infarction, brain edema and BBB disruption were quantified. The contents of Fe²⁺, GSH, MDA and MPO in the ischemic penumbra were determined with spectrophotometric tests. Serum levels of TNF-α and IL-1βwere analyzed using ELISA, and the expressions of GPX4, MMP-9 and occludin around the lesion were detected with Western blotting and immunohistochemistry. RESULTS: The rCBF was sharply reduced in the rats in I/R group and SI group after successful insertion of the monofilament. Compared with those in Sham group, the rats in I/R group showed significantly increased neurological deficit scores, cerebral infarction volume, brain water content and Evans blue permeability (P < 0.01), decreased Fe²⁺ level, increased MDA level, decreased GSH content and GPX4 expression (P < 0.01), increased MPO content and serum levels of TNF-α and IL-1β (P < 0.01), increased MMP-9 expression and lowered occludin expression (P < 0.01). All these changes were significantly ameliorated in rats pretreated with IS prior to I/R injury (P < 0.05 or 0.01). CONCLUSION SI preconditioning reduces cerebral I/R injury in rats possibly by improving rCBF, inhibiting ferroptosis and inflammatory response and protecting the BBB.
Rats ; Male ; Animals ; Rats, Sprague-Dawley ; Matrix Metalloproteinase 9/metabolism* ; Soybeans/metabolism* ; Occludin/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Ferroptosis ; Blood-Brain Barrier/ultrastructure* ; Brain Ischemia/metabolism* ; Cerebral Infarction ; Reperfusion Injury/metabolism* ; Isoflavones/therapeutic use* ; Infarction, Middle Cerebral Artery

Objective:The investigation and research on the application status of Hepatic Venous Pressure Gradient (HVPG) is very important to understand the real situation and future development of this technology in China.Methods:This study comprehensively investigated the basic situation of HVPG technology in China, including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications and existing problems.Results:According to the survey, there were 70 hospitals in China carrying out HVPG technology in 2021, distributed in 28 provinces (autonomous regions and municipalities directly under the central Government). A total of 4 398 cases of HVPG were performed in all the surveyed hospitals in 2021, of which 2 291 cases (52.1%) were tested by HVPG alone. The average cost of HVPG detection was (5 617.2±2 079.4) yuan. 96.3% of the teams completed HVPG detection with balloon method, and most of the teams used thrombectomy balloon catheter (80.3%).Conclusion:Through this investigation, the status of domestic clinical application of HVPG has been clarified, and it has been confirmed that many domestic medical institutions have mastered this technology, but it still needs to continue to promote and popularize HVPG technology in the future.