ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective:To investigate long-term auditory changes and characteristics of Alport syndrome（AS） patients with different degrees of renal injury. Methods:Retrospectively analyzing clinical data of patients diagnosed AS from January 2007 to September 2022, including renal pathology, genetic detection and hearing examination. A long-term follow-up focusing on hearing and renal function was conducted. Results:This study included 70 AS patients, of which 33（25 males, 8 females, aged 3.4-27.8 years） were followed up, resulting in a loss rate of 52.9%.The follow-up period ranged from 1.1to 15.8 years, with 16 patients followed-up for over 10 years. During the follow-up, 10 patients presenting with hearing abnormalities at the time of diagnosis of AS had progressive hearing loss, and 3 patients with new hearing abnormalities were followed up, which appeared at 5-6 years of disease course. All of which were sensorineural deafness. While only 3 patients with hearing abnormalities among 13 patients received hearing aid intervention. Of these patients,7 developed end-stage renal disease（ESRD）, predominantly males （6/7）. The rate of long-term hearing loss was significantly different between ESRD group and non-ESRD group（P=0.013）. There was no correlation between the progression of renal disease and long-term hearing level（P>0.05）. kidney biopsies from 28 patients revealed varying degrees of podocyte lesion and uneven thickness of basement membrane. The severity of podocyte lesion was correlated with the rate of long-term hearing loss（P=0.048）, and there was no correlation with the severity of hearing loss（P>0.05）. Among 11 cases, theCOL4A5mutationwas most common （8 out of 11）, but there was no significant correlation between the mutation type and hearing phenotype（P>0.05）. Conclusion:AS patients exhibit progressive hearing loss with significant heterogeneity over the long-term.. THearing loss is more likely to occur 5-6 years into the disease course. Hearing abnormalities are closely related to renal disease status, kidney tissue pathology, and gene mutations, emphasizing the need for vigilant long-term hearing follow-up and early intervention.
Male ; Child ; Female ; Humans ; Nephritis, Hereditary/pathology* ; Retrospective Studies ; Kidney ; Deafness ; Hearing Loss/genetics* ; Kidney Failure, Chronic/pathology* ; Mutation

Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P＜0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P＜0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P＜0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

Osteoporotic proximal humeral fracture (OPHF) is one of the common osteoporotic fractures in the aged, with an incidence only lower than vertebral compression fracture, hip fracture, and distal radius fracture. OPHF, secondary to osteoporosis and characterized by poor bone quality, comminuted fracture pattern, slow healing, and severely impaired shoulder joint function, poses a big challenge to the current clinical diagnosis and treatment. In the field of diagnosis, treatment, and rehabilitation of OPHF, traditional Chinese and Western medicine have accumulated rich experience and evidence from evidence-based medicine and achieved favorable outcomes. However, there is still a lack of guidance from a relevant consensus as to how to integrate the advantages of the two medical systems and achieve the integrated diagnosis and treatment. To promote the diagnosis and treatment of OPHF with integrated traditional Chinese and Western medicine, relevant experts from Orthopedic Expert Committee of Geriatric Branch of Chinese Association of Gerontology and Geriatrics, Youth Osteoporosis Group of Orthopedic Branch of Chinese Medical Association, Osteoporosis Group of Orthopedic Surgeon Branch of Chinese Medical Doctor Association, and Osteoporosis Committee of Shanghai Association of Integrated Traditional Chinese and Western Medicine have been organized to formulate Expert consensus on the diagnosis and treatment of osteoporotic proximal humeral fracture with integrated traditional Chinese and Western medicine ( version 2024) by searching related literatures and based on the evidences from evidence-based medicine. This consensus consists of 13 recommendations about the diagnosis, treatment and rehabilitation of OPHF with integrated traditional Chinese medicine and Western medicine, aimed at standardizing, systematizing, and personalizing the diagnosis and treatment of OPHF with integrated traditional Chinse and Western medicine to improve the patients ′ function.

Objective To evaluate the predictive value of global longitudinal strain(GLS)measured by cardiac magnetic resonance(CMR)feature-tracking technique for left ventricular remodeling(LVR)after percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 403 patients undergoing PCI for acute STEMI were prospectively recruited from multiple centers in China.CMR examinations were performed one week(7±2 days)and 6 months after myocardial infarction to obtain GLS,global radial strain(GRS),global circumferential strain(GCS),ejection fraction(LVEF)and infarct size(IS).The primary endpoint was LVR,defined as an increase of left ventricle end-diastolic volume by≥20%or an increase of left ventricle end-systolic volume by≥15%from the baseline determined by CMR at 6 months.Logistic regression analysis was performed to evaluate the predictive value of CMR parameters for LVR.Results LVR occurred in 101 of the patients at 6 months after myocardial infarction.Compared with those without LVR(n=302),the patients in LVR group exhibited significantly higher GLS and GCS(P<0.001)and lower GRS and LVEF(P<0.001).Logistic regression analysis indicated that both GLS(OR=1.387,95%CI:1.223-1.573;P<0.001)and LVEF(OR=0.951,95%CI:0.914-0.990;P=0.015)were independent predictors of LVR.ROC curve analysis showed that at the optimal cutoff value of-10.6%,GLS had a sensitivity of 74.3%and a specificity of 71.9%for predicting LVR.The AUC of GLS was similar to that of LVEF for predicting LVR(P=0.146),but was significantly greater than those of other parameters such as GCS,GRS and IS(P<0.05);the AUC of LVEF did not differ significantly from those of the other parameters(P>0.05).Conclusion In patients receiving PCI for STEMI,GLS measured by CMR is a significant predictor of LVR occurrence with better performance than GRS,GCS,IS and LVEF.

Objective:To establish biological exposure index (BEI) of occupational exposure to arsenic and its inorganic compounds through occupational epidemiology and the regression analysis of internal and external exposure of workers.Methods:In November 2021, 125 workers with occupational exposure to arsenic and its inorganic compounds and 49 office administrators in a non-ferrous metal smelter in Yunnan Province were selected as the exposure group and control group, respectively. Air samples from the workplace of the study subjects on weekdays were collected and arsenic concentrations were determined. Urine samples were collected in end-of-work weekend and high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) was used to detect the levels of trivalent inorganic arsenic (iAs 3+) , pentavalent inorganic arsenic (iAs 5+) , monomethyl arsenic (MMA) and dimethyl arsenic (DMA) in urine. The correlations between arsenic concentration in the workplace air and arsenic species in urine of workers were analyzed. Arsenic exposure concentration and the level of urinary arsenic (∑iAs+MMA+DMA) of workers was analyzed by linear regression and the BEI of arsenic and its inorganic compounds in the workplace was proposed based on the results of micronucleus test. Results:The median of time-weighted average concentration ( CTWA) of arsenic in the workplace air of the exposure group was 0.0116 mg/m 3, and the over-standard rate was 71.2% (89/125) . The concentrations of iAs 3+, iAs 5+, inorganic arsenic (iAs=∑iAs 3++iAs 5+) 、MMA、DMA and urinary arsenic in the exposure group were higher than those in the control group at the end of shift, and the differences were statistically significant ( P<0.05) . The concentration of arsenic in the workplace air had the strongest correlation with the concentration of urinary arsenic at the end of the shift ( rs=0.909, P<0.001) . The regression equation was lg ( y) =7.662+2.968lg ( x) ( r=0.821, P<0.05) . According to the occupational exposure limit (OEL) of arsenic in China, the concentration of urinary arsenic in the end-of-work weekend was calculated to be 53.2 μg/L. Combined with the results of micronucleus test, the BEI of occupational exposure to arsenic and its inorganic compounds in the workplace was proposed to be 50 μg/L. Conclusion:The urinary arsenic in the end-of-work weekend can be used as a biomarker of occupational exposure to arsenic, and its BEI is recommended to be 50 μg/L.

Objective:To explore the correlation between urinary arsenic and health effects through the determination and analysis of urinary arsenic levels in occupational arsenic exposed workers.Methods:In November 2021, 95 workers exposed to arsenic and its inorganic compounds and 31 administrative personnel from a non-ferrous metal smelter in Yunnan Province were selected as the contact group and control group, respectively. Urine forms of arsenic, blood tumor markers, liver function were detected, and micronucleus test was used to analyze the chromosome damage. The correlation between urine forms of arsenic and health effects were analyzed.Results:Compared with the control group, the concentrations of urinary trivalent inorganic arsenic (iAs 3+) , pentavalent inorganic arsenic (iAs 5+) , inorganic arsenic (iAs=∑iAs 3++iAs 5+) , monomethyl arsenic (MMA) , dimethyl arsenic (DMA) and urinary arsenic (∑iAs+MMA+DMA) at the end of class in contact group were higher ( P<0.05) . There was no statistically significant difference in blood tumor markers and liver function indicators between the two groups ( P>0.05) . Compared with the control group, the peripheral blood micronucleus rate and cell micronucleus rate in the contact group were significantly increased ( P<0.05) . The urinary arsenic, iAs 5+, inorganic arsenic and DMA were positively correlated with peripheral blood micronucleus rate in contact group ( rs=0.48, 0.34, 0.37, 0.23, P<0.05) , and the urinary arsenic, iAs 5+, DMA were positively correlated with peripheral blood micronucleus rate ( rs=0.48, 0.34, 0.26, P<0.05) . Conclusion:There is a significant correlation between different valence states of arsenic in the urine and abnormal health effects of occupational arsenic exposed workers. It is necessary to strengthen the detection of arsenic species in the urine of occupational arsenic exposed workers to better protect their health.

Objective:To establish biological exposure index (BEI) of occupational exposure to arsenic and its inorganic compounds through occupational epidemiology and the regression analysis of internal and external exposure of workers.Methods:In November 2021, 125 workers with occupational exposure to arsenic and its inorganic compounds and 49 office administrators in a non-ferrous metal smelter in Yunnan Province were selected as the exposure group and control group, respectively. Air samples from the workplace of the study subjects on weekdays were collected and arsenic concentrations were determined. Urine samples were collected in end-of-work weekend and high performance liquid chromatography-inductively coupled plasma mass spectrometry (HPLC-ICP-MS) was used to detect the levels of trivalent inorganic arsenic (iAs 3+) , pentavalent inorganic arsenic (iAs 5+) , monomethyl arsenic (MMA) and dimethyl arsenic (DMA) in urine. The correlations between arsenic concentration in the workplace air and arsenic species in urine of workers were analyzed. Arsenic exposure concentration and the level of urinary arsenic (∑iAs+MMA+DMA) of workers was analyzed by linear regression and the BEI of arsenic and its inorganic compounds in the workplace was proposed based on the results of micronucleus test. Results:The median of time-weighted average concentration ( CTWA) of arsenic in the workplace air of the exposure group was 0.0116 mg/m 3, and the over-standard rate was 71.2% (89/125) . The concentrations of iAs 3+, iAs 5+, inorganic arsenic (iAs=∑iAs 3++iAs 5+) 、MMA、DMA and urinary arsenic in the exposure group were higher than those in the control group at the end of shift, and the differences were statistically significant ( P<0.05) . The concentration of arsenic in the workplace air had the strongest correlation with the concentration of urinary arsenic at the end of the shift ( rs=0.909, P<0.001) . The regression equation was lg ( y) =7.662+2.968lg ( x) ( r=0.821, P<0.05) . According to the occupational exposure limit (OEL) of arsenic in China, the concentration of urinary arsenic in the end-of-work weekend was calculated to be 53.2 μg/L. Combined with the results of micronucleus test, the BEI of occupational exposure to arsenic and its inorganic compounds in the workplace was proposed to be 50 μg/L. Conclusion:The urinary arsenic in the end-of-work weekend can be used as a biomarker of occupational exposure to arsenic, and its BEI is recommended to be 50 μg/L.

Objective:To explore the correlation between urinary arsenic and health effects through the determination and analysis of urinary arsenic levels in occupational arsenic exposed workers.Methods:In November 2021, 95 workers exposed to arsenic and its inorganic compounds and 31 administrative personnel from a non-ferrous metal smelter in Yunnan Province were selected as the contact group and control group, respectively. Urine forms of arsenic, blood tumor markers, liver function were detected, and micronucleus test was used to analyze the chromosome damage. The correlation between urine forms of arsenic and health effects were analyzed.Results:Compared with the control group, the concentrations of urinary trivalent inorganic arsenic (iAs 3+) , pentavalent inorganic arsenic (iAs 5+) , inorganic arsenic (iAs=∑iAs 3++iAs 5+) , monomethyl arsenic (MMA) , dimethyl arsenic (DMA) and urinary arsenic (∑iAs+MMA+DMA) at the end of class in contact group were higher ( P<0.05) . There was no statistically significant difference in blood tumor markers and liver function indicators between the two groups ( P>0.05) . Compared with the control group, the peripheral blood micronucleus rate and cell micronucleus rate in the contact group were significantly increased ( P<0.05) . The urinary arsenic, iAs 5+, inorganic arsenic and DMA were positively correlated with peripheral blood micronucleus rate in contact group ( rs=0.48, 0.34, 0.37, 0.23, P<0.05) , and the urinary arsenic, iAs 5+, DMA were positively correlated with peripheral blood micronucleus rate ( rs=0.48, 0.34, 0.26, P<0.05) . Conclusion:There is a significant correlation between different valence states of arsenic in the urine and abnormal health effects of occupational arsenic exposed workers. It is necessary to strengthen the detection of arsenic species in the urine of occupational arsenic exposed workers to better protect their health.

Objective To evaluate the predictive value of global longitudinal strain(GLS)measured by cardiac magnetic resonance(CMR)feature-tracking technique for left ventricular remodeling(LVR)after percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 403 patients undergoing PCI for acute STEMI were prospectively recruited from multiple centers in China.CMR examinations were performed one week(7±2 days)and 6 months after myocardial infarction to obtain GLS,global radial strain(GRS),global circumferential strain(GCS),ejection fraction(LVEF)and infarct size(IS).The primary endpoint was LVR,defined as an increase of left ventricle end-diastolic volume by≥20%or an increase of left ventricle end-systolic volume by≥15%from the baseline determined by CMR at 6 months.Logistic regression analysis was performed to evaluate the predictive value of CMR parameters for LVR.Results LVR occurred in 101 of the patients at 6 months after myocardial infarction.Compared with those without LVR(n=302),the patients in LVR group exhibited significantly higher GLS and GCS(P<0.001)and lower GRS and LVEF(P<0.001).Logistic regression analysis indicated that both GLS(OR=1.387,95%CI:1.223-1.573;P<0.001)and LVEF(OR=0.951,95%CI:0.914-0.990;P=0.015)were independent predictors of LVR.ROC curve analysis showed that at the optimal cutoff value of-10.6%,GLS had a sensitivity of 74.3%and a specificity of 71.9%for predicting LVR.The AUC of GLS was similar to that of LVEF for predicting LVR(P=0.146),but was significantly greater than those of other parameters such as GCS,GRS and IS(P<0.05);the AUC of LVEF did not differ significantly from those of the other parameters(P>0.05).Conclusion In patients receiving PCI for STEMI,GLS measured by CMR is a significant predictor of LVR occurrence with better performance than GRS,GCS,IS and LVEF.