Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Background: and Purpose Ruptured intracranial aneurysms (RIA) are associated with a mortality rate of up to 40% in the Chinese population, highlighting the critical need for targeted treatment interventions for at-risk individuals. Although the impact of aldehyde dehydrogenase 2 (ALDH2) gene mutations on susceptibility to intracranial aneurysms (IA) is well documented, the potential connection between ALDH2 rs671 single-nucleotide polymorphism (SNP) and RIA remains unexplored. Given the increased prevalence of ALDH2 gene mutations among Chinese Han individuals, it is clinically relevant to investigate the link between ALDH2 rs671 SNP and IA rupture. Methods: A prospective study was conducted on 546 patients diagnosed with IA to investigate the association between ALDH2 rs671 SNP and the risk of IA rupture. Results: The ALDH2 rs671 SNP (ALDH2*2) was significantly more prevalent in patients with unruptured IA (UIA) than in those with RIA (32.56% vs. 18.58%, P=0.004). Multivariate logistic regression analysis revealed that people with the ALDH2 mutation (ALDH2*1/*2 and ALDH2*2/*2 gene type) had a significantly reduced odds ratio (OR=0.49; 95% confidence level [CI] 0.27–0.88; P=0.018) for RIAs. Age-specific subgroup analysis indicated that the ALDH2 mutation provided a stronger protective effect in individuals aged 60 years and above with IA compared to those under 60 years old (OR=0.38 vs. OR=0.52, both P<0.05). Conclusion The incidence of RIA was significantly higher in individuals with a normal ALDH2 gene (ALDH2*1/*1) than in those with an ALDH2 rs671 SNP (ALDH2*1/*2 or ALDH2*2/*2). ALDH2 rs671 SNP may serve as a protective factor against RIA in the Chinese Han population.

Attempts have been made to modulate motor sequence learning (MSL) through repetitive transcranial magnetic stimulation, targeting different sites within the sensorimotor network. However, the target with the optimum modulatory effect on neural plasticity associated with MSL remains unclarified. This study was therefore designed to compare the role of the left primary motor cortex and the left supplementary motor area proper (SMAp) in modulating MSL across different complexity levels and for both hands, as well as the associated neuroplasticity by applying intermittent theta burst stimulation together with the electroencephalogram and concurrent transcranial magnetic stimulation. Our data demonstrated the role of SMAp stimulation in modulating neural communication to support MSL, which is achieved by facilitating regional activation and orchestrating neural coupling across distributed brain regions, particularly in interhemispheric connections. These findings may have important clinical implications, particularly for motor rehabilitation in populations such as post-stroke patients.
Humans ; Transcranial Magnetic Stimulation ; Motor Cortex/physiology* ; Male ; Electroencephalography ; Neuronal Plasticity/physiology* ; Female ; Adult ; Evoked Potentials, Motor/physiology* ; Young Adult ; Learning/physiology*

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.

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 features,treatment and prognosis of traumatic subdural effusion(TSE)in infants.Methods Data of 51 cases of traumatic subdural effusion in infants admitted to the single center of Dalian Women and Children Medical Center(Group)from February 2013 to February 2020 were retrospectively analyzed,and their clinical manifestations,imaging features,treatment methods and prognosis were summarized and analyzed.Results Fifty-one cases(26 males and 25 females),ranging in age from 1 month to 3 years old of traumatic subdural effusion in infants were reviewed in our hospital,all cases were confirmed by Computed Tomography(CT)examination.31 cases were treated conservatively,29 cases were cured,and 2 cases were treated surgically due to poor conservative treatment.Surgical treatment was performed in 22 cases(including 2 cases who received surgical treatment due to poor conservative treatment).One patient underwent puncture and continuous drainage at the lateral Angle of the anterior fontanelle and was cured.Twenty-one cases underwent cranial drilling,subdural space catheterization for external drainage,and 17 cases(80.95％,17/21)were cured at one time.There were 4 cases(19.05％,4/21)of recurrence after external drainage with catheterization.Two cases were cured by external drainage with Ommaya capsule insertion and intermittent aspiration and fluid drainage.It was changed to subdural peritoneal shunt surgery,and 2 cases were cured after the operation.There was no surgical infection or death in all the children in the group.The median follow-up time ranged from 3 months to 60 months,and the conditions were all stable.Conclusion Traumatic subdural effusion is a common complication after craniocerebral injury in infants and young children.Due to its lack of self-expression,the hidden condition is often ignored.Moreover,the brain tissue of infants and young children is in the growth and development stage,which will affect the development of brain tissue after its onset.

Objective:To explore the association between A Body Shape Index (ABSI) and sarcopenia in Chinese older adults.Methods:Totally 1 728 participants in waves 1 and 3 of the China Health and Retirement Longitudinal Survey (CHARLS) were enrolled in this cohort-based cross-sectional analysis. ABSI was calculated by using anthropometric measurements from CHARLS. According to the Asian Working Group for Sarcopenia (AWGS) 2019 consensus update on sarcopenia, low muscle strength and low muscle mass were used as the diagnostic criteria for sarcopenia. Logistic regression and restricted cubic spline (RCS) were used to assess the relationship between ABSI and sarcopenia, and subgroup and interaction analyses were conducted to evaluate the influence of other factors on this association.Results:High ABSI showed a significant association with the risk of sarcopenia among older adults in China, and RCS analysis demonstrated a positive linear correlation between ABSI and sarcopenia. Additionally, the relationship of ABSI with sarcopenia was significantly modified by educational level and depressive status.Conclusion:ABSI, a novel anthropometric measure, serves as an effective threshold for assessing sarcopenia risk in the Chinese older population, providing a basis for developing clinical interventions and public health strategies for the prevention and early identification of sarcopenia.

Objective:To explore the association between A Body Shape Index (ABSI) and sarcopenia in Chinese older adults.Methods:Totally 1 728 participants in waves 1 and 3 of the China Health and Retirement Longitudinal Survey (CHARLS) were enrolled in this cohort-based cross-sectional analysis. ABSI was calculated by using anthropometric measurements from CHARLS. According to the Asian Working Group for Sarcopenia (AWGS) 2019 consensus update on sarcopenia, low muscle strength and low muscle mass were used as the diagnostic criteria for sarcopenia. Logistic regression and restricted cubic spline (RCS) were used to assess the relationship between ABSI and sarcopenia, and subgroup and interaction analyses were conducted to evaluate the influence of other factors on this association.Results:High ABSI showed a significant association with the risk of sarcopenia among older adults in China, and RCS analysis demonstrated a positive linear correlation between ABSI and sarcopenia. Additionally, the relationship of ABSI with sarcopenia was significantly modified by educational level and depressive status.Conclusion:ABSI, a novel anthropometric measure, serves as an effective threshold for assessing sarcopenia risk in the Chinese older population, providing a basis for developing clinical interventions and public health strategies for the prevention and early identification of sarcopenia.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.