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.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

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.

In the aftermath of the pandemic,the government is accelerating the development of top-tier medical resources to broaden the supply and deliver superior healthcare services.However,during this transitional phase,hospitals are experiencing operational challenges due to concurrent construction activities.Notably,a shortage of parking facilities and increased traffic con-gestion continue to impactmedial consultation experience of patients.This paper tries to explore strategies and methods for dynam-ic parking management during hospital campus expansions,offering insights for other medical institutions into grappling with pa-tient parking issues.

Objective To discuss the clinical value of systemic immune-inflammation index(SII)in predicting the prognosis of patients with extrahepatic cholangiocarcinoma(ECCA)treated with biliary stenting combined with 125I seeds implantation.Methods A total of 128 patients with unresectable ECCA,who received biliary stenting combined with 125I seeds implantation at the Interventional Department of the Affiliated Hospital of Xuzhou Medical University of China between August 2018 and August 2021,were enrolled in this study.The peripheral blood routine testing was performed within 3 days before operation,based on which the SII was calculated.Receiver operating characteristic(ROC)curve was applied to determine the optimal cut-off value of SII,based on which the patients were divided into high-SII group and low-SII group.Cox regression model was used to analyze the independent factors affecting patient prognosis.The Kaplan-Meier curve was plotted to analyze the one-year survival.Results The optimal cut-off value of SII was 1 050,the sensitivity was 66.0％,the specificity was 69.3％,and the area under ROC curve of SII was 0.676.The one-year survival rate of patients with ECCA in the high-SII group was significantly lower than that in the low-SII group(P＜0.05).Univariate Cox regression analysis indicated that vascular invasion,T stage,adjuvant chemotherapy,CA19-9,and preoperative SII were the important factors affecting the prognosis of patients with ECCA.Multivariate Cox regression analysis revealed that T stage,CA19-9,and preoperative SII were the independent risk factors for patient prognosis,while adjuvant chemotherapy was a protective factor.The Kaplan-Meier curves showed that the one-year survival rate in high-SII group was remarkably lower than that in the low-SII group.Conclusion Preoperative SII has an important value in evaluating the prognosis of patients with ECCA who are treated with biliary stenting combined with 125I seed implantation.(J Intervent Radiol,2023,32:1221-1225)

Animal survival necessitates adaptive behaviors in volatile environmental contexts. Virtual reality (VR) technology is instrumental to study the neural mechanisms underlying behaviors modulated by environmental context by simulating the real world with maximized control of contextual elements. Yet current VR tools for rodents have limited flexibility and performance (e.g., frame rate) for context-dependent cognitive research. Here, we describe a high-performance VR platform with which to study contextual behaviors immersed in editable virtual contexts. This platform was assembled from modular hardware and custom-written software with flexibility and upgradability. Using this platform, we trained mice to perform context-dependent cognitive tasks with rules ranging from discrimination to delayed-sample-to-match while recording from thousands of hippocampal place cells. By precise manipulations of context elements, we found that the context recognition was intact with partial context elements, but impaired by exchanges of context elements. Collectively, our work establishes a configurable VR platform with which to investigate context-dependent cognition with large-scale neural recording.
Animals ; Mice ; Rodentia ; Virtual Reality ; Cognition ; Recognition, Psychology

Biofilms are closely associated with the tough healing and dysfunctional inflammation of chronic wounds. Photothermal therapy (PTT) emerged as a suitable alternative which could destroy the structure of biofilms with local physical heat. However, the efficacy of PTT is limited because the excessive hyperthermia could damage surrounding tissues. Besides, the difficult reserve and delivery of photothermal agents makes PTT hard to eradicate biofilms as expectation. Herein, we present a GelMA-EGF/Gelatin-MPDA-LZM bilayer hydrogel dressing to perform lysozyme-enhanced PTT for biofilms eradication and a further acceleration to the repair of chronic wounds. Gelatin was used as inner layer hydrogel to reserve lysozyme (LZM) loaded mesoporous polydopamine (MPDA) (MPDA-LZM) nanoparticles, which could rapidly liquefy while temperature rising so as to achieve a bulk release of nanoparticles. MPDA-LZM nanoparticles serve as photothermal agents with antibacterial capability, could deeply penetrate and destroy biofilms. In addition, the outer layer hydrogel consisted of gelatin methacryloyl (GelMA) and epidermal growth factor (EGF) promoted wound healing and tissue regeneration. It displayed remarkable efficacy on alleviating infection and accelerating wound healing in vivo. Overall, the innovative therapeutic strategy we came up with has significant effect on biofilms eradication and shows promising application in promoting the repair of clinical chronic wounds.