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: Rhei Radix et Rhizoma has five types of products, namely, raw rhubarb (RR), wine rhubarb (WR), vinegar rhubarb (VR), cooked rhubarb (CR), and rhubarb charcoal (RC). However, Rhei Radix et Rhizoma is easily contaminated with fungi and mycotoxins if not harvested or processed properly. Here, we intend to analyze how microbiome assemblies and co-occurrence patterns are influenced by sampling locations and processing methods. METHODS: High-throughput sequencing and internal transcribed spacer 2 (ITS2) were carried out to study the diversities (α- and β-diversity), composition (dominant taxa and potential biomarkers), and network complexitity of surface fungi on RR, WR, VR, CR, and RC collected from Gansu and Sichuan provinces, China. RESULTS: The phyla Ascomycota and Basidiomycota; the genera Kazachstania, Malassezia, and Asterotremella; and the species Kazachstania exigua, Asterotremella pseudolonga, and Malassezia restricta were the dominant fungi and exhibited differences in the two provinces and the five processed products. The α-diversity and network complexity were strongly dependent on processing methods. Chao 1, the Shannon index, and network complexity and connectivity were highest in the CR group. The α-diversity and network complexity were influenced by sampling locations. Chao 1 and network complexity and connectivity were highest in the Gansu Province. CONCLUSION The assembly and network of the surface microbiome on Rhei Radix et Rhizoma were shaped by processing methods and sampling locations. This paper offers a comprehensive understanding of microorganisms, which can provide early warning for potential mycotoxins and ensure the safety of drugs and consumers.

Refined operational management is crucial to enhance hospital operational efficiency and achieve sustainable and high-quality development.A large tertiary comprehensive hospital,selected as an observation subject in this study,has har-nessed the value inherent in its extensive operational data,thereby constructing a data-driven operational management framework.Through measures such as developing an operational management system,setting up an operational data hub,and optimizing re-source allocation based on data modeling,this hospital has conducted comprehensive operational analysis at the hospital,depart-ment,and project levels,established a performance management system grounded in data,and enhanced risk prevention and con-trol capabilities,investigating the refined operational management.These efforts have led to incremental improvements in hospital quality,continuous enhancements in operational efficiency,and significant increases in patient and employee satisfaction.

Objective:To establish daily quality assurance workflow based on self-developed phantom to ensure MR-linac performance such as beam accuracy, MR image guidance accuracy, and the clinical treatment workflow to enhance the efficiency of daily quality assurance (QA).Methods:The self-developed phantom was made by 3D printer and used in conjunction with Daily QA-MR detector array. After CT-sim scanning, a treatment plan was designed and transmitted to the accelerator, tests were performed such as image guidance accuracy, beam output and beam quality, the differences in daily QA results between the self-developed phantom and standard phantom recommended by the manufacturer were analyzed by using paired t-test. Results:A total of 24 sets results were collected, the image guide accuracy in the X, Y and Z directions between standard and self-made phantom were (0.1±0.4), (-0.14±0.16), (0.07±0.05) mm and (0±0.02), (-0.02±0.02), (0.02±0.01) mm, respectively, and the differences were statistically significant ( P<0.001, =0.001 and <0.001). Daily QA-MR detector array beam measurement results including output, symmetry, beam quality and field size were -0.11%±0.20%, -0.10%±0.19%, -0.01%±0.08%, (0.4±0.1) mm and (0.2±0.1) mm, respectively. The new process saved 25% (approximately 9 min) of the time compared to the standard process. Conclusions:The new daily QA process for MR-linac is performed based on self-developed phantom and Daily QA-MR detector array. The accuracy and sensitivity meet the requirements and can improve the QA efficiency.

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.

Adenomyosis is a common gynecological disease characterized by the invasion of endometrial glands and stroma into the myometrium of uterus, the pathological mechanism of which remains unclear yet. Disturbed lipid metabolism extensively affects abnormal cell proliferation and invasion in various diseases. However, the lipidome signature of human myometrium, which could be crucial in the development of adenomyosis, remains unknown. In this study, we generated the first lipidome profiling of human myometrium using a high-coverage and quantitative lipidomics approach based on ultra-performance liquid chromatography (UPLC) coupled with triple quadrupole (QqQ)-mass spectrometry (MS). A total of 317 lipid species were successfully quantified in the myometrial tissues from women with (n = 38) or without (n = 65) adenomyosis who underwent hysterectomy at Peking Union Medical College Hospital (Bejing, China). Up to 83 lipid species showed significant alternations in content between the two groups. These lipid aberrations involved multiple metabolic pathways, and emphasized inflammation, cell migration, and immune dysregulation upon adenomyosis. Moreover, receiver operating characteristic (ROC) curve analysis found that the combination of five lipid species could accurately distinguished the myometrial samples from women with and without adenomyosis with an area under the curve (AUC) of 0.906. Desorption electrospray ionization MS imaging (MSI) further underscored the heterogeneous distributions of these lipid markers in the adenomyosis lesion and adjacent myometrial tissue. Collectively, these results extremely improved our understanding on the molecular basis of adenomyosis, and could shed light on developing potential biomarkers and new therapeutic directions for adenomyosis.

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny