Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective: Previous studies have discovered a correlation between cigarette smoking and cortical thickness and surface area, but the causal relationship remains unclear. The objective of this investigation is to scrutinize the causal association between them. Methods: To derive summary statistics from a genome-wide association study (GWAS) on cortical thickness, surface area, and four smoking behaviors: 1) age of initiation of regular smoking (AgeSmk); 2) smoking initiation (SmkInit); 3) smoking cessation (SmkCes); 4) cigarettes per day (CigDay). Linkage disequilibrium score regression (LDSC) was employed to examine genetic association analysis. Furthermore, for traits with significant genetic associations, Mendelian randomization (MR) analyses were conducted. Results: The LDSC analysis revealed nominal genetic correlations between AgeSmk and right precentral surface area, left caudal anterior cingulate surface area, left cuneus surface area, left inferior parietal surface area, and right caudal anterior cingulate thickness, as well as between CigDay and left caudal middle frontal surface area, between SmkCes and left entorhinal thickness, and between SmkInit and left rostral anterior cingulate surface area, right rostral anterior cingulate thickness, and right superior frontal thickness (rg=-0.36–0.29, p<0.05). MR analysis showed a unidirectional causal association between left caudal middle frontal surface area and CigDay (βIVW=0.056, pBonferroni=2×10-4). Conclusion Left caudal middle frontal surface area has the potential to serve as a significant predictor of smoking behavior.

Objective:To investigate the impact of non-alcoholic fatty liver disease (NAFLD) on the outcome of patients with acute ischemic stroke (AIS).Methods:Patients with AIS visited the Affiliated Jiangning Hospital of Nanjing Medical University between June 2017 and December 2023 were included retrospectively. At 3 months after onset, the modified Rankin Scale was used to evaluate the outcome, with scores of 0-2 defined as good outcome and >2 defined as poor outcome. Multivariate logistic regression analysis was used to determine the impact of NAFLD on the outcome of patients with AIS. Results:A total of 143 patients with AIS were enrolled, including 95 males (66.43%), aged 67.79±11.15 years. Ninety six patients (67.13%) had good outcome, and 47 (32.87%) had poor outcome. Multivariate logistic regression analysis showed that after adjusting for confounding factors, NAFLD was independently associated with the poor outcome in patients with AIS (odds ratio 2.500, 95% confidence interval 1.015-6.161; P=0.046). Conclusion:NAFLD is an independent risk factor for poor outcome in patients with AIS.

The rehabilitation compliance of stroke patients is generally low.Evaluating the rehabilitation motivation of patients is helpful to promote the rehabilitation management of patients,enhance the rehabilitation enthusiasm and compliance of patients,and improve the rehabilitation outcome.This paper reviews the existing stroke patients rehabilitation motivation assessment tools,and expounds the main contents,application status,characteristics and limitations of stroke patients rehabilitation motivation assessment tools,in order to provide references for the appropriate selection of clinical assessment tools,the rehabilitation management of stroke patients and the development of domestic localized stroke rehabilitation motivation assessment tools.

China is currently experiencing rapid population aging,leading to a significant expansion of the elderly demographic.This aging process is accompanied by cognitive,motor,and sensory function decline and diseases,resulting in an increasing number of elderly individuals with disabilities.To address this challenge,extended reality technology offers a personalized,motivating,and human-computer interactive training environment that can effectively tackle the obstacles hindering active health and disability prevention in the elderly,such as inadequate infrastructure and motivation.This review summarized the current research status and effectiveness of extended reality technology in preventing disability among the elderly.Additionally,the review discusses the limitations and future prospects of extended reality technology in the context of elderly disability prevention,aiming to provide guidance for preventing disability in the elderly and promoting healthy aging.

Objective To construct a morphological brain network in patients with cerebral small vessel disease(CSVD)and predict it application for cognitive function.Methods A total of 64 eld-erly CSVD patients admitted in our hospital from January 2020 to February 2024 were retrospec-tively recruited.Cognitive function was assessed with Mini-Mental State Examination(MMSE)and Montreal Cognitive Assessment(MoCA).Their clinical data,and results of cognitive function and multi-modal MRI scanning were collected and analyzed.3D T1-weighted imaging based on Kullback-Leibler divergence similarity was used to construct individual morphological brain net-work,and the connectome-based predictive model was employed to construct a cognitive predic-tion model.Results The network,which is significantly and positively correlated with the MMSE and MoCA scores,was mainly located in the default mode network,and could effectively predict individual MMSE and MoCA scores(r=0.795,P=4.436×10-15;r=0.794,P=4.974×10-15,P＜0.01).The connections,which were significantly negatively correlated with MMSE or MoCA scores,were mainly located between the salience/ventral attention network and other networks,and could also effectively predict individual MMSE and MoCA scores(r=0.766,P=1.679× 10-13;r=0.850,P=6.915×10-19,P＜0.01).Combined positive correlation and negative correla-tion networks,the model showed further improved predictive performance(r=0.849,P=7.603 × 10-19;r=0.888,P=1.445 × 10-22,P＜0.01).Conclusion Individual morphological brain network can effectively predict cognitive function in elderly CSVD patients,and can be used as a convenient tool for early warning of cognitive impairment related to CSVD.

A 31-year-old man sought medical evaluation for a 2-year history of edema and proteinuria, with prior pathology suggesting atypical membranous nephropathy (MN). Despite treatment with a combination of steroids, calcineurin inhibitors, and four courses of rituximab (1 g, intravenous injection), the patient′s nephrotic syndrome showed no relief (24 h urine protein peaked at 31.18 g/d), indicating refractory nephrotic syndrome. Later in the disease course, a sudden surge of creatinine level (322.5 μmol/L) prompted a renal biopsy, which revealed concurrent acute interstitial nephritis. Further treatment involving steroids, cyclophosphamide, and a fifth rituximab infusion (1 g, intravenous injection) resulted in improvement in renal function (serum creatinine: 322.5?147 μmol/L), but the MN failed to achieve partial relief. Subsequent treatment with the novel humanized CD20 monoclonal antibody obinutuzumab (1 g, intravenous injection) was initiated. In the latest follow-up, anti-phospholipase-A2-receptor antibody (PLA2R) antibody were negative, B cells were eliminated, serum albumin was 36 g/L, urine protein-to-creatinine ratio was 4 810 mg/g, and serum creatinine was 162 μmol/L. This case underscores the potential efficacy of obinutuzumab in refractory MN. For advanced MN cases, prompt identification of the cause of acute kidney injury is crucial, emphasizing the need for targeted interventions to potentially stall renal function decline.