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 develop a differentiated performance evaluation system for surgical and non-surgical clinical departments based on Diagnosis-Related Groups(DRG),promoting refined hospital management.Methods Data from 13 clini-cal departments in a tertiary hospital in Tibet Autonomous Region(2022-2024)were analyzed and evaluated using the entropy weight method combined with the TOPSIS method and quadrant analysis.Results A dual-track evaluation system was estab-lished,comprising 10 indicators for surgical departments and 9 for non-surgical departments.Weight analysis revealed that the proportion of Grade Ⅳ surgeries(weight 0.20)and total DRG weight(0.13)were core competitiveness indicators for surgical departments,while the proportion of patients with RW≥2.0(0.29)and Case Mix Index(CMI)(0.15)were key drivers for non-surgical departments.TOPSIS evaluation showed that orthopedics and general surgery ranked highest among surgical depart-ments,whereas pediatric ward Ⅱ and internal medicine ward Ⅰ led among non-surgical departments.Evaluation results were con-sistent over the three-year period and aligned with quadrant analysis.Conclusion The classification-based evaluation system for clinical departments facilitates refined hospital management.It is recommended for application in performance appraisal and other management initiatives to further enhance high-quality hospital development.

In recent years,our understanding of neutrophil extracellular traps(NETs)has been deepened with advancements in technology.Extensive research has demonstrated that NETs are intricately linked to autoimmunity and contribute to the path-ogenesis of autoimmune diseases through multiple mechanisms,such as serving as a source of self-antigens,activating the com-plement system,or modulating other immune cells.Notably,the interaction between NETs and immune cells plays a critical role in disease progression.This article primarily reviews the relationship of NETs with dendritic cells,macrophages,B cells,and CD4 T cells in autoimmune diseases,providing insights into potential therapeutic strategies by NETs level modulation and NETs-immune cell interactions intervenion.

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.

The year 2025 marks the 110th anniversary of the Chinese Medical Association. As one of the founding institutions of modern plastic surgery in China, Department of Plastic Surgery, the First Affiliated Hospital of Air Force Medical University (Xijing Hospital), has played a pioneering role in advancing the specialty since its establishment in 1955. The department has achieved remarkable innovations in key areas such as microsurgery, skin and soft tissue expansion, facial allotransplantation, and interdisciplinary integration. Through sustained efforts in platform development, talent cultivation, and scientific research, it has evolved into a comprehensive academic center. This article provides a comprehensive overview of the department’s 70-year developmental journey, highlights its major contributions, and outlines its future directions in promoting high-quality development in plastic surgery in China.

Objective To develop a differentiated performance evaluation system for surgical and non-surgical clinical departments based on Diagnosis-Related Groups(DRG),promoting refined hospital management.Methods Data from 13 clini-cal departments in a tertiary hospital in Tibet Autonomous Region(2022-2024)were analyzed and evaluated using the entropy weight method combined with the TOPSIS method and quadrant analysis.Results A dual-track evaluation system was estab-lished,comprising 10 indicators for surgical departments and 9 for non-surgical departments.Weight analysis revealed that the proportion of Grade Ⅳ surgeries(weight 0.20)and total DRG weight(0.13)were core competitiveness indicators for surgical departments,while the proportion of patients with RW≥2.0(0.29)and Case Mix Index(CMI)(0.15)were key drivers for non-surgical departments.TOPSIS evaluation showed that orthopedics and general surgery ranked highest among surgical depart-ments,whereas pediatric ward Ⅱ and internal medicine ward Ⅰ led among non-surgical departments.Evaluation results were con-sistent over the three-year period and aligned with quadrant analysis.Conclusion The classification-based evaluation system for clinical departments facilitates refined hospital management.It is recommended for application in performance appraisal and other management initiatives to further enhance high-quality hospital development.

Objective:To determine the pathogens causing viral diarrhea in children under 5 years of age and the epidemiological patterns in Chengdu from 2021 to 2024.Methods:Fecal samples were collected from hospitalized children under 5 years of age with diarrhea in a sentinel surveillance hospital for viral diarrhea in Chengdu from 2021 to 2024. Norovirus（NoV），sapovirus（SaV），astrovirus（AstV），and enteric adenovirus（EAdV）were detected by real-time PCR or real-time RT-PCR. Group A rotavirus（RVA）was detected by enzyme-linked immunosorbent assay. The results were analyzed statistically by using SPSS 20.0 software.Results:RVA，NoV，SaV，AstV，and EAdV were detected in 329 fecal samples from 719 hospitalized children with diarrhea under 5 years of age. The total detection rate was 48.8%（329/719）. The detection rate of RVA，NoV，SaV，AstV，and EAdV was 17.0%（122/719），20.9%（150/719），4.0%（29/719），2.8%（20/719），8.6%（62/719），separately. The detection rate of mixed infection with multiple pathogens was 7.1%（51/719），among which RVA combined with NoV infection was the most common（2.2%，16/719）. Except for EAdV（ χ2=14.368， P=0.002），there was no significant difference in the detection rates of RVA，NoV，SaV，and AstV in different years. Except for SaV and EAdV，the detection rates of RVA（ χ2=11.106， P<0.001），NoV（ χ2=65.164， P<0.001）and AstV（ χ2=19.612， P<0.001）were statistically significant in different quarters. There was no statistically significant difference in the detection rates of the five pathogens between males and females. Except for NoV，there were statistically significant differences in the detection rates of RVA（ χ2=32.209， P<0.001），SaV（ χ2=13.983， P=0.002），AstV（ χ2=9.56， P=0.015）and EAdV，（ χ2=8.992， P=0.029）in children of different months of age. Conclusion:RVA and NoV are the main pathogens causing viral diarrhea in children under 5 years of age in Chengdu. The peak infection period of viral diarrhea tends to occur in winter and spring and occurs most frequently in 12-24 months old and 24-59 months old children.