ObjectiveTo observe the clinical effectiveness and safety of Qingfei Shenshi Decoction （清肺渗湿汤） combined with western medicine for patients with bronchial asthma of heat wheezing syndrome， and to explore its potential mechanism of action. MethodsEighty-six participants with bronchial asthma of heat wheezing syndrome were randomly divided into treatment group and control group， each group with 43 participants. The control group received conventional western medicine， and the treatment group was additionally administered Qingfei Shenshi Decoction orally on the basis of the control group， 1 dose per day. Both groups were treated for 14 days. The primary outcome measure was clinical effectiveness； secondary outcome measures included traditional Chinese medicine （TCM） syndrome score， asthma control test （ACT） score， pulmonary function indices such as forced expiratory volume in 1 second （FEV₁）， forced vital capacity （FVC）， peak expiratory flow （PEF）， serum inflammatory factor levels including interleukin-4 （IL-4）， tumour necrosis factor-α （TNF-α）， and high-sensitivity C-reactive protein （hs-CRP）， and immune function indices including CD3⁺， CD4⁺， CD8⁺， CD4⁺/CD8⁺. All outcome measures were evaluated before and after treatment. Vital signs were monitored， and electrocardiography， blood routine， urine routine， liver function， and renal function tests were performed before and after treatment. Adverse events and reactions during the study were recorded. ResultsA total of 80 patients completed the trial with 40 in each group. The total clinical effective rate of the treatment group was 97.5% （39/40）， which was significantly higher than that of the control group （85.0%， 34/40， P＜0.05）. After treatment， both groups showed decreased TCM syndrome scores， IL-4， TNF-α， hs-CRP， and CD8⁺ levels， as well as increased ACT scores， CD3⁺， CD4⁺， CD4⁺/CD8⁺， FEV₁， FVC， and PEF levels （P＜0.05 or P＜0.01）. Moreover， the improvements in these indices were more significant in the treatment group than in the control group （P＜0.05 or P＜0.01）. No significant abnormalities in safety indicators were observed in either group， and no adverse events or reactions occurred. ConclusionQingfei Shenshi Decoction combined with conventional western medicine for patients with bronchial asthma of heat wheezing syndrome can effectively improve the clinical symptoms， pulmonary function， and clinical effectiveness， with good safety. Its mechanism may be related to reducing inflammatory factor levels and regulating T lymphocyte subsets to improve immune function.

Objective To systematically analyze the characteristics of the disease burden of hypertensive heart disease (HHD) in the elderly (≥60 years) globally and in China from 1990 to 2021, and to predict its future trends from 2022 to 2040, with the aim of providing data support for optimizing comprehensive prevention and control strategies for HHD. Methods Based on the Global Burden of Disease (GBD) 2021 database, the number of prevalent cases and disability-adjusted life years (DALYs) of HHD in the elderly were extracted for the world, China, and five regions categorized by sociodemographic index (SDI). Joinpoint regression was used to analyze the temporal trends of age-standardized prevalence rate and age-standardized DALYs rate of HHD in the elderly. A three-factor decomposition method was applied to evaluate the relative contributions of aging, population growth, and epidemiological changes to the variations in the elderly HHD burden. Additionally, a Bayesian age-period-cohort model was used to predict the elderly HHD burden from 2022 to 2040. Results In 2021, the number of prevalent elderly HHD cases reached 10 283 000 globally and 3 412 400 in China, representing increases of 179.20% and 159.20% respectively, compared with 1990. The DALYs of elderly HHD were 18 812 700 person-years globally and 4 731 400 person-years in China, rising by 76.08% and 29.45% respectively from 1990. Meanwhile, the growth rates of the number of prevalent cases and DALYs of elderly HHD varied across different SDI regions. From 1990 to 2021, the age-standardized prevalence rate of elderly HHD in China, as well as the age-standardized DALYs rate of elderly HHD both globally and in China, showed significant downward trends (all average annual percentage changes<0, all P<0.001). In 2021, the 70-74 years age group accounted for the highest proportion of prevalent cases and DALYs of elderly HHD, both globally and in China. Decomposition analysis revealed that population growth was the dominant factor driving the increase in the elderly HHD burden across all regions. The prediction model results indicated that the number of prevalent cases and DALYs of elderly HHD would continue to rise globally and in China from 2022 to 2040, with the growth rate of the elderly HHD burden in China between 2021 and 2040 expected to exceed the global average. Conclusion Over the past 32 years, although the age-standardized disease rates of elderly HHD have mainly shown a downward trend globally and in China, the absolute number of the disease burden has increased substantially. The projection model indicates a continued upward trajectory, with the growth rate in China higher than the global average. Therefore, there is an urgent need to implement precise prevention and control strategies to effectively mitigate the disease burden of elderly HHD.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

BACKGROUND: The mechanisms distinguishing metabolically healthy from unhealthy phenotypes within the same BMI categories remain unclear. This study aimed to investigate the associations between regional fat distribution and metabolically unhealthy phenotypes in Chinese adults across different BMI categories. METHODS: This cross-sectional study involving 11833 Chinese adults aged 20 years and older. Covariance analysis, adjusted for age, compared the percentage of regional fat (trunk, leg, or arm fat divided by whole-body fat) between metabolically healthy and unhealthy participants. Trends in regional fat percentage with the number of metabolic abnormalities were assessed by the Jonckheere-Terpstra test. Odds ratios (ORs) and their 95% confidence intervals (CIs) were estimated by logistic regression models. All analyses were performed separately by sex. RESULTS: In non-obese individuals, metabolically unhealthy participants exhibited higher percent trunk fat and lower percent leg fat compared to healthy participants. Additionally, percent trunk fat increased and percent leg fat decreased with the number of metabolic abnormalities. After adjustment for demographic and lifestyle factors, as well as BMI, higher percent trunk fat was associated with increased odds of being metabolically unhealthy [highest vs. lowest quartile: ORs (95%CI) of 1.64 (1.35, 2.00) for men and 2.00 (1.63, 2.46) for women]. Conversely, compared with the lowest quartile, the ORs (95%CI) of metabolically unhealthy phenotype in the highest quartile for percent arm and leg fat were 0.64 (0.53, 0.78) and 0.60 (0.49, 0.74) for men, and 0.72 (0.56, 0.93) and 0.46 (0.36, 0.59) for women, respectively. Significant interactions between BMI and percentage of trunk and leg fat were observed in both sexes, with stronger associations found in individuals with normal weight and overweight. CONCLUSIONS Trunk fat is associated with a higher risk of metabolically unhealthy phenotype, while leg and arm fat are protective factors. Regional fat distribution assessments are crucial for identifying metabolically unhealthy phenotypes, particularly in non-obese individuals.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Adipose Tissue ; Body Fat Distribution ; Body Mass Index ; China/epidemiology* ; Cross-Sectional Studies ; Health Surveys ; Phenotype

BACKGROUND: Previous studies have demonstrated that short-term exposure to ambient particulate matter elevates the risk of ischemic stroke in major urban areas of various countries. However, there is a notable gap in research focusing on remote areas inhabited by ethnic minorities and the cumulative effects of air pollutants. Our study conducted in the area aims to explore the potential association between ischemic stroke and air pollutants and contribute to improving health outcomes among the community. METHODS: This retrospective observational study was conducted at the Xing'an League People's Hospital in Inner Mongolia. The medical records of 4,288 patients admitted for IS between November 1, 2019, and October 31, 2020, were reviewed. Data on demographics (age and sex), air pollutants (PM₁₀, PM_2.5, NO₂, NO, CO, and O₃), and meteorological factors (daily average temperature, daily average wind speed, and daily average atmosphere pressure) were collected and analyzed. The statistical analysis included descriptive statistics, Poisson distribution analysis to evaluate the adverse effects of atmospheric pollutants on daily hospitalizations, and subgroup analysis to determine whether gender and age could modify the impact on hospitalizations. RESULTS: A substantial correlation was revealed in single-day lags model. The peak delayed effects of PM₁₀, PM_2.5, SO₂, and NO₂ were observed at lag8 (PM₁₀ (OR = 1.016, 95%CI 1.002, 1.030), PM_2.5 (OR = 1.027, 95%CI 1.007, 1.048), SO₂ (OR = 1.153, 95%CI 1.040, 279) and NO₂ (OR = 1.054, 95%CI 1.005, 1.105)) while males exhibited a consistent trend from lag0 to lag8 (PM₁₀ (OR = 1.035, 95%CI 1.018, 1.053), PM_2.5 (OR = 1.056, 95%CI 1.030, 1.082), SO₂ (OR = 1.220, 95%CI 1.072, 1.389), NO₂ (OR = 1.126, 95%CI 1.061, 1.120), CO (OR = 10.059, 95%CI 1.697, 59.638) and O₃ (OR = 0.972, 95%CI 0.946, 0.999)). When gender and age were considered, a positive impact was also observed after three days cumulative effect in males. CONCLUSIONS There is a significant cumulative effect of exposure to air pollution on IS hospital admissions, especially the males and patients under the age of 65. Our results also suggested that a notable association between CO and NO₂ in two-pollutant models.
Humans ; Male ; Female ; Air Pollution/analysis* ; China/epidemiology* ; Retrospective Studies ; Middle Aged ; Air Pollutants/analysis* ; Aged ; Particulate Matter/analysis* ; Hospitalization/statistics & numerical data* ; Adult ; Ischemic Stroke/chemically induced* ; Environmental Exposure/adverse effects* ; Aged, 80 and over

Objective To investigate the effects of low-dose ionizing radiation on the thyroid status and hormone levels of radiation workers. Methods Radiation workers who underwent occupational health examinations at a hospital in Guangzhou from 2015 to 2022 were selected as the subjects of this study. The levels of FT3, FT4 and TSH were analyzed, and the thyroid abnormality status of radiation workers in different groups were compared. Results A total of 1152 participants were included in this study, consisting of 885 (76.82%) males and 267 (23.18%) females, with an average age of (35.26 ± 10.16) years. The prevalence of thyroid abnormalities was 9.38%, which was significantly higher in females (13.86%) than in males (8.02%) (P < 0.05). The TSH level of females [(2.15 ± 1.29) mIU/L] was higher than that of males [(1.85 ± 1.20) mIU/L], while the levels of FT3 [(5.10 ± 0.64) pmol/L] and FT4 [(15.84 ± 2.32) pmol/L] in females were lower than those in males [(5.23 ± 0.63) pmol/L and (16.61 ± 2.75) pmol/L, P < 0.05]. The FT3 of industrial workers [(5.25 ± 0.63) pmol/L] was higher than that of medical workers [(5.10 ± 0.63) pmol/L], while the TSH of industrial workers [(1.80 ± 1.12) mIU/L] was lower than that of medical workers [(2.15 ± 1.37) mIU/L]. FT4 levels decreased with increasing age and duration of occupational exposure. Multivariable logistic regression analysis revealed that sex was a significant independent predictor of thyroid abnormalities among radiation workers. Female workers were more likely to experience thyroid abnormalities (β = −0.62, P < 0.05). Conclusion Low-dose ionizing radiation may have a certain impact on the thyroid status of radiation workers, especially for female workers, which requires further attention and research.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

AIM:To investigate the protective effects of soy isoflavones on retinal ganglion cells(RGCs)damage in diabetic rats and related mechanisms.METHODS: Totally 80 male SD rats(80 eyes), aged 4-6 weeks, were randomly divided into four groups(n=20 per group): a control group, a diabetic model group, a low-dose soy isoflavone treatment group, and a high-dose soy isoflavone treatment group. Among them, the control group was fed normal chow, while the diabetic group, soy isoflavone low-dose-treated group, and soy isoflavone high-dose-treated group were fed high-fat chow. After a feeding period of 4 wk, rats in the diabetic group, as well as those in the soy isoflavone low-dose and high-dose treatment groups, were injected intraperitoneally with streptozotocin(STZ)at a dose of 50 mg/kg to establish a diabetic model. Rats in the control group received an equivalent volume of sodium citrate buffer acid. The soy isoflavone low-dose-treated group was administered 360 mg/kg of soy isoflavones daily via gavage, while the soy isoflavone high-dose-treated group received 540 mg/kg of soy isoflavones daily via gavage. Both the control group and the diabetic group were given an equal amount of purified water daily via gavage. Body weight and blood glucose levels were measured at 4 and 8 wk post-gavage treatment. The eyes were extracted and the retinas were dissected at 8 wk following the gavage treatment. The number of RGCs in each group was determined using immunochemical tissue staining and protein blotting techniques, while the superoxide dismutase(SOD)activity and malondialdehyde(MDA)content of the rat retinal tissue were measured through histochemical methods.RESULTS: Compared with diabetic rats, treatment with high-dose soy isoflavones for 8 wk resulted in a reduction of blood glucose to 8.9±1.23 mmol/L, an increase in intraretinal SOD activity to 849.93±63.71 U/mgprot, a decrease in MDA content to 45.77±0.59 nmol/mgprot, and an increase in the number of RGCs to 76±1 cells/mm2, which is comparable to the control group's data(all P<0.05).CONCLUSION: Soy isoflavones can reduce retinal oxidative stress in diabetic rats and protect RGCs.