Objective: To investigate the association of serum alanine aminotransferase (ALT) with left ventricular hypertrophy (LVH) in adolescents, and to provide scientific evidence for the early screening and intervention strategy of cardiac structure damage. Methods: Data were obtained from the third follow up survey (October 2023) of the "Huantai Childhood Cardiovascular Health Cohort Study", including 1 156 healthy adolescents aged 12-17 with complete information. The sample population was stratified into low ( Q 1 group), medium ( Q 2 group), and high ( Q 3 group) ALT levels based on tertiles within the same gender and age groups. Inter group comparisons were conducted using analysis of variance and trend test. A multivariate Logistic regression model was used to analyze the association between ALT levels and LVH, and stratified analyses were performed by gender and age groups. Results: With the increase of ALT quantile level, the detection rate of LVH showed an increasing trend ( Q 1: 3.7%; Q 2: 10.6%; Q 3: 16.7%, Z= 5.89 , P <0.01). After adjusting for potential covariates, compared with the ALT group ( Q 1), the group ( Q 3) increased the risk of developing LVH in adolescents ( OR=2.09, 95%CI =1.21-4.12). Stratified analyses by age and sex showed a significant association only in boys and younger individuals aged 12 to 14 years [ OR (95% CI ) were 2.64(1.04-7.67) and 3.24( 1.35 -9.06), both P <0.05)]. Conclusion Elevated serum ALT levels are associated with an increased risk of LVH in adolescents, and early detection and control of abnormal liver enzyme levels can help reduce early vascular structural damage and prevent adverse cardiovascular events.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

OBJECTIVE: To explore the effect of acupuncture therapy on dysphagia in patients with Parkinson's disease. METHODS: This randomized controlled study lasted 42 days and included 112 patients with Parkinson's disease and dysphagia. Participants were randomly assigned to the experimental and control groups (56 cases each group) using the completely randomized design, all under routine treatment. The experimental group was given acupuncture therapy. The primary outcome was Penetration-Aspiration Scale (PAS). The secondary outcomes were (1) Standardized Swallowing Assessment (SSA), and (2) nutritional status including body mass index (BMI), serum albumin, prealbumin, and hemoglobin. Adverse events were recorded as safety indicators. RESULTS: One participant quitted the study midway. There were no significant differences in baseline assessment (P>0.05). After treatment, both groups showed significant improvement in PAS, SSA and nutritional status except for BMI of the control group. There were significant differences between the two groups in the PAS for both paste and liquid, SSA (25.18±8.25 vs. 20.84±6.92), BMI (19.97±3.34 kg/m²vs. 21.26 ±2.38 kg/m²), serum albumin (35.16 ±5.29 g/L vs. 37.24 ±3.98 g/L), prealbumin (248.33 ±27.72 mg/L vs. 261.39 ±22.10 mg/L), hemoglobin (119.09±12.53 g/L vs. 126.67±13.97 g/L) (P<0.05). There were no severe adverse events during the study. CONCLUSION: The combination of routine treatment and acupuncture therapy can better improve dysphagia and nutritional status in patients with Parkinson's disease, than routine treatment solely. (registration No. CLINICALTRIAL gov NCT06199323).
Humans ; Parkinson Disease/therapy* ; Deglutition Disorders/physiopathology* ; Acupuncture Therapy/adverse effects* ; Male ; Female ; Aged ; Middle Aged ; Treatment Outcome ; Nutritional Status ; Body Mass Index

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 explore the clinical value of plasma von Willebrand factor antigen(VWF:Ag)and VWF activity(VWF:GPIbM)based on ABO blood group in the risk assessment of deep vein thrombosis(DVT).Methods:A total of 163 patients with DVT who sought medical treatment from March 2021 to December 2022 were selected as the case group,and 135 healthy volunteers during the same period were selected as the control group.The differences of ABO blood groups,plasma VWF:Ag and VWF:GPIbM levels between the two groups were compared.Receiver operating characteristic(ROC)curves were used to evaluate the clinical value of VWF testing in predicting DVT events.Logistic regression analysis was applied to identify risk factors for DVT.Results:The levels of plasma VWF:Ag and VWF:GPIbM in the DVT group were significantly higher than those in the control group both overall and across ABO blood type subgroups(P＜0.01).Within the DVT group,the levels of plasma VWF:Ag and VWF:GPIbM in patients with non-O blood type were significantly higher than those with blood type O[VWF:Ag:219.74％±63.64％vs 162.21％±56.03％,P＜0.01;VWF:GPIbM:228.10％(185.15％,249.10％)vs 148.25％(116.48％,225.48％),P＜0.01].The area under the ROC curve(AUC)of VWF:Ag for predicting DVT events was 0.855,with a cut-off value of 142.4％,sensitivity of 82.2％and specificity of 72.6％;the AUC of VWF:GPIbM was 0.861,with a cut-off value of 141.2％,sensitivity of 84.7％,and specificity of 71.1％.Univariate analysis showed that both VWF:Ag and VWF:GPIbM were influencing factors for DVT events(P＜0.05).Multivariate logistic regression analysis indicated that VWF:Ag＞142.4％(OR=13.961,95％CI:7.654-25.464,P＜0.01)and VWF:GPIbM＞141.2％(OR=17.615,95％CI:9.155-33.892,P＜0.01)were independent risk factors for DVT events.Conclusion:Levels of VWF:Ag and VWF:GPIbM are significantly elevated in non-O blood type DVT patients.VWF:Ag＞142.4％and VWF:GPIbM＞141.2％are independent risk factors for DVT events.VWF testing based on ABO blood group aids in the precision prevention and control of DVT.

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 explore the clinical value of plasma von Willebrand factor antigen(VWF:Ag)and VWF activity(VWF:GPIbM)based on ABO blood group in the risk assessment of deep vein thrombosis(DVT).Methods:A total of 163 patients with DVT who sought medical treatment from March 2021 to December 2022 were selected as the case group,and 135 healthy volunteers during the same period were selected as the control group.The differences of ABO blood groups,plasma VWF:Ag and VWF:GPIbM levels between the two groups were compared.Receiver operating characteristic(ROC)curves were used to evaluate the clinical value of VWF testing in predicting DVT events.Logistic regression analysis was applied to identify risk factors for DVT.Results:The levels of plasma VWF:Ag and VWF:GPIbM in the DVT group were significantly higher than those in the control group both overall and across ABO blood type subgroups(P＜0.01).Within the DVT group,the levels of plasma VWF:Ag and VWF:GPIbM in patients with non-O blood type were significantly higher than those with blood type O[VWF:Ag:219.74％±63.64％vs 162.21％±56.03％,P＜0.01;VWF:GPIbM:228.10％(185.15％,249.10％)vs 148.25％(116.48％,225.48％),P＜0.01].The area under the ROC curve(AUC)of VWF:Ag for predicting DVT events was 0.855,with a cut-off value of 142.4％,sensitivity of 82.2％and specificity of 72.6％;the AUC of VWF:GPIbM was 0.861,with a cut-off value of 141.2％,sensitivity of 84.7％,and specificity of 71.1％.Univariate analysis showed that both VWF:Ag and VWF:GPIbM were influencing factors for DVT events(P＜0.05).Multivariate logistic regression analysis indicated that VWF:Ag＞142.4％(OR=13.961,95％CI:7.654-25.464,P＜0.01)and VWF:GPIbM＞141.2％(OR=17.615,95％CI:9.155-33.892,P＜0.01)were independent risk factors for DVT events.Conclusion:Levels of VWF:Ag and VWF:GPIbM are significantly elevated in non-O blood type DVT patients.VWF:Ag＞142.4％and VWF:GPIbM＞141.2％are independent risk factors for DVT events.VWF testing based on ABO blood group aids in the precision prevention and control of DVT.

ObjectiveTo simulate the microstructure and mechanical properties of tendon tissue and promote its regeneration and repair, electrospinning technology was used to prepare L-polylactic acid (PLLA) fiber membranes loaded with different nano zinc oxide contents and with oriented structures. Physical and chemical characterization and biological performance evaluation were carried out to explore their effects on tendon cell proliferation and differentiation. MethodsPreparation of PLLA fiber scaffolds and PLLA/ZnO fiber scaffolds containing different mass fractions of nano ZnO was performed using electrospinning technology. The physicochemical properties of the scaffold were characterized by scanning electron microscopy, mechanical stretching, and EDS spectroscopy. The scaffold was co-cultured with mouse tendon cells to detect its biocompatibility and regulatory effects on cell differentiation behavior. ResultsThe fiber scaffolds were arranged in an oriented manner, and zinc elements were uniformly distributed in the fibers. The tensile strength and Young’s modulus of PLLA/0.1%ZnO fiber scaffolds were significantly higher than PLLA fiber scaffolds. The number of cells on the surface of PLLA/0.1%ZnO fiber scaffold was significantly higher than that of the PLLA group, and the activity was better; mouse tendon cells exhibit directional adhesion and growth along the fiber arrangement direction. ConclusionThe oriented PLLA/0.1%ZnO fiber scaffold had excellent physicochemical properties, which can significantly promote the oriented growth, proliferation and differentiation of tendon cells. It is expected to be used for tendon tissue regeneration and repair in the future.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.