1.What will be the next step of LLMs in TCM? A narrative review
Siyi CHEN ; Ruikang ZHONG ; Wenzheng ZHANG ; Zexing LI ; Yisha SU ; Lei GAO ; Kaiwen HU
Science of Traditional Chinese Medicine 2026;4(2):111-118
Large language models (LLMs) offer a modern approach to help inherit traditional Chinese medicine (TCM). This article discussed the progress of LLM applications in TCM and proposed future development directions by reviewing the existing research. We have found that LLMs and related technologies have excellent applications and performance in the management of TCM knowledge and data. They are often applied in information extraction, knowledge graph construction, and data standardization processing. However, data quality and security issues need to be given more attention. In clinical diagnosis and treatment, LLMs can imitate the thinking of TCM by disassembling and reconstructing its diagnostic process and can achieve functions such as prescription recommendation and question and answer (Q&A). However, this approach involves LLMs making inferences and predictions based on existing corpora and thus may not flexibly handle complex environments and tasks. Moreover, the current evaluation criteria for TCM LLMs can be summarized into 3 categories: general evaluation metrics, technical framework evaluation, and evaluation criteria for the characteristics of TCM (such as consistency rates of prescriptions and diagnostic suggestions). However, the lack of a unified and standardized evaluation system hinders the clinical application of TCM LLMs. The future progress of TCM LLMs should focus on the 3 aforementioned critical aspects to achieve technological breakthroughs. In addition, we are promoting the research on vertical TCM LLMs and application terminals. We believe this will bring new ideas to the research on TCM LLMs.
2.Expert consensus on the application of artificial intelligence in lung cancer screening, diagnosis, and treatment (2026 edition)
Wenzhao ZHONG ; Haibo WANG ; Yi HU ; Hao ZHANG ; Jigang DAI ; Junqiang FAN ; Guibin QIAO ; Fan YANG ; Jian HU ; Fengwei TAN ; Xuening YANG ; Qiang PU ; Zihao CHEN ; Hongxia TIAN ; Lunxu LIU ; Hecheng LI ; Xiaolong YAN ; Zongyang YU ; Zhenbin QIU ; Yihua SUN ; Jing HU ; Yuhang SHI ; Zhifei GUO ; Peng ZHANG ; Kezhong CHEN ; Shugeng GAO ; Yilong WU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(06):848-856
With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.
3.The Neural Circuit Characteristics of Repetitive Transcranial Magnetic Stimulation Over The Dorsolateral Prefrontal Cortex for The Treatment of Migraine
Chen-Xia JIN ; Bo-Lin TAN ; Yang YE ; Ji-Qing HE ; Ling-Yan WANG ; Zhong-Ming GAO ; Yu-Jun WANG ; Hui-Li LIU ; Yong-Xing YAN ; Xian-Wei CHE
Progress in Biochemistry and Biophysics 2026;53(7):1953-1968
ObjectiveMigraine is a leading neurological disorder and the fourth most common cause of years lived with disability worldwide, affecting nearly 116 million individuals. Although pharmacological treatments are available, their efficacy is often limited by side effects and variable response rates. Repetitive transcranial magnetic stimulation (rTMS) over the dorsolateral prefrontal cortex (DLPFC) offers a safe, non-invasive alternative for migraine management. However, the neurophysiological mechanisms, particularly how rTMS modulates local cortical excitability and distributed pain-related circuits, remain poorly understood. Elucidating these mechanisms is essential for optimizing treatment protocols and improving clinical outcomes. MethodsThis study employed concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) to investigate neuroplastic and neurocircuitry mechanisms of DLPFC-rTMS in migraine. Study 1 compared 30 migraineurs and 28 healthy controls to identify abnormalities in TMS-evoked potentials (TEPs) and significant current density (SCD) within sensory-discriminative regions including the primary somatosensory cortex (S1) and posterior insula (pINS), cognitive-affective regions including the anterior insula (aINS) and midcingulate cortex (MCC), and a descending modulatory region, the periaqueductal gray (PAG). Study 2 used a single-blind, crossover, sham-controlled design in 34 healthy participants. Each participant received both active (10 Hz, 80% RMT, 1 500 pulses) and sham DLPFC-rTMS in counterbalanced order. TMS-EEG and cold pain tolerance were assessed before and after each session. ResultsIn Study 1, migraineurs showed a significantly less negative N120 amplitude compared to healthy controls (P=0.027, Cohen’s d=0.60), indicating local intracortical disinhibition. No group differences were observed for N40, P60, or P180 components. At the source level, migraineurs exhibited significantly higher SCD in the S1, pINS, aINS, and MCC (allQ<0.05), but not in the ventroposterior thalamus (vpTHAL), mediodorsal thalamus (mdTHAL), or PAG. In Study 2, active rTMS significantly reduced SCD from pre- to post-stimulation in the S1, aINS, and MCC (all Q<0.05). Sham stimulation also reduced SCD in the S1 (Q<0.05) but not in the aINS or MCC. Although no significant group-level analgesic effect was observed between active and sham conditions (P=0.107), correlation analyses revealed that greater SCD reductions in the S1 and MCC were significantly associated with higher post-rTMS pain tolerance (R=-0.487 and -0.495, both Q<0.01) and larger improvements in pain tolerance(R=-0.487 and -0.451, both Q<0.05). No such correlations were found following sham stimulation, suggesting that the behavioural relevance of neural changes is specific to active rTMS. ConclusionThis study provides novel evidence that migraineurs exhibit both local neuroplastic abnormalities (reduced N120 amplitude) and hyperactivity in key pain-processing regions (S1, pINS, aINS, MCC). A single session of DLPFC-rTMS reduced hyperactivity in the aINS, MCC, and S1. Notably, greater reductions in the S1 and MCC were associated with improved pain tolerance. These findings identify distinct cortical circuitries, particularly within the cognitive-affective pain network, that may serve as potential biomarkers for optimizing rTMS treatment in migraine and other chronic pain conditions. Future studies should validate these results in patient populations experiencing spontaneous migraine attacks and explore multi-session or accelerated rTMS protocols.
4.The efficacy and safety of nebulized inhalation of recombinant human interferon α1b in the treatment of pediatric respiratory syncytial viral associated lower respiratory tract infections: a multicenter, randomized, double-blind, placebo-controlled phase Ⅲ clinical study
Xiaohui LIU ; Baoping XU ; Yunxiao SHANG ; Han ZHANG ; Zhenkun ZHANG ; Guangyu LIN ; Ju YIN ; Aihua CUI ; Guocheng ZHANG ; Zhaoling SHI ; Liwei GAO ; Chunming JIANG ; Junmei BIAN ; Yongjian HUANG ; Rongfang ZHANG ; Xiaomei LIU ; Xiaoqing YANG ; Yu TANG ; Lili ZHONG ; Hongmei QIAO ; Chuangli HAO ; Yuqing WANG ; Qubei LI ; Ling CAO ; Yungang YANG ; Ling LU ; Rongjun LIN ; Xingzhen SUN ; Wei ZHOU ; Qiang CHEN ; Jikui DENG ; Yuejie ZHENG ; Lin ZHAO ; Tao AI ; Xiaohong LIU ; Xiaoxia LU ; Ning JIANG ; Ming LI
Chinese Journal of Applied Clinical Pediatrics 2025;40(3):180-186
Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.
5.Comparison of clinical manifestations,laboratory characteristics,and treatment outcomes of 258 patients with acute and chronic brucellosis
Xu ZHAO ; Ke-mei NIU ; Xia GAO ; Chun-xu SONG ; Yu FAN ; Qing-qing XU ; Zhong-rong LU ; Kun LI ; Feng GAO ; Mei-chun HAO ; Bing-zhi LIU ; Hai JIANG
Chinese Journal of Zoonoses 2025;41(6):660-667
To compare and analyze the clinical manifestations,laboratory characteristics,imaging findings,and treatment outcomes of patients with acute and chronic brucellosis,a retrospective analysis was conducted on 258 patients with brucellosis(202 in the acute group and 56 in the chronic group)hospitalized in Xinkang Hospital in Dalad Banner,Ordos City,Inner Mongolia Autonomous Region,from November 2023 to November 2024.General data,epidemiological characteristics,clinical presentations,laboratory test results,imaging findings,treatment outcomes,and prognosis were collected.The incidences of fever(51.5%vs 7.1%),fatigue(30.2%vs 12.5%),joint pain(42.9%vs 16.1%),and muscle pain(9.9%vs.1.8%)were significantly higher in the acute phase group(all P<0.05).The incidence of osteoarthritis complications was higher in the chronic brucellosis group(51.8%vs 8.9%,χ2=75.697,P<0.01).Univariate ANOVA analysisshowed that the Serum Agglutination Tests(SAT),alanine aminotransferase(ALT),aspartate aminotransferase(AST),total bilirubin(TBIL),creatinine(CRE),C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),and bone destructionexhibited statistically significant differences between the acute and chronic phases of brucellosis(all P<0.05).Multivariate logistic regression analysis indicated that abnormal ALT(OR=14.18,95%CI:1.11-181.72;P=0.041)and bone destruction(OR=0.16,95%CI:0.04-0.63;P=0.009)were associated with chronic brucellosis.After treatment,all patients experienced have symptom relief in varying degrees,with 157 patients(60.9%)cured and 101 patients(39.1%)symptomatic improved(P<0.01).In conclusion,the incidences of fever,fatigue,and joint pain in patients during the acute phase is significantly higher than that those in patients during the chronic phase,while the incidence of osteoarthritis complications is higher in chronic phase patients.The incidences of abnormal SAT,ALT,AST,TBIL,CRE,CRP,and ESR,and bone destruction varies at different stages of brucellosis.Of those,abnormal ALT and bone destruction show a stronger association with,which can assist the clinical staging of brucellosis.
6.Experimental study on the decontamination ability of different cleaning waters for surgical instruments
Bing-qing LIAO ; Xiao-mei REN ; Jing-rong WEI ; Yan GAO ; Zhong-jin YAN ; Xiao-feng LI ; Bin LI
Journal of Regional Anatomy and Operative Surgery 2025;34(7):610-613
Objective To analyze differences of purified water,softened water,and concentrated softened water on the decontamination effects for surgical instruments,so as to provide a reliable reference for the selection of cleaning water for surgical instruments.Methods The physical and chemical indexes and components of concentrated softened water,softened water,and purified water were detected,and their cleaning effects for instrument were compared.The decontamination cleaning experiment was conducted in three hospitals with different types of cleaning water using mini cleaning machines,and the differences in the decontamination time were analyzed.The cleaning and decontamination experiments on contaminated instruments was performed using a spray cleaning and disinfection device,and the cleaning effects of instruments with different types of cleaning water were analyzed.Results Calcium content and hardness of the three types of cleaning water were all at a low level,which can avoid scale adhesion for cleaning surgical instruments.There were statistically significant differences in the pH value,conductivity,and contents of calcium,sodium and chloride among the three cleaning waters(P<0.05).The purified water was weakly acidic,and its conductivity,hardness,and contents of calcium,sodium and chloride were all at low levels.The softened water and concentrated softened water were weakly alkaline,with high levels of conductivity and sodium content and low level of chloride.There were statistically significant differences in the decontamination time of the purified water,softened water and concentrated softened water among hospitals(P<0.05).Under the same contamination condition of surgical instruments,there was a statistically significant difference in the qualified rate of instruments cleaning in the upper and lower cleaning baskets with different cleaning waters(P<0.05).Conclusion Concentrated softened water and softened water have high sodium content,and their decontamination and cleaning abilities are significantly stronger than those of the purified water.Purified water has poorer effects in instruments cleaning for its deionized property.Using concentrated softened water or softened water in the surgical instrument cleaning process can achieve effects of reducing consumption and increasing efficiency,which is conducive to improving cleaning efficiency and quality.
7.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
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.
8.Distribution characteristics of smoking behavior among adult twins in China
Shunkai LIU ; Wenjing GAO ; Weihua CAO ; Jun LYU ; Canqing YU ; Shengfeng WANG ; Tao HUANG ; Dianjianyi SUN ; Chunxiao LIAO ; Yuanjie PANG ; Ruqin GAO ; Min YU ; Jinyi ZHOU ; Xianping WU ; Zhong DONG ; Fan WU ; Dezheng WANG ; Zhihua XU ; Yu LIU ; Jianrui WANG ; Jie YIN ; Shengli YIN ; Liming LI
Chinese Journal of Preventive Medicine 2025;59(7):1090-1096
This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.
9.Effects of Jisuishang Formula on neurological function and ferroptosis in a rat model of cervical spondylotic myelopathy
Han-li YANG ; Ming SHI ; Chun-zhi LIU ; Shao-hu LIN ; Ming-gao HU ; Xian-zhong BU ; Yuan-ming ZHONG ; Wei XU
Chinese Traditional Patent Medicine 2025;47(10):3233-3241
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.
10.Expert Consensus on the Ethical Requirements for Generative AI-Assisted Academic Writing
You-Quan BU ; Yong-Fu CAO ; Zeng-Yi CHANG ; Hong-Yu CHEN ; Xiao-Wei CHEN ; Yuan-Yuan CHEN ; Zhu-Cheng CHEN ; Rui DENG ; Jie DING ; Zhong-Kai FAN ; Guo-Quan GAO ; Xu GAO ; Lan HU ; Xiao-Qing HU ; Hong-Ti JIA ; Ying KONG ; En-Min LI ; Ling LI ; Yu-Hua LI ; Jun-Rong LIU ; Zhi-Qiang LIU ; Ya-Ping LUO ; Xue-Mei LV ; Yan-Xi PEI ; Xiao-Zhong PENG ; Qi-Qun TANG ; You WAN ; Yong WANG ; Ming-Xu WANG ; Xian WANG ; Guang-Kuan XIE ; Jun XIE ; Xiao-Hua YAN ; Mei YIN ; Zhong-Shan YU ; Chun-Yan ZHOU ; Rui-Fang ZHU
Chinese Journal of Biochemistry and Molecular Biology 2025;41(6):826-832
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.

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