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 construct a risk prediction model for atherosclerosis(AS)in patients with rheumatoid arthritis(RA)based on Lasso-Logistic regression analysis and provide a scientific basis for individualized clinical intervention.Methods The retrospective clinical data were collected from 344 RA patients,including 86 patients with AS(RA+AS group)and 258 patients with without AS(RA group).The clinical characteristics and initial laboratory test results were compared between the two groups.Lasso regression was used to screen the key predictive variables,and Logistic regression was combined to construct the prediction mode.The discrimination of the model was evaluated through the receiver operating characteristic(ROC)curve and the area under the curve(AUC).The Hosmer-Lemeshow test was used to assess the calibration,and decision curve analysis was used to verify the clinical applicability of the model.Results Seven predictive variables were identified including RA disease duration,DAS28 score,C-reactive protein(CRP),triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),fasting blood glucose(FBG)and hypertension.The risk prediction model for AS in RA patients was:Logit(P)=-2.674+0.605×RA disease duration+0.393×DAS28 score+0.310×CRP+1.346×TG-2.289×HDL-C+0.679×FBG+0.711×hypertension.The AUC of the model was 0.965(95%CI:0.943-0.987),and the Hosmer-Lemeshow test showed χ2=0.547,P=1.000,indicating good discrimination and calibration.Clinical decision curve analysis showed that the probability threshold ranged from 7%to 92%,demonstrating high clinical applicability.Conclusion The AS risk prediction model constructed in this study for RA patients can effectively identify high-risk individuals,supporting the development of personalized prevention and treatment strategies.

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 construct a risk prediction model for atherosclerosis(AS)in patients with rheumatoid arthritis(RA)based on Lasso-Logistic regression analysis and provide a scientific basis for individualized clinical intervention.Methods The retrospective clinical data were collected from 344 RA patients,including 86 patients with AS(RA+AS group)and 258 patients with without AS(RA group).The clinical characteristics and initial laboratory test results were compared between the two groups.Lasso regression was used to screen the key predictive variables,and Logistic regression was combined to construct the prediction mode.The discrimination of the model was evaluated through the receiver operating characteristic(ROC)curve and the area under the curve(AUC).The Hosmer-Lemeshow test was used to assess the calibration,and decision curve analysis was used to verify the clinical applicability of the model.Results Seven predictive variables were identified including RA disease duration,DAS28 score,C-reactive protein(CRP),triglycerides(TG),high-density lipoprotein cholesterol(HDL-C),fasting blood glucose(FBG)and hypertension.The risk prediction model for AS in RA patients was:Logit(P)=-2.674+0.605×RA disease duration+0.393×DAS28 score+0.310×CRP+1.346×TG-2.289×HDL-C+0.679×FBG+0.711×hypertension.The AUC of the model was 0.965(95%CI:0.943-0.987),and the Hosmer-Lemeshow test showed χ2=0.547,P=1.000,indicating good discrimination and calibration.Clinical decision curve analysis showed that the probability threshold ranged from 7%to 92%,demonstrating high clinical applicability.Conclusion The AS risk prediction model constructed in this study for RA patients can effectively identify high-risk individuals,supporting the development of personalized prevention and treatment strategies.

Ketamine,an antagonist of the glutamate N-methyl-D-aspartate(NMDA)receptor,is cur-rently one of the most widely abused psychoactive substances.Prolonged abuse can result in damages to various systems in the body,making it crucial to investigate the regulatory mechanism of ketamine addic-tion and screening related biomarkers.In this study,zebrafish embryos/larvae were initially exposed a-cutely to ketamine.Then,a ketamine addiction model was established in 6-month-old zebrafish through conditioned place preference(CPP)experiments.The zebrafish brain transcriptome was analyzed using RNA-seq,while qPCR and Western blotting were employed to detect the expression of key genes.Results revealed significant reductions in the spontaneous tail coiling,embryo hatching rate,and survival rate of zebrafish embryos in the ketamine-treated group compared to the control group.The distance moved also decreased significantly,from 1904.2 mm in the control group to 319.0 mm in the high dose of ketamine group(300 μmol/L).Conditional positional preference experiments demonstrated that the control ze-brafish did not exhibit significant changes in activity in the CPP tank.In contrast,the ketamine-treated group increased their activity time in the light zone of the tank from 385.2 s before training to 706.4 s af-ter training,representing a 26.8％increase(***P＜0.001).This suggests a preference for ketamine stimulation in zebrafish.KEGG analysis indicated enrichment of differentially expressed genes in the neu-roactive ligand-receptor interaction pathway in the ketamine-treated samples.GSEA analysis further re-veals a significant upregulation of the glutamatergic synapse pathway(NES=1.5).In addition,compared with the control group,the mRNA levels of Grin2b and Gria2 in the ketamine group increased by 4.6 and 1.4 times,respectively,while the protein levels increased by 2.0 and 1.4 times,respectively.These findings suggest that ketamine can induce addiction in zebrafish,potentially through upregulation of the glutamatergic synaptic pathway.

Aim To investigate the possible mechanism of action of Qingjie Huagong decoction(QJHGD)on acute lung injury(ALI)associated with severe acute pancreatitis(SAP)using network pharmacology,and to verify it by animal experiments.Methods The TC-MSP,BATMAN-TCM,ETCM,and SwissTargetPredic-tion databases were searched to obtain the action tar-gets of the blood-entering active ingredients of each drug in the QJHGD.The GeneCard database was searched to obtain SAP-ALI disease targets.The drug targets and disease targets were intersected to obtain common targets.Subsequently,the common targets were analyzed by STRING database and Cytoscape 3.7.1 software for protein interaction network analysis.GO and KEGG enrichment analysis was performed with the help of DAVID database.Finally,the key signa-ling pathways were verified by animal experiments.Results A total of 28 active ingredients were screened out for the treatment of SAP-ALI with 42 common tar-gets.PPI network analysis showed that STAT3,IL-6,and TGFB1 might be core targets;GO and KEGG en-richment analysis mainly involved cell proliferation,PI3K/AKT signaling pathways,etc.Animal experi-ments confirmed that QJHGD could improve the pathol-ogy of pancreas and lung tissues in SAP-ALI rat mod-el,down-regulate the expression levels of α-amylase,lipase,IL-1 β,IL-6,and TNF-α in serum,and down-regulate the expression levels of proteins and mRNAs related to PI3K/AKT1 signaling pathway in lung tis-sues.Conclusion QJHGD synergistically treats SAP-ALI through multi-component,multi-target,and multi-pathway,with a mechanism that may be related to the inhibition of PI3K/AKT signaling pathway activation.

Objective:To study the curative effect of rehmannia glutinosa leaves total glycoside capsules and the role of mitochondrial autophagy on nucleos(t)ide drug-induced renal injury.Methods:Adefovir dipivoxil (ADV) was used to construct a hepatitis B virus (HBV) transgenic mouse model for renal injury. Renal function was measured in each group at one and two weeks of modeling. Mitochondrial autophagy indicators were measured at two weeks of modeling in renal tissue. Transmission electron microscopy was used to detect mitochondrial autophagy phenomena in renal tissue. The model was established for two weeks. Mouse with renal injury were treated with rehmannia glutinosa leaves total glycoside capsules or isotonic saline for eight weeks by intragastric administration. Renal function was measured. Renal tissue morphology was observed. Mitochondrial autophagy indicators were detected in renal tissue. The protective effect of different concentrations of verbascoside (the main active ingredient of rehmannia glutinosa capsule) was observed on HK-2 cell damage induced by ADV. HK-2 cells were divided into control, ADV, and ADV plus verbascoside groups. The effects of verbascoside at different times and concentrations were observed on the HK-2 mitochondrial autophagy indicators. Fifty patients with chronic hepatitis B were collected who presented with renal injury after treatment with nucleos(t)ide analogs. The random number method was used to divide 29 cases into a control group that received conventional treatment. The treatment group of 21 cases was treated with rehmannia glutinosa leaves total glycoside capsules on the basis of the control group. Serum creatinine (Scr) and urinary protein were detected at eight weeks.The χ2 test or t-test was used for statistical analysis. Results:Compared with the control group, two weeks of modeling in the ADV group induced renal function injury in HBV mice. The expression of autophagy indicators was higher in the renal tissue of the ADV group than that of the control group. Transmission electron microscopy had revealed mitochondrial autophagy in the renal tissue of the ADV group. Compared with the control group, the renal function of HBV mice treated with rehmannia glutinosa leaves total glycoside capsules improved for two months, and the expressions of autophagy indicators were down-regulated.Verbascoside promoted proliferation in ADV-damaged HK-2 cells, and the expression of autophagy indicators was down-regulated compared with the ADV alone group. In 50 patients with renal function injury, the urinary protein improvement was significantly superior in the treatment group than that in the control group, with eighteen and three cases being effective and ineffective in the treatment group and 12 and 17 cases being effective and ineffective in the control group, with a statistically significant difference ( χ2 ?=?9.975 0, P ?=?0.001 6). Serum creatinine was decreased in the treatment group compared with the control group, with 11 and 10 cases being effective and ineffective in the treatment group and 12 and 17 cases being effective and ineffective in the control group, with no statistically significant difference ( χ2 ?= 0.593 5, P ?=?0.441 1). Conclusion:Rehmannia glutinosa leaves total glycoside capsule can improve the nucleos(t)ide drug-induced renal function injury in chronic hepatitis B, possibly playing a role via inhibiting PINK1/Parkin-mediated mitochondrial autophagy.

ObjectiveTo investigate the effect of mucin 1 (MUC1) on the proliferation and apoptosis of nasopharyngeal carcinoma (NPC) and its regulatory mechanism. MethodsThe 60 NPC and paired para-cancer normal tissues were collected from October 2020 to July 2021 in Quanzhou First Hospital. The expression of MUC1 was measured by real-time quantitative PCR (qPCR) in the patients with PNC. The 5-8F and HNE1 cells were transfected with siRNA control (si-control) or siRNA targeting MUC1 (si-MUC1). Cell proliferation was analyzed by cell counting kit-8 and colony formation assay, and apoptosis was analyzed by flow cytometry analysis in the 5-8F and HNE1 cells. The qPCR and ELISA were executed to analyze the levels of TNF-α and IL-6. Western blot was performed to measure the expression of MUC1, NF-кB and apoptosis-related proteins (Bax and Bcl-2). ResultsThe expression of MUC1 was up-regulated in the NPC tissues, and NPC patients with the high MUC1 expression were inclined to EBV infection, growth and metastasis of NPC. Loss of MUC1 restrained malignant features, including the proliferation and apoptosis, downregulated the expression of p-IкB、p-P65 and Bcl-2 and upregulated the expression of Bax in the NPC cells. ConclusionDownregulation of MUC1 restrained biological characteristics of malignancy, including cell proliferation and apoptosis, by inactivating NF-κB signaling pathway in NPC.

Humans ; Infant ; Mucocutaneous Lymph Node Syndrome/surgery* ; Coronary Artery Bypass/adverse effects* ; Coronary Aneurysm/surgery* ; Coronary Artery Disease/surgery*

Animals ; SARS-CoV-2 ; Antibodies, Neutralizing ; Macaca mulatta ; COVID-19/prevention & control* ; Antibodies, Viral ; Vaccines