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 summarize the laboratory findings of a case of hemolytic disease of the fetus and newborn (HDFN) caused by Rh system anti-c antibodies and to review the literature, so as to explore the characteristics of anti-c HDFN. Methods: The ABO blood type, Rh blood type, direct antiglobulin test (DAT) results, and the presence of unexpected antibodies and their titers were determined by serological methods. The cases of anti-c HDFN in our laboratory in China and abroad were statistically analyzed, and the incidence of severe HDFN caused by anti-c, anti-D and anti-E was compared. Results: The blood type of the child was B (Rh CcDee) with a positive DAT. Anti-c antibody was detected in both serum and eluate, with a serum antibody titer of 4. The mother’s blood type was AB (Rh CCDee) with a negative DAT, and anti-c antibody was detected in the serum with a titer of 128. Among 20 cases of anti-c HDFN, 17 were DAT positive, and 9 (45%, 9/20) underwent blood transfusion or exchange transfusion. The incidence of severe HDFN was 47.60% (10/21) for anti-c, 47.60% (10/21) for anti-D and 31.30% (5/16) for anti-E. Conclusion: Maternal pregnancy and/or blood transfusion are the main reasons for the production of Rh alloantibodies such as anti-c. The prevention and management of anti-c should be similar to that of anti-D. Rh antigen-matched (five antigens of Rh blood group) transfusion is necessary for women of childbearing age to avoid antibody production, and Rh typing and antibody screening during prenatal examination is recommended to ensure early detection, intervention and treatment.

Background Animal farming may affect the structure and diversity of gut microbiota of farm workers, but it needs more studies to provide solid evidence. Objective To analyze the diversity characteristics of gut microbiota in dairy farm workers, dairy cows, and the control population (non-animal contact occupational group), and to assess the impact of dairy farming on the gut microbiota of workers. Methods The 16S rRNA full-length amplicon sequencing technology was used to sequence 60 fecal samples from dairy farm workers, 89 from dairy cows, and 50 from the general population. The gut microbiota structure characteristics, including operational taxonomic units (OTUs), alpha diversity, beta diversity, and the composition of species at the phylum, family, and genus levels were analyzed. The differences in gut microbiota among the three groups of samples were compared to explore the impact of occupational exposure on the gut microbiota structure of dairy farm workers. Results A total of 50478 OTUs were identified in the gut microbiota of farm workers, dairy cows, and the general population, with 23613, 42723, and 16592 OTUs, respectively. The number of shared OTUs between the dairy cows and the general population was 12674 (27.17%), between the general population and the farm workers was 10099 (33.54%), and between the dairy cows and the farm workers was 17690 (36.36%). Compared with the general population, the farm workers and dairy cows showed more shared gut microbiota (P<0.01). The abundance of Firmicutes in the gut of the farm workers was higher than that of the general population (P<0.01), while Actinobacteriota and Proteobacteria were the opposite (P<0.01). The alpha diversity of gut microbiota in the farm workers was different from that of the general population. The ACE index of the farm workers was slightly lower than that of the general population and much lower than that of dairy cows (P<0.05), while their Shannon index was higher than that of the general population but lower than that of dairy cows (P<0.01). The linear discriminant analysis effect size (LefSe) showed that the abundances of Lachnospiraceae and Ruminococcaceae in the gut microbiota of the farm workers were significantly higher than those of the general population, while Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae were lower than those of the general population. Conclusion The dairy farm workers shares a certain proportion of common bacterial communities with dairy cows. Dairy farming operations can affect the structure and diversity of the gut microbiota of workers by increasing the abundances of Lachnospiraceae and Ruminococcaceae, while decreasing the abundances of Streptococcaceae, Lactobacillaceae, Bifidobacteriaceae, Enterobacteriaceae, and Erysipelatoclostridiaceae. The study results provide reference data for further exploring the cross-host transmission of pathogens related to occupational exposure in dairy farming.

With the increasing attention paid by the state to traditional medicine and the need for the inheritance and innovative development of Tibetan medicine in the new era， the research and development of new Tibetan medicines has attracted the attention of the industry. This article analyzes the characteristics of prescriptions， dosage forms， preparation methods， and processing of the 34 Tibetan medicine formulas included in the Catalogue of Ancient Famous Classical Formulas（Second Batch）， discusses the problems and challenges in the research and development of ancient famous classical formulas of Tibetan medicine， and puts forward opinions and suggestions in order to promote the research and development of new Tibetan medicine. The main issues that may be encountered in the research and development of 34 Tibetan medicine formulas are as follows：①Some medicinal material resources are scarce， and planting/breeding technologies are not yet mature. Among the 34 formulas， there are not only ingredients derived from endangered protected animals， but also national second-class protected plants and rare high-altitude wild species. ②The quality control level of Tibetan medicinal materials urgently needs to be strengthened and improved. After review， among the 102 medicinal materials in the 34 Tibetan medicine formulas， there are 2 varieties that currently have no national or local medicinal material standards/decoction piece processing specifications. Excluding those without quality standards， the proportion of varieties without any quantitative testing items is 49%. ③There are a large number of mineral medicines in Tibetan medicine formulas， making quality control difficult. The proportion of formulas containing mineral medicines among the 34 formulas is 35%， and most of them have not yet established a targeted quality standard system. ④Some Tibetan medicinal materials in the 34 formulas have unclear origins， with issues such as different substances with the same name and the same substance with different names. ⑤The 34 formulas contain medicinal materials labeled as toxic or slightly toxic in the current quality standards. It is recommended to accelerate the verification of key information of Tibetan medicine， and on this basis， to intensify research on planting and breeding， quality control in response to the above issues. It is also suggested to encourage the rational use of new technologies and processes that are suitable for the characteristics of preparations to develop new drugs from ancient famous classical formulas of Tibetan medicine， and promote the inheritance and innovative development of Tibetan medicine.

Objective To evaluate the safety and efficacy of total arterial off-pump coronary artery bypass grafting (OPCABG) using a left internal thoracic artery (LITA) combined with bilateral radial arteries (RAs). Methods We retrospectively analyzed the clinical data of patients with severe multi-vessel coronary artery disease who underwent total arterial OPCABG with a LITA and bilateral RAs at Sichuan Provincial People’s Hospital from November 2020 to April 2023. Results A total of 24 patients were included, comprising 23 males and 1 female, with a mean age of (53.63±4.33) years. The New York Heart Association (NYHA) functional class was Ⅱ to Ⅲ. The mean number of distal anastomoses was 3.17±0.38. A Y-graft was constructed in 12 patients and sequential grafting was performed in 4 patients. Concomitant procedures included coronary endarterectomy in 1 patient, intra-aortic balloon pump (IABP) implantation in 10 patients, and thymoma resection in 1 patient. The mean operative time was (308.13±30.39) min, mechanical ventilation time was (15.42±7.42) h, ICU stay was (46.08±27.32) h, and postoperative hospital stay was (11.71±1.90) d. There were no in-hospital deaths. Postoperative complications included one patient of acute renal failure and one patient of cerebral infarction. Pre-discharge color Doppler echocardiography revealed that the left ventricular end-diastolic diameter was significantly smaller than before surgery (P<0.05), while the left ventricular ejection fraction and fractional shortening were significantly higher (P<0.05). Coronary computed tomography angiography (CTA) showed that all arterial grafts were patent. During a mean follow-up of (14.58±8.75) months, no patients experienced angina recurrence or mortality. Repeat coronary CTA or angiography in 16 patients one year postoperatively confirmed that all arterial grafts remained patent. Conclusion Total arterial OPCABG using a LITA and bilateral RAs is a safe and effective treatment for patients with severe multi-vessel coronary artery disease. For high-risk patients, intraoperative IABP support is recommended.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.