BACKGROUND: Spicy food consumption has been reported to be inversely associated with mortality from multiple diseases. However, the effect of spicy food intake on the incidence of vascular diseases in the Chinese population remains unclear. This study was conducted to explore this association. METHODS: This study was performed using the large-scale China Kadoorie Biobank (CKB) prospective cohort of 486,335 participants. The primary outcomes were vascular disease, ischemic heart disease (IHD), major coronary events (MCEs), cerebrovascular disease, stroke, and non-stroke cerebrovascular disease. A Cox proportional hazards regression model was used to assess the association between spicy food consumption and incident vascular diseases. Subgroup analysis was also performed to evaluate the heterogeneity of the association between spicy food consumption and the risk of vascular disease stratified by several basic characteristics. In addition, the joint effects of spicy food consumption and the healthy lifestyle score on the risk of vascular disease were also evaluated, and sensitivity analyses were performed to assess the reliability of the association results. RESULTS: During a median follow-up time of 12.1 years, a total of 136,125 patients with vascular disease, 46,689 patients with IHD, 10,097 patients with MCEs, 80,114 patients with cerebrovascular disease, 56,726 patients with stroke, and 40,098 patients with non-stroke cerebrovascular disease were identified. Participants who consumed spicy food 1-2 days/week (hazard ratio [HR] = 0.95, 95% confidence interval [95% CI] = [0.93, 0.97], P <0.001), 3-5 days/week (HR = 0.96, 95% CI = [0.94, 0.99], P = 0.003), and 6-7 days/week (HR = 0.97, 95% CI = [0.95, 0.99], P = 0.002) had a significantly lower risk of vascular disease than those who consumed spicy food less than once a week ( Ptrend <0.001), especially in those who were younger and living in rural areas. Notably, the disease-based subgroup analysis indicated that the inverse associations remained in IHD ( Ptrend = 0.011) and MCEs ( Ptrend = 0.002) risk. Intriguingly, there was an interaction effect between spicy food consumption and the healthy lifestyle score on the risk of IHD ( Pinteraction = 0.037). CONCLUSIONS Our findings support an inverse association between spicy food consumption and vascular disease in the Chinese population, which may provide additional dietary guidance for the prevention of vascular diseases.
Humans ; Male ; Female ; Prospective Studies ; Middle Aged ; Aged ; Vascular Diseases/etiology* ; Risk Factors ; China/epidemiology* ; Adult ; Proportional Hazards Models ; Cerebrovascular Disorders/epidemiology* ; East Asian People

Diffuse large B-cell lymphoma(DLBCL)is the most common subtype of non-Hodgkin lymphoma,which demonstrates significant heterogeneity.Some DLBCL exhibit poor responses to chemotherapy,highlighting the urgent need for precise prognostic evaluation methods.As a critical biological parameter,tumor burden closely associated with disease progression and unfavorable prognosis,but representing tumor burden of DLBCL only with anatomical parameters was not enough to comprehensively reflect its biology features.Multiple parameters derived from 18F-FDG PET/CT could characterize metabolic features of tumors,hence enabling accurate quantification of tumor burden and providing a theoretical basis for individualized treatment of DLBCL.The research progresses of 18 F-FDG PET/CT for assessing tumor burden of DLBCL were reviewed in this article.

Extremely unbalanced data refers to datasets with independent or dependent variables showing severe imbalances in proportions, which might lead to deviation of classical test statistics from theoretical distribution and difficulties in controlling type Ⅰ error. The increased availability of genome-wide resources from large population cohorts has highlighted the growing demand for efficient and accurate statistical methods for the process of extremely unbalanced data to improve the development of genetic statistical methods. This paper introduces two widely used correction methods in current genome-wide association study for extremely unbalanced data, i.e. Firth correction and saddle point approximation, describes their effectiveness in controlling type Ⅰ errors confirmed by simulation experiments, finally, and summarizes the commonly used software for extremely unbalanced genomic data to provide theoretical reference and suggestion for its application for the statistical analysis on extremely unbalanced data in future.

ObjectiveTo explore the characteristics of the tongue coating microbiota in patients of coronary heart disease （CHD） with qi deficiency and blood stasis syndrome. MethodsA total of 27 CHD patients with qi deficiency and blood stasis syndrome， 29 patients with non-qi deficiency and blood stasis syndrome， and 20 healthy individuals were included in this study. The tongue coating microbiota of the participants was analyzed using 16S rDNA high-throughput sequencing technology， followed by Alpha and Beta diversity analyses and comparisons of microbial abundance. ResultsA total of 479 operational taxonomic units （OTUs） were detected， among which 245 OTUs were shared across all three groups. There were 33 OTUs unique to the qi deficiency and blood stasis syndrome group， 21 OTUs unique to the non-qi deficiency and blood stasis syndrome group， and 121 OTUs unique to the healthy group. The observed species count （Sob）， total species richness （Chao1）， abundance-based coverage estimator （ACE）， and Shannon diversity index were significantly lower in the qi deficiency and blood stasis syndrome and non-qi deficiency and blood stasis syndrome groups compared to the healthy group （P＜0.05）. Principal coordinate analysis （PCoA） of the tongue coating microbiota showed significant differences in distance matrices among the three groups （P＜0.05）. Compared with the healthy group， the qi deficiency and blood stasis syndrome group exhibited an increased abundance of Actinobacteria， Patescibacteria， Spirochaetes， Verrucomicrobia， Rothia， TM7X， Gemella， and Corynebacterium， while Fusobacteria， Cyanobacteria， Leptotrichia， and Lactobacillus decreased （P＜0.05）. In the non-qi deficiency and blood stasis syndrome group， Actinobacteria， Verrucomicrobia， Rothia， and Corynebacterium increased， whereas Cyanobacteria and Lactobacillus reduced （P＜0.05）. When comparing with the non-qi deficiency and blood stasis syndrome group， the qi deficiency and blood stasis syndrome group had a significantly higher abundance of Patescibacteria， Peptostreptococcus， Solobacterium， Filifactor， Moraxella， Porphyromonas endodontalis， and Capnocytophaga， while Cyanobacteria reduced （P＜0.05）. Conclusuion Patients with CHD of qi deficiency and blood stasis syndrome exhibit a decrease in beneficial bacteria and an increase in pathogenic bacteria. Patescibacteria， Peptostreptococcus， Solobacterium， Filifactor， Moraxella， Porphyromonas endodontalis， and Capnocytophaga were identified as the key differential microbiota distinguishing qi deficiency and blood stasis syndrome from non-qi deficiency and blood stasis syndrome patients.

The concept of amplification feedback pathways represents an intersection between electronics and control theory,involving both amplification and feedback processes.It reveals the dynamic evolution mechanisms of systems under the combined influence of these two processes.In Traditional Chinese Medicine(TCM),Chest Bi syndrome is considered a"ben xu biao shi"condition,with its primary pathology located in the heart and closely related to other organs such as the liver,spleen and kidneys.This article focuses on the interrelationship between organ dysfunction and the imbalance of the Five Elements Theory.By applying amplification feedback theory and models,the study constructs and analyzes single-stage amplification feedback pathways involving the heart,liver and kidneys,as well as double-stage amplification feedback pathways involving the heart,liver,kidneys and spleen,in the context of multifactorial interactions such as heart and kidney Yang deficiency,Qi stagnation in the heart and chest,and spleen-stomach dysfunction.Particular emphasis is placed on analyzing the phenomena of deep feedback and self-excited oscillation,and specific formulas and clinical evidence are used to validate the analysis results,clarifying the role of relevant organ function changes in the pathogenesis of Chest Bi syndrome.The article aims to provide new insights into the complex pathogenesis of refractory diseases from a control theory perspective,offering new directions for modernizing TCM research with digital technology and theoretical support for future simulation-based digital systems guided by TCM theory.

Extremely unbalanced data refers to datasets with independent or dependent variables showing severe imbalances in proportions, which might lead to deviation of classical test statistics from theoretical distribution and difficulties in controlling type Ⅰ error. The increased availability of genome-wide resources from large population cohorts has highlighted the growing demand for efficient and accurate statistical methods for the process of extremely unbalanced data to improve the development of genetic statistical methods. This paper introduces two widely used correction methods in current genome-wide association study for extremely unbalanced data, i.e. Firth correction and saddle point approximation, describes their effectiveness in controlling type Ⅰ errors confirmed by simulation experiments, finally, and summarizes the commonly used software for extremely unbalanced genomic data to provide theoretical reference and suggestion for its application for the statistical analysis on extremely unbalanced data in future.

The concept of amplification feedback pathways represents an intersection between electronics and control theory,involving both amplification and feedback processes.It reveals the dynamic evolution mechanisms of systems under the combined influence of these two processes.In Traditional Chinese Medicine(TCM),Chest Bi syndrome is considered a"ben xu biao shi"condition,with its primary pathology located in the heart and closely related to other organs such as the liver,spleen and kidneys.This article focuses on the interrelationship between organ dysfunction and the imbalance of the Five Elements Theory.By applying amplification feedback theory and models,the study constructs and analyzes single-stage amplification feedback pathways involving the heart,liver and kidneys,as well as double-stage amplification feedback pathways involving the heart,liver,kidneys and spleen,in the context of multifactorial interactions such as heart and kidney Yang deficiency,Qi stagnation in the heart and chest,and spleen-stomach dysfunction.Particular emphasis is placed on analyzing the phenomena of deep feedback and self-excited oscillation,and specific formulas and clinical evidence are used to validate the analysis results,clarifying the role of relevant organ function changes in the pathogenesis of Chest Bi syndrome.The article aims to provide new insights into the complex pathogenesis of refractory diseases from a control theory perspective,offering new directions for modernizing TCM research with digital technology and theoretical support for future simulation-based digital systems guided by TCM theory.

Diffuse large B-cell lymphoma(DLBCL)is the most common subtype of non-Hodgkin lymphoma,which demonstrates significant heterogeneity.Some DLBCL exhibit poor responses to chemotherapy,highlighting the urgent need for precise prognostic evaluation methods.As a critical biological parameter,tumor burden closely associated with disease progression and unfavorable prognosis,but representing tumor burden of DLBCL only with anatomical parameters was not enough to comprehensively reflect its biology features.Multiple parameters derived from 18F-FDG PET/CT could characterize metabolic features of tumors,hence enabling accurate quantification of tumor burden and providing a theoretical basis for individualized treatment of DLBCL.The research progresses of 18 F-FDG PET/CT for assessing tumor burden of DLBCL were reviewed in this article.

Objective:To develop a grading system for necrosis of pedicled flaps in reconstruction of foot and ankle, and to verify its effectiveness and repeatability.Methods:A retrospective observational study was conducted. A total of 40 necroses of foot and ankle pedicled flaps were selected by 2 senior surgeons based on the flap surgery performed by the same surgical group in Department of Orthopaedic Surgery, the 920 Hospital of Joint Logistic Support Force of PLA from January 2010 to January 2022. A grading system for pedicled flap necrosis was proposed by a working group and the 40 necrotic flaps were graded. The coincidence rate was calculated to evaluate the effectiveness of the grading system through correlation studies between grading and clinical treatment. One photo of a typical postoperative necrotic flap was collected from each of the 40 flaps. Then 5 extramural surgeons were asked to grade the necroses shown on the photos according to the proposed grading system. Moreover, weighted Kappa analysis was performed on the results of proposed grading system and also on the standard grading currently in use, to evaluate the repeatability of the proposed grading system. Evaluated data were expressed by Mean±SD, and the coincidence rate was expressed by percentage. The reproducibility was studied by weighted Kappa analysis.Results:Of the 40 necrotic flaps, 7 flaps were classified in Grade I, 16 in Grade Ⅱ, 12 in Grade Ⅲ and 5 in Grade IV. In comparison with the actual treatment methods, the overall coincidence rate of the grading system was 92.5%. It indicated that the proposed grading system could effectively guide the selection of a treatment procedure. The average weighted Kappa coefficient of surgeons was at 0.628 with a 95% confidence interval (95%CI) between 0.460-0.796, which was strongly consistent with the standard of the grading system currently in use.Conclusion:The grading system for necrosis of pedicled flap in reconstruction of foot and ankle proposed in this study is simple and clear. It is able to effectively guide the treatment of flap necrosis. The preliminary validation shows that the classification system has good repeatability.

Extremely unbalanced data here refers to datasets where the values of independent or dependent variables exhibit severe unbalance in proportions, such as extremely unbalanced case-control ratio, very low incidence rate of disease, heavily censored time-to-event data, and low-frequency or rare variants. In such scenarios, the statistic derived from hypothesis test using the classical statistical method, e.g., logistic regression model and Cox proportional hazard regression model, might deviate from theoretical asymptotic distribution, resulting in inflation or deflation of type I error. With the increased availability and exploration of resources from large-scale population cohorts in genome-wide association study (GWAS), there is a growing demand for effective and accurate statistical approaches to handle extremely unbalanced data in independent and non-independent samples. Our study introduces classical statistical methods in genetic statistics firstly, then, summarizes the failure of classical statistical methods in dealing with extremely unbalanced data through simulation experiments to draw researchers' attention to the extremely unbalanced data in GWAS.