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.

ObjectivesTo investigate the molecular epidemiological characteristics of HIV-1 infection among men who had sex with men (MSM) in Taizhou City, Zhejiang Province, and to provide a scientific reference for acquired immune deficiency syndrome prevention and control efforts. MethodsThe research subjects were all newly reported MSM population in Taizhou City from 2020 to 2023. Blood samples without antiviral therapy were collected. The HIV-1 pol gene was amplified and sequenced, and the sequences were submitted to the Stanford University drug resistance database to identify the mutation sites and drug resistance. MEGA 11.0 software was used to analyze the nucleic acid sequences, construct phylogenetic tree, and calculate genetic distance of gene sequences. The molecular transmission network diagram of HIV-1 was constructed using Cytoscape_v3.10.1, and the influencing factors of network entry were analyzed by logistic regression. ResultsA total of 363 newly reported HIV-infected MSM patients were included, with a median age [M (P₂₅, P₇₅)] of 34 (26,47) years old. The majority had an educational level of junior high school or below (55.65%). A total of eight subtypes were found, mainly CRF07_BC and CRF01_AE. The primary drug resistance rate was 10.47% (38/363). The optimal molecular network gene distance was 0.019, with a network access rate of 42.70% (155/363), and a total of 47 molecular clusters were formed. Multivariate logistic analyses showed that compared with the CRF01_AE subtype, the clustering risk of CRF07_BC subtype was higher (OR=1.916, 95%CI: 1.191‒3.109), cases with drug resistance had a higher risk of cluster formation than those without drug resistance (OR=2.011, 95%CI: 1.006‒4.080), and recent infected patients had a lower risk of entering the largest molecular cluster than long-term infected patients (OR=0.376, 95%CI: 0.137‒0.928). ConclusionThe newly diagnosed infections among the MSM population are active in Taizhou City, Zhejiang Province, with a high level of primary drug resistance. Individuals carrying drug-resistant strains are more likely to cluster. Drug resistance monitoring should be strengthened to prevent further spread of drug-resistant strains in the network.

Objective: To describe the association of different sleep characteristics and cardiometabolic risk among college students, so as to provide reference for health promotion of college students. Methods: By random cluster sampling method, a questionnaire survey and physical examination including blood pressure, waist circumference and blood lipid indicators, which were conducted in April and May of 2019 among a total of 1 179 college students from the first grade in two universities in Hefei City of Anhui Province and Shangrao City of Jiangxi Province. A total of 729 college students with valid questionnaires were included into analysis. The Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI) were used to investigate sleep behavior, and the Morning And Evening Questionnaire-5 (MEQ-5) was used to investigate sleep characteristics. The cardiometabolic risk score was derived using the sum of the standardized sex specific Z scores of waist circumference, mean arterial pressure, HDL cholesterol (multiplied by -1), triglycerides, and insulin resistance index. The rank sum tests were used to compare differences in cardiometabolic risk scores across demographic characteristics. Generalized linear models were used to compare the association of different sleep characteristics with cardiometabolic risk scores among college students. Results: The average cardiovascular metabolic risk score of college students was -0.32(-2.03, 1.58). There were statistically significant differences in cardiovascular metabolic risk scores among college students in variables such as smoking, health status, and physical activity levels ( t/F=-3.41, 12.88, 51.07, P <0.01). The results of the generalized linear model showed that nighttime preference ( B=1.89, 95%CI =1.02-3.49), insomnia symptoms ( B=3.25, 95%CI =1.79-5.90), and short or long sleep duration ( B=1.92, 95%CI =1.21-3.05) were positively correlated with the cardiovascular metabolic risk score of college students ( P <0.05). Conclusions Poor sleep patterns among college students are positively correlated with the risk of cardiovascular metabolism. The sleep behavior of college students should be actively changed to reduce the risk of cardiovascular disease.

BackgroundCombination of antipsychotic drugs and modified electroconvulsive therapy （MECT） is currently a commonly used method for treating schizophrenia， but its efficacy varies among different patient groups. ObjectiveTo explore the therapeutic effects of MECT on schizophrenia patients living in different urban versus rural environments， so as to provide references for the selection of treatment plans based on patients' residence. MethodsA total of 587 patients hospitalized at Luzhou Mental Health Center， Zigong Mental Health Center and Yibin Fourth People's Hospital from May 2018 to August 2022， who met the diagnostic criteria for schizophrenia in the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） ，were included in the study. Patients were divided into two groups： medication-only group （n=106） and MECT combined with medication group （n=481）. In MECT combined with medication group， 24 rural patients residing in urban areas were excluded， leaving the remaining patients divided into urban group （n=103） and rural group （n=354） based on their place of residence. Positive and Negative Syndrome Scale （PANSS） was used to assess the severity of symptoms. Clinical efficacy was evaluated using PANSS score reduction rate， and covariance analysis was used to compare the therapeutic effects of different patients. ResultsThe differences of reduction rate of PANSS total score， positive symptom scale score and negative symptom scale score as well as treatment effectiveness rate between MECT combined with medication group and medication-only group were statistically significant （F=11.149， 12.111， 31.725， χ²=14.010， P<0.01）. Statistically significant differences were also observed in reduction rate of PANSS total score and positive symptom subscale score as well as treatment effectiveness rate between urban and rural patients in MECT combined with medication group （F=3.946， 4.523， χ²=4.033， P<0.05）. ConclusionThe efficacy of MECT combined with medication may be superior to medication alone in the treatment of schizophrenia， and the combined therapy may be more effective in urban patients than that in rural patients， with potentially more pronounced improvements in positive symptoms.

ObjectiveTo analyze the failure of antiretroviral therapy (ART) and drug resistance characteristics among the newly reported HIV-infected patients in Taizhou City from 2020 to 2022. MethodsBlood samples, sociodemographic characteristics and ART information of the newly reported HIV-infected patients who received ART for ≥6 months in Taizhou City from 2020 to 2022 were collected for the detection of recent infections and HIV-1 genotypic drug resistance. Multivariate logistic regression analysis was used to analyze the influencing factors of treatment failure. The gene sequences of cases with failed ART were submitted to the HIV drug resistance database of Stanford University to determine the drug resistance mutation sites and drug resistance characteristics. ResultsAmong the 1 023 newly reported HIV-infected patients receiving ART, the median age （P₂₅，P₇₅） was 47 (33, 58) years, 81.4% were male, 66.4% (679/1 023) were infected through heterosexual transmission, 74.7% had a WHO clinical stage Ⅰ/Ⅱ, 62.2% had a baseline CD4 count of >200 cell·μL^-1, 94.4% (966/1 023) received an immediate ART, and 78.7% were long-term infected. Among the 66 patients with treatment failure (6.5%), the likelihood of treatment failure was lower in those with homosexual transmission (OR=0.39, 95%CI: 0.17‒0.84) and without history of sexually transmitted disease (STD) (OR=0.45, 95%CI: 0.24‒0.92), but higher in those with a baseline CD4 count of ≤200 cell·μL^-1, delayed ART (OR=3.19, 95%CI: 1.24‒7.52), and primary drug resistance (OR=4.69, 95%CI: 1.68‒11.89). Among the 36 HIV-infected patients with virological failure, 27 sequences were successfully amplified, with a successful amplification rate of 75.0% (27/36). The total drug resistance rate was 55.6% (15/27), of which the drug resistance rates of nucleoside reverse transcriptase inhibitors (NRTIs), non-nucleoside reverse transcriptase inhibitors (NNRTIs) and protease inhibitors (PIs) were 37.0% (10/27), 51.9% (14/27) and 3.7% (1/27), respectively. Among the NNRTIs, the degree of resistance to efavirenz and nevirapine was consistent, with a majority (51.9%) of highly drug-resistant. K103N and M184V were the most common mutation sites, but PIs mutations occured less frequently. A total of 8 genotypes of HIV-1 were detected, in which subtype CRF01_AE accounted for 37.0% (10/27), followed by CRF07_BC [14.8% (4/27)], CRF08_BC [14.8% (4/27)] and subtype C [14.8% (4/27)]. ConclusionDuring the period from 2020 to 2022, the newly reported HIV-infected individuals in Taizhou City were predominated by long-term infections. Immediate initiation of ART can reduce the risk of treatment failure in HIV-infected individuals. Virological treatment failures are primarily associated with resistance to NRTIs and NNRTIs. It is recommended to strengthen active detection and promptly initiate ART to minimize the occurrence of ART failure. Simultaneously, there is a need to intensify drug resistance detection targeted for those with treatment failure, so as to provide a scientific guidance for drug replacement.

The pricing and reimbursement of orphan drugs are related to the accessibility of patients,and are of great significance to the prevention and guarantee of rare diseases.European countries have formed special standards and paths for health technology evaluation,and established special payment funds and diversified risk-sharing agreements,which have effectively improved the accessibility of orphan drugs.Based on this,it selected typical European countries to compare the orphan drug pricing and reimbursement methods.Then,it put forward some suggestions"building orphan drug health technology evaluation accelerated program,exploring the health of orphan drug classification security mechanism,and attaining supply incentives and development incentives through orphan drug pricing and adjustment",to optimize the basis for the orphan drug market access mechanism to provide reference.