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 tripartite game model involving the government,the public,and the pharmaceutical industry alliance during public health emergencies,revealing the dynamic mechanisms of health-related information quality regulation and exploring effective strategies to optimize the informa-tion dissemination environment through reward-punishment mechanisms.Methods:Based on evolutionary game theory,a tripartite evolutionary game model was established,integrating strategy spaces,payoff functions,and parameter definitions for each stakeholder.The pharmaceutical industry alliance's strate-gies included publishing high-or low-quality information(α),the public's strategies encompassed ration-al analysis or passive response(β),and the government's strategies involved regulatory enforcement or inaction(γ).Key parameters,such as economic benefits(Iyy),regulatory costs(Czf),penalties(Fyy),and incentives(Pyy),were quantified to reflect real-world scenarios.Replicator dynamic equa-tions and Jacobian matrices were derived to analyze the stability of equilibrium points,while MATLAB 2016a simulations were conducted to validate the model under varying initial conditions(e.g.,Iyy=100,150,200;Pyy=0,20,35;Fyy=0,10,20).Sensitivity analyses examined the impact of critical pa-rameters on system evolution,by 50 iterative simulations to observe convergence patterns.Results:The study revealed three key findings:(1)Public rational discernment(β)significantly influenced the phar-maceutical industry's strategy.Simulations demonstrated that increasing Iqz(benefits of information acqui-sition)reduced Cqz(cognitive costs),elevating β from 0.4 to 0.8 and driving α(high-quality information probability)to stabilize at 1.(2)Government regulatory intensity(γ)correlated positively with the so-cial hazards of low-quality information.When Fyy+Pyy＞Iyy,speculative behaviors decreased,achieving equilibrium at α=1.(3)Dual stable equilibria emerged:a high-quality equilibrium(α=1,β=1,γ=0)with lower regulatory costs and a low-quality equilibrium(α=0,β=0,γ=1)associated with higher social risks.Phase diagrams illustrated path dependency,where initial α＜0.5 led to the low-quality equilibrium unless dynamic penalties(Fyy＞20)and incentives(Pyy＞30)were enforced.Conclusion:A"carrot-stick"collaborative governance framework is proposed,emphasizing categorized regulation,AI-enabled auditing,and dynamic penalty systems.Future research should integrate emotional utility func-tions to address irrational decision-making impacts,thereby enhancing the adaptability of health informa-tion regulatory systems.

Objective:To observe the effects of ear acupressure combined with acupoint application on serum inflammatory factors,pain and psychological status of children with limb fractures.Methods:By using random number table method,60 children with limb fracture who were admitted to Qiantang Campus of Zhejiang Provincial Traditional Chinese Medicine Hospital from February 2022 to August 2024 were divided into control group(received conventional treatment combined with acupoint application)and experimental group(combined with ear acupressure based on the control group),with 30 cases in each group.Pain and swelling degree of the affected limb,anxiety and depression[Screening Checklist for Childhood Anxiety Disorders(SCARED),Depression self-rating scale for children(DSRSC)],inflammatory factors[High sensitivity C-reactive protein(hs-CRP),tumor necrosis factor-α(TNF-α),interleukin-6(IL-6),interleukin-1(IL-1)]and family satisfaction rate were compared between the two groups.Results:The scores of visual analogue scale(VAS),SCARED and DSRSC in the experimental group were lower than those in the control group at 1 week and 4 weeks after treatment(P＜0.05).Swelling degree of the affected limb in the experimental group was better than that in the control group at 4 weeks after treatment(P＜0.05).hs-CRP,IL-1,IL-6 and TNF-α in the experimental group were lower than those in the control group at 4 weeks after treatment(P＜0.05).The family satisfaction rate in the experimental group was higher than that in the control group(P＜0.05).Conclusion:Ear acupressure combined with acupoint application therapy for children with limb fractures can significantly alleviate postoperative pain,promote swelling reduction,effectively reduce inflammation,and improve anxiety and depression,with high treatment satisfaction.

Objective To develop the value of machine learning(ML)models based on contrast-transthoracic echocardiography(cTTE)and transesophageal echocardiography(TEE)combined with clinical and laboratory indicators for predicting patent foramen ovale-associated stroke(PFO-AS).Methods Totally 313 patients with PFO diagnosed with cTTE and TEE were retrospectively enrolled.Among them,65 cases were found complicated with ischemic stroke and confirmed as PFO-AS(PFO-AS group),and the rest 248 cases without ischemic stroke were classified as non-PFO-AS group.The patients were divided into training set(n=219,including 48 cases of PFO-AS and 171 cases of non-PFO-AS)and test set(n=94,including 17 cases of PFO-AS and 77 cases of non-PFO-AS)at the ratio of 7∶3.Univariable and multivariable logistic regression(LR)were used to analyze clinical and laboratory indicators as well as cTTE and TEE parameters in training set to screen independent predictive factors of PFO-AS.ML models,including LR,K-nearest neighbor(KNN),support vector machine(SVM),random forest(RF),decision tree(DT),back propagation neural network(BPNN)and gradient boosting machine(GBM)were constructed,and the predictive efficacy of the models for predicting PFO-AS was evaluated,then the optimal model was selected.Results Patient's age＞49-69 years,with smoking history,plasma albumin≥43.8 g/L,significant right-to-left shunt at rest shown on cTTE and complicated atrial septal aneurysm shown on TEE were all independent predictors of PFO-AS,which were used to construct ML models.The area under the curve(AUC)of LR,KNN,SVM,RF,DT,BPNN and GBM models in training set was 0.779-0.853,while in test set was 0.730-0.877.RF model had relatively high and comparable sensitivity,specificity and AUC in both training and test sets,also higher precision and smaller Brier score in test set,hence was regarded as the optimal ML model.Conclusion RF model based on cTTE and TEE combined with clinical and laboratory indicators could be used to effectively predict PFO-AS.

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:A retrospective analysis was conducted on the clinical characteristics and polysomnography (PSG) features of patients with obstructive sleep apnea (OSA) of different ages.Methods:From January 2015 to March 2024, the patients who underwent overnight PSG monitoring at the Sleep Respiratory Disease Diagnosis and Treatment Center, Department of Otolaryngology, Head and Neck Surgery, Sixth Medical Center of the PLA General Hospital were sequentially enrolled.A total of 4 396 patients[aged from 18 to 97(46.04±12.60)years] with OSA who met the criteria were finally enrolled and divided into the youth group (18-44 years old, n=2 099), middle-aged group (45-59 years old, n=1 641), and elderly group (≥60 years old, n=656).The differences in general condition, Epworth sleepiness Scale (ESS) score, rapid eye movement sleep (REM) sleep time in total sleep time, micro-awakening index, apnea hypopnea index (AHI), minimum oxygen saturation at night (LSpO 2), oxygen hypoxia index (ODI) and so on were compared.Multivariate Logistic regression was used to analyze the relationship between age stratification and different severity of OSA (mild 5≤AHI≤15, moderate 1530, Times per hour). Results:The neck circumference [(39.11±3.71) cm], body mass index [BMI, (26.63±3.70) kg/m2], total sleep time [(386.13±66.09) min], the percentage of deep sleep in total sleep time [(3.05±4.80)%], the percentage of REM sleep time in total sleep time [(16.73±6.83)%], apnea-hypopnea index [AHI, (31.17±19.20) events/h], oxygen desaturation index [ODI, (46.57±33.54) events/h], microarousal index [(14.82±12.27) events/h], and Epworth Sleepiness Scale (ESS) score (8.29±5.92) in the elderly group were all lower than those in the young group [neck circumference (41.36±3.37) cm, BMI (28.55±4.21) kg/m2, total sleep time [(424.67±62.21) min], the percentage of deep sleep in total sleep time (5.89±6.79)%, the percentage of REM sleep time in total sleep time (17.95±6.67)%, AHI (39.55±27.89) events/h, ODI (61.88±34.60) events/h, microarousal index (22.77±19.31) events/h, ESS score (9.63±5.82)] and the middle-aged group [neck circumference (40.75±3.59) cm, BMI (27.89±3.55)kg/m2, total sleep time [(410.98±63.02)min], the percentage of deep sleep in total sleep time (3.59±5.11)%, the percentage of REM sleep time in total sleep time (17.47±6.63)%, AHI (36.01±23.63) events/h, ODI (57.20±34.75) events/h, microarousal index (19.23±15.59) events/h, ESS score (9.98±6.11)], with F values of 102.62, 62.15, 95.87, 95.94, 8.71, 29.60, 49.72, 59.11, and 19.03, respectively, and all P values were <0.001. The proportion of females [29.57% (94/656)], the proportion of patients with hypertension [37.20% (244/656)], and the nocturnal LSpO 2 [(79.09±9.88)%] in the elderly group were all higher than those in the young group [proportion of females [6.48% (136/2 099)], proportion of patients with hypertension 18.10% (380/2 099), nocturnal LSpO 2(75.19±12.90)%] and the middle-aged group [proportion of females [15.84%(260/1 641)], proportion of patients with hypertension 33.09% (543/1 641), nocturnal LSpO 2(76.15±12.44)%], with F values of 242.62, 150.90, and 25.05, respectively, and all P values were <0.001.There were no significant differences in neck circumference, percentage of REM sleep time in total sleep time, AHI and LSpO 2 at night between young and middle-aged groups ( P>0.05). After adjusting for gender, neck circumference, BMI, and hypertension confounders, the risk of severe OSA in the older group was increased by 27.4% compared with the younger group ( OR=1.274, 95% CI=1.036-1.566, P<0.05). Further stratified analysis showed that neck circumference and BMI were independent factors for severe OSA in the young and middle-aged groups ( P<0.01), while, only neck circumference was independently associated with severe OSA in the elderly group (OR=1.119, 95% CI=1.039-1.207, P<0.01). Conclusion:The severity of OSA in young and middle-aged patients is more serious than that in elderly patients. Obesity is an important factor affecting the degree of OSA in young and middle-aged patients. After controlling for confounding factors such as obesity, the risk of severe OSA in elderly patients is higher than that in young patients, which is considered to be related to factors such as pharyngeal collapse and relaxation of pharyngeal muscles.

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*