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.

AIM To investigate the effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy(CSM).METHODS The CSM rat models were established and randomly assigned to the model group,the Fer-1 group(2 g/kg Ferrostatin-1 via intraperitoneal injection),the low-dose(9.7 g/kg,intragastrically),medium-dose(19.4 g/kg,intragastrically)and high-dose(38.8 g/kg,intragastrically)Jisuishang Formula groups,and the sham operation group,with 6 rats in each group.Following 4 weeks of treatment administration,BBB locomotor scores and oblique plate test result were recorded to assess their neurological function in rats.Histopathological evaluation utilized HE staining for spinal cord tissue pathology,Nissl staining for Nissl body visualization,and Prussian blue staining for iron ion deposition analysis.Protein expressions of Nrf2,SLC7A11,GPX4,HO-1,TFRC and Cox2 in spinal cord tissues was detected by immunofluorescence and Western blot,while mRNA expressions were quantified using RT-qPCR.RESULTS Compared to the sham group,the CSM model group exhibited significantly reduced BBB locomotor scores and inclined plane test performance at 1,2 and 4 weeks post-operation(P＜0.05);obvious tissue cavitation,cellular edema and Prussian blue positive iron deposition in spinal cord tissues;downregulated protein and mRNA expressions of Nrf2,SLC7A11,GPX4,HO-1(P＜0.05);and upregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).Compared to the model group,the Jisuishang Formula and Fer-1 intervention groups showed significantly improved BBB scores and inclined plane test result at 1,2 and 4 weeks post-operation(P＜0.05);reduced tissue cavitation,attenuated cellular edema and decreased Prussian blue positive iron deposition in spinal cord tissues;upregulated protein and mRNA expression of Nrf2,SLC7A11,GPX4 and HO-1 in spinal cord tissues(P＜0.05);and downregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).CONCLUSION Targeting the Nrf2/SLC7A11/GPX4 signaling pathway,Jisuishang Formula potentially suppresses ferroptosis and alleviates iron accumulation in spinal cord neurons,thereby improving neurological recovery in CSM rats.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

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.

AIM To investigate the effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy(CSM).METHODS The CSM rat models were established and randomly assigned to the model group,the Fer-1 group(2 g/kg Ferrostatin-1 via intraperitoneal injection),the low-dose(9.7 g/kg,intragastrically),medium-dose(19.4 g/kg,intragastrically)and high-dose(38.8 g/kg,intragastrically)Jisuishang Formula groups,and the sham operation group,with 6 rats in each group.Following 4 weeks of treatment administration,BBB locomotor scores and oblique plate test result were recorded to assess their neurological function in rats.Histopathological evaluation utilized HE staining for spinal cord tissue pathology,Nissl staining for Nissl body visualization,and Prussian blue staining for iron ion deposition analysis.Protein expressions of Nrf2,SLC7A11,GPX4,HO-1,TFRC and Cox2 in spinal cord tissues was detected by immunofluorescence and Western blot,while mRNA expressions were quantified using RT-qPCR.RESULTS Compared to the sham group,the CSM model group exhibited significantly reduced BBB locomotor scores and inclined plane test performance at 1,2 and 4 weeks post-operation(P＜0.05);obvious tissue cavitation,cellular edema and Prussian blue positive iron deposition in spinal cord tissues;downregulated protein and mRNA expressions of Nrf2,SLC7A11,GPX4,HO-1(P＜0.05);and upregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).Compared to the model group,the Jisuishang Formula and Fer-1 intervention groups showed significantly improved BBB scores and inclined plane test result at 1,2 and 4 weeks post-operation(P＜0.05);reduced tissue cavitation,attenuated cellular edema and decreased Prussian blue positive iron deposition in spinal cord tissues;upregulated protein and mRNA expression of Nrf2,SLC7A11,GPX4 and HO-1 in spinal cord tissues(P＜0.05);and downregulated protein and mRNA expressions of TFRC and Cox2(P＜0.05).CONCLUSION Targeting the Nrf2/SLC7A11/GPX4 signaling pathway,Jisuishang Formula potentially suppresses ferroptosis and alleviates iron accumulation in spinal cord neurons,thereby improving neurological recovery in CSM rats.

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.