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.

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.

Nonalcoholic fatty liver disease （NAFLD） is a multisystem disease associated with obesity， insulin resistance， and dyslipidemia and has a complex pathogenesis. Studies have shown that gut microbiota dysbiosis is closely associated with the onset of NAFLD， and traditional Chinese medicine treatment can improve the laboratory markers and clinical symptoms of NAFLD patients by regulating intestinal microbiota and its metabolites. This article elaborates on the association between NAFLD and gut microbiota， the involvement of gut microbiota dysbiosis in the pathogenesis of NAFLD， and the possible mechanism of traditional Chinese medicine treatment in improving NAFLD from the perspective of gut microbiota， in order to provide new ideas for the treatment of NAFLD.

Objective To investigate the population characteristics,distribution of traditional Chinese medicine(TCM)syndromes and influencing factors of long-term prognosis of diarrhea-predominant irritable bowel syndrome(IBS-D),and to provide evidence for the formulation of intervention program for IBS-D patients.Methods A total of 124 patients with IBS-D admitted to the medical institutions of the project team members from July 2020 to August 2022 were selected.According to the scoring results of IBS Quality of Life Measure(IBS-QOL),the patients were divided into the good prognosis group(81 cases)and the poor prognosis group(43 cases).The distribution of TCM syndromes in patients with IBS-D was explored,and the difference of IBS-QOL scores of the patients between good prognosis group and poor prognosis group was compared.Univariate logistic regression analysis and multivariate logistic regression analysis were used to determine the main risk factors for poor prognosis in patients with IBS-D.Results(1)The analysis of population characteristics showed that there was no significant difference in the proportion of male and female patients with IBS-D.The patients with IBS-D were usually middle-aged,and had a large interval span of the course of disease.The severity of their symptoms was mostly moderate.All of the patients with IBS-D had various degrees of anxiety and depression,and had nutritional imbalance.(2)The distribution of TCM syndromes in the patients with IBS-D were shown as the following:78 cases were identified as liver depression and spleen deficiency type,accounting for 62.90％;26 cases were identified as spleen-qi deficiency type,accounting for 20.97％;20 cases were identified as spleen and kidney yang deficiency type,accounting for 16.13％.(3)Analysis of IBS-QOL score showed that compared with the good prognosis group,the items scores of negative emotion,physical function,behavioral disorder,health status,being fastidious about food,social function,sexual behavior and interpersonal relationship of IBS-QOL in the poor prognosis group were significantly lowered(P＜0.01).(4)The univariate analysis showed that the risk of poor prognosis in patients with IBS-D would be increased by the factors of age,education level,course of disease,severity of symptoms,anxiety state,depression state,TCM syndrome types,Acute Physiology and Chronic Health Evaluation scoring system Ⅱ(APACHE 11)score,complication of neurological diseases,hemoglobin level,albumin level and total protein level(P＜0.01).(5)The multivariate Logistic regression analysis showed that the risk factors for poor prognosis of IBS-D patients involved age,education level below junior high school,the severity of symptoms being severe,Self-Rating Anxiety Scale(SAS)score,Self-Rating Depression Scale(SDS)score,TCM syndrome being liver depression and spleen deficiency type,hemoglobin level,albumin level and total protein level(P＜0.01).Conclusion Most of IBS-D patients exert long-term poor prognosis,and their long-term prognosis is affected by the factors of age,education level,severity of symptoms,anxiety and depression state,nutritional imbalance and TCM syndrome being liver depression and spleen deficiency type.The identification of the risk factors of poor prognosis will provide evidence for the formulation and adjustment of clinical intervention programs.

Objective To achieve automatic segmentation of cell nuclei in gastrointestinal cancer pathological images by using a deep learning algorithm,so as to assist in the quantitative analysis of subsequent pathological images.Methods A total of 59 patients with gastrointestinal cancer treated in Ruijin Hospital,Shanghai Jiao Tong University School of Medicine from Jan 2022 to Feb 2022,were selected as the research objects.Python and LabelMe were used for data anonymization,image segmentation,and region of interest annotation of patients'pathological images.A total of 944 pathological images were included,and 9 703 nuclei were annotated.Then,a new semantic segmentation model based on deep learning was constructed.The model introduced deformable attention transformer(DAT)to realize automatic,accurate and efficient segmentation of pathological image nuclei.Finally,multiple segmentation evaluation criteria are used to evaluate the model's performance.Results The mean absolute error of the segmentation results of the model proposed in this paper was 0.112 6,and the dice coefficient(Dice)was 0.721 5.Its effect was significantly better than the U-net baseline model,and it was ahead of models such as ResU-net++,R2Unet and R2AttUnet.Moreover,the segmentation results were relatively stable with good generalization.Conclusion The segmentation model established in this study can accurately identify and segment the nuclei in the pathological images,with good robustness and generalization,which is helpful to play an auxiliary diagnostic role in practical applications.

Objective:To investigate the current situation of diet management in patients with colorectal cancer after stent-based diverting technique, and to provide basis for formulating relevant nursing intervention strategies.Methods:Objective sampling method was used to conduct semi-structured interviews on 15 patients who underwent stent-based diverting technique for colorectal cancer and had the bypass tube removed from Sir Run Run Shaw Hospital Affiliated to Medical College of Zhejiang University from March to July 2023. The interview outline was established based on information-motivation-behavioral skills(IMB) model, and the data were analyzed, summarized and extracted by Colaizzi 7-step analysis method.Results:There were 10 males and 5 females, aged 34-76 years old. According to the three elements of the IMB model, the current situation of diet management was summarized into nine themes. The information included the difficulty in obtaining effective diet guidance information, the lack of specific diet guidance content, the need for individualized diet information guidance mode, and the poor continuity of information exchange after discharge. The motivations included ignoring the importance of diet management, dislike the taste of oral nutritional preparations, and weak support from family members. Behavioral skills include inadequate tube care skills and lack of oral nutrition preparation skills.Conclusions:There are many problems in the diet management of patients after colorectal cancer stent-based diverting technique. Medical staff should optimize the diet education information of colorectal cancer patients after surgery, provide multi-level, multi-time and multi-form continuous care, mobilize the active participation of family members, improve the motivation of patients′ diet management, refine the nursing process of the bypass tube, strengthen the application guidance of oral nutrition preparation skills, and improve patients′ diet management ability.

Objective To construct an artificial intelligence assisted diagnosis model based on deep learning for dynamically recognizing gastric lesions and their locations under gastroscopy in real time,and to evaluate its ability to detect and recognize gastric lesions and their locations.Methods The gastroscopy videos of 104 patients in our hospital was retrospectively analyzed,and the video frames were manually annotated.The annotated picture frames of lesion category were divided into the training set and the validation set according to the ratio of 8∶2,and the annotated picture frames of location category were divided into the training set and the validation set according to the patient sources at the ratio of 8∶2.These sets were utilized for training and validating the respective models.YoloV4 model was used for the training of lesion recognition,and ResNet152 model was used for the training of location recognition.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value and location recognition accuracy of the auxiliary diagnostic model were evaluated.Results A total of 68 351 image frames were annotated,with 54 872 frames used as the training set,including 41 692 frames for lesion categories and 13 180 frames for location categories.The validation set consisted of 13 479 frames,comprising 10 422 frames for lesion categories and 3 057 frames for location categories.The lesion recognition model achieved an overall accuracy of 98.8%,with a sensitivity of 96.6%,specificity of 99.3%,positive predictive value of 96.3%,and negative predictive value of 99.3% in validation set.Meanwhile,the location recognition model demonstrated an top-5 accuracy of 87.1% .Conclusion The artificial intelligence assisted diagnosis model based on deep learning for real-time dynamic recognition of gastric lesions and their locations under gastroscopy has good ability in lesion detection and location recognition,and has great clinical application prospects.

Peroxisome proliferator-activated receptor gamma(PPAR-γ)is a member of the ligand-activated nuclear tran-scription factor superfamily.Activated PPAR-γ is involved in the regulation of many central nervous system(CNS)events,and is involved in cholesterol metabolism by inducing or inhibi-ting a series of gene pathways,thereby inhibiting the deposition of β-amyloid protein(Aβ).It plays an important neuroprotec-tive role in Alzheimer's disease(AD),improves memory and cognition in AD,and is a potential target for AD.Drug develop-ment aimed at restoring cholesterol homeostasis may be a poten-tial strategy to counteract AD.By analyzing the distribution and structure of PPAR-γ,focusing on the biological correlation be-tween PPAR-γ-mediated cholesterol metabolism and AD,this paper describes the mechanism regulation of PPAR-γ on key proteins,genes and their corresponding molecules,providing a new reference for the treatment of AD.

This study systematically reviewed the randomized controlled trial(RCT) of traditional Chinese medicine(TCM) treatment of coronary heart disease patients with angina pectoris after percutaneous coronary intervention(PCI). The basic elements of these RCTs, including sample size and estimation method, randomizing scheme, allocation concealment, blind method implementation, data integrity, statistical method, TCM syndrome, intervention measures, treatment course, follow-up time, and outcome indicators, were analyzed to provide reference for the design of future RCT and the clinical application of TCM in treating angina pectoris after PCI. CNKI, Wanfang, VIP, SinoMed, PubMed, EMbase, Cochrane Library, Web of Science, ClinicalTrials.gov, and Chinese Clinical Trial Registry were searched for the RCT about TCM treatment of coronary heart disease patients with angina pectoris after PCI according to pre-defined criteria, with the time interval from inception to January 31, 2024. A total of 188 RCTs were included, of which 184 were clinical research articles and 4 were clinical trial registration schemes. These RCTs involved a total of 15 521 patients, with an average sample size of 83 patients and a maximum sample size of 248 patients. Among them, 126 RCTs reported TCM syndromes, the top three of which were Qi deficiency and blood stasis(38.89%), phlegm combined with stasis(17.46%), and Qi stagnation and blood stasis(9.52%). The control group received guideline-directed medical therapy(GDMT) or GDMT combined with placebo, and the treatment group received GDMT combined with TCM. The treatment mainly lasted for 4-8 weeks, most of the RCTs did not set the follow-up period or the follow-up period was unknown. A total of 160 outcome indicators were used, with the total frequency of 1 348. According to functional attributes, the outcome indicators can be categorized into 6 groups: symptoms/signs(403, 29.90%), TCM syndromes/symptoms(182, 13.50%), physical and chemical examination(468, 34.72%), quality of life(89, 6.60%), long-term prognosis(5, 0.37%), and safety evaluation(201, 14.91%). The clinical trial design of TCM intervention in angina pectoris after PCI of coronary heart disease is becoming more and more rigorous, while it remains to be improved. It is expected that more clinical trial schemes with rigorous design and taking into account the TCM advantages can be adopted in the future to provide a basis for the TCM treatment of angina pectoris after PCI of coronary heart disease.
Humans ; Randomized Controlled Trials as Topic ; Angina Pectoris/drug therapy* ; Coronary Disease/drug therapy* ; Percutaneous Coronary Intervention ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Treatment Outcome ; Female

The process of semen collection plays a key role in the quality of semen specimens. However, the association between semen collection time and semen quality is still unclear. In this study, ejaculates by masturbation from 746 subfertile men or healthy men who underwent semen analysis were examined. The median (interquartile range) semen collection time for all participants was 7.0 (5.0-11.0) min, and the median time taken for semen collection was lower in healthy men than that in subfertile men (6.0 min vs 7.0 min). An increase in the time required to produce semen samples was associated with poorer semen quality. Among those undergoing assisted reproductive technology (ART), the miscarriage rate was positively correlated with the semen collection time. After adjusting for confounders, the highest quartile (Q4) of collection time was negatively associated with semen volume and sperm concentration. A longer time to produce semen samples (Q3 and Q4) was negatively correlated with progressive and total sperm motility. In addition, there was a significant negative linear association between the semen collection time and the sperm morphology. Higher risks of asthenozoospermia (adjusted odds ratio [OR] = 2.06, 95% confidence interval [CI]: 1.31-3.25, P = 0.002) and teratozoospermia (adjusted OR = 1.98, 95% CI: 1.10-3.55, P = 0.02) were observed in Q3 than those in Q1. Our results indicate that a higher risk of abnormal semen parameter values was associated with an increase in time for semen collection, which may be related to male fertility through its association with semen quality.
Male ; Humans ; Semen Analysis ; Semen ; Sperm Motility ; Sperm Count ; Asthenozoospermia ; Spermatozoa