Background Previous studies have focused on the respiratory system and skin damage caused by refractory ceramic fibers (RCFs). However, investigations into cardiovascular health of workers exposed to RCFs are insufficient. There is limited research on the association between occupational RCFs exposure and abnormal blood pressure, as well as the potential underlying mechanisms. Objective To explore the association between occupational exposure to RCFs and abnormal blood pressure, and to analyze the role of serum 8-hydroxy-2’-deoxyguanosine (8-OHdG) in this relationship, providing a reference for comprehensive health protection strategies for RCFs-exposed workers. Methods Using a cluster sampling method, 311 workers engaged in the production and processing of RCFs at a large RCFs enterprise were selected as the study population. A questionnaire survey was conducted to collect demographic information and other relevant data. The workers’ total dust, respirable fiber, and noise exposure levels were measured. Blood pressure was measured during occupational health examinations, and blood samples were collected. Based on blood pressure levels, the participants were divided into three groups: normotension, prehypertension, and hypertension. Serum 8-OHdG concentrations were determined by enzyme-linked immunosorbent assay (ELISA). Ordinal logistic regression and multiple linear regression models were applied to evaluate the associations of exposures to noise and RCFs with abnormal blood pressure and serum 8-OHdG levels. The mediating effect of serum 8-OHdG on the relationship between occupational RCFs exposure and abnormal blood pressure was analyzed using the PROCESS 4.1 macro. Results All 311 RCFs workers had varying levels of occupational exposure to RCFs, among whom 113 were also exposed to noise. The overall prevalences of prehypertension and hypertension among the participants were 49.84% and 11.25%, respectively. In the noise-exposed group, the prevalences of normotension, prehypertension, and hypertension were 44.2%, 43.4%, and 12.4%, respectively, which showed no statistically significant difference compared to the non-noise-exposed group (35.9%, 53.5%, and 10.6%, respectively; P=0.652). Significant differences were observed in the prevalences of normotension, prehypertension, and hypertension among workers with different levels of total dust exposure (P=0.033) and respirable fiber exposure (P=0.034). The differences in serum 8-OHdG concentrations across these groups were also statistically significant (P<0.05). Multiple regression analyses showed that both total dust exposure level (OR=1.83, 95%CI: 1.34, 2.51) and respirable fiber exposure level (OR=1.85, 95%CI: 1.31, 2.62) were positively associated with the detection of abnormal blood pressure. Furthermore, total dust exposure level (β=5.85, 95%CI: 0.53, 11.17) and respirable fiber exposure level (β=6.04, 95%CI: 0.14, 11.94) were positively associated with serum 8-OHdG concentrations. Further analysis indicated that the severity of abnormal blood pressure was positively associated with serum 8-OHdG concentrations (β=10.54, 95%CI: 3.62, 17.46). Mediation analysis demonstrated that serum 8-OHdG mediated the relationship between RCFs total dust exposure levels and the risk of abnormal blood pressure (P<0.05), accounting for 8.63% of the total effect. However, no mediating effect of serum 8-OHdG was observed in the association between RCFs respirable fiber exposure levels and the risk of abnormal blood pressure (P>0.05). Conclusion Occupational exposure to RCFs is closely associated with an increased risk of abnormal blood pressure and elevated serum 8-OHdG levels. Oxidative stress may play a mediating role in the relationship between RCF exposure and abnormal blood pressure.

Objective: To analyze the trajectories of cognitive function changes and their influencing factors among the elderly, so as to provide evidence for the prevention and intervention of cognitive impairment in this population. Methods: Data were obtained from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), which was conducted in 2011, 2014, and 2018. Information on demographic characteristics and lifestyle behaviors of elderly individuals aged ≥65 years was collected. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Group-based trajectory modeling was conducted using MMSE scores from 2011, 2014, and 2018 to identify trajectories of cognitive function change. The optimal trajectory model was determined using the Bayesian information criterion, Akaike information criterion, and average posterior probability. Factors affecting cognitive function trajectories among the elderly were analyzed using a Multinomial logistic regression model. Results: Data were collected from 2 614 individuals, with the mean age of (78.20±8.93) years. There were 1 251 males (47.86%) and 1 363 females (52.14%). The group-based trajectory model identified three distinct cognitive function trajectories, defined as the stable group, slow decline group, and rapid decline group, consisting of 2 187 (83.66%), 170 (6.50%), and 257 (9.83%) individuals, respectively. Multinomial logistic regression analysis showed that compared with the stable group, each 1-year increase in age was associated with a 315.7% higher risk of being classified into the slowly declining group (OR=4.157, 95%CI: 2.922-5.914) and a 214.6% higher risk of being classified into the rapidly declining group (OR=3.146, 95%CI: 2.428-4.076). Compared with elderly individuals with no formal education, those with primary/junior high school education had a 67.5% lower risk of being classified into the slowly declining group (OR=0.325, 95%CI: 0.207-0.511) and a 30.2% lower risk of being classified into the rapidly declining group (OR=0.698, 95%CI: 0.505-0.964). Compared with unmarried/divorced/widowed elderly individuals, those who were married had a 31.0% lower risk of being classified into the rapid decline group (OR=0.690, 95%CI: 0.509-0.935). Conclusions Based on the CLHLS data, cognitive function trajectories among individuals aged ≥65 years were classified into three patterns: stable, slow decline, and rapid decline. Increased age was associated with a higher risk of cognitive decline, while higher educational level and being married demonstrated protective effects against cognitive deterioration.

This paper presents an automatic acquisition and analytic procedure of acupuncture manipulation based on optical navigation, aiming at solving the shortcomings of existing acquisition methods of acupuncture manipulation. An acquisition holder installed at the handle tail of filiform needle was designed to display the movement trajectory of the needle during acupuncture delivery by collecting the movement trajectory of holder. The 3-month old male Bama miniature pig was selected as the experimental subject, and 6 points, "Bojian" "Qiangfeng" "Housanli" "Xiaokua" "Huiyang" (BL35) and "Baihui" (GV20), were selected during acupuncture manipulation. The optical navigation system was used to collect the real-time data, and these data were per-processed and analyzed using mean filtering and Fourier transform. The acupuncture procedure was divided into 3 stages, inserting, lifting-thrusting, and twisting. The results showed that the accuracy was 96.3% at lifting-thrusting stage, and that was 100.0% at twisting stage. The decomposition effect of the entire procedure was satisfactory. This study provides a new approach to the quantitative analysis of acupuncture manipulation. In the future, it needs to further optimize the algorithm and expand the sample size so as to improve the accuracy of this analytic technique.
Acupuncture Therapy/methods* ; Male ; Animals ; Swine ; Acupuncture Points ; Humans ; Swine, Miniature ; Needles

Objective To explore the efficiency improvement in segmenting neural network with the application of Transformer + U-Net artificial intelligence (AI) and modeling with the application of Python scripts in three-dimensional (3D) printing brachytherapy. Methods A Transformer + U-Net AI neural network model was constructed, and Adam optimizer was used to ensure rapid gradient descent. Computed tomography or magnetic resonance imaging data of patients were standardized and processed as self-made data sets. The training set was used to train AI and the optimal result weight parameters were saved. The test set was used to evaluate the AI ability. Python programming language was used to write an automated script to obtain the output segmentation image and convert it to the STL file for import. The source applicator and needle could be automatically modeled. The time of automatic segmentation and modeling and the time of manual segmentation and modeling were entered by two people, and the difference was verified by paired t-test. Results Dice similarity coefficient (DSC), mean intersection over union (MIOU), and Hausdorff distance (HD95) were used for evaluation. DSC was 0.9341, MIOU was 0.8762, and mean HD95 was 2.516. The mean time of manual segmentation was 1187 s, and the mean time of AI segmentation was 145 s (P < 0.01). The mean time of manual modeling was 321 s, and the mean time of modeling with Python automated scripts was 18 s (P < 0.01). Conclusion The application of Transformer + U-Net automatic segmentation and Python automated scripts can effectively improve work efficiency in the 3D printing brachytherapy for cervical cancer.

In the context of rapid global aging, the number of vulnerable elderly individuals who are sensitive to climate change and air pollution is increasing rapidly, potentially augmenting the burden of related diseases. The intrinsic capacity (IC) of the elderly refers to the comprehensive ability of individuals in physical, cognitive, and mental health aspects, typically encompassing 5 dimensions: cognitive status, motor ability, mental health, sensory function, and vitality. This article reviewed the advancements in epidemiological research on the effects of air pollution and climate change (including meteorological factors) on the overall intrinsic capacity of the elderly and its various dimensions. The results indicated that pollutants such as fine particulate matter (PM_2.5) and ozone (O₃) are most significantly associated with the decline in the cognitive function and vitality dimensions, and extreme meteorological events like high temperatures are also related to the functional deterioration of each dimension of IC. Nevertheless, the current studies mostly focus on the impact of atmospheric environmental factors on a specific dimension of IC rather than on overall IC, and research on the combined exposure to multiple atmospheric factors is even rarer, and the exploration of associated mechanisms is insufficient. Future research should enhance the investigation of the influence and mechanism of the combined exposure to air pollution and climate change on the dynamic changes of IC, and promote multi-center research and transnational cooperation. This review is conducive to clarifying the potential impact of atmospheric environmental factors on the IC of the elderly, providing a scientific basis for formulating health intervention policies to address climate change and air pollution.

AIM:To investigate alterations in the expression levels of inflammatory cytokines and subsets of CD8+ T cells in the peripheral blood of patients with diabetic retinopathy(DR).METHODS:Retrospective study. A total of 40 patients with type 2 diabetes admitted to Xi'an People's Hospital(Xi'an Fourth Hospital)from April to July 2022 were recruited for this study and categorized into two groups: 20 cases in the simple type 2 diabetes mellitus(DM)group, and 20 cases in the DR group. Additionally, 20 healthy individuals undergoing routine physical examinations served as the control group. The expression levels of cytokines, including interleukin(IL)-6, IL-8, and IL-10 in peripheral blood were quantified using ELISA. Flow cytometry was employed to analyze the expression of programmed cell death-1(PD-1), T cell immunoglobulin domain and mucin domain protein-3(TIM-3), CD28, and CD57 on CD8+ T cells.RESULTS:The peripheral blood expression of IL-6, IL-8, and IL-10 inflammatory cytokines were significantly elevated in DR patients as detected by ELISA(all P<0.001); flow cytometry analysis showed that the expression of PD-1, TIM-3, and CD57 were elevated in peripheral blood CD8+ T cells of DR patients(all P<0.001), and the expression of CD28 was decreased(all P<0.001).CONCLUSION:In DR patients, CD8+ T cells may undergo depletion and senescence as a result of elevated pro-inflammatory cytokines, including IL-6, IL-8, and IL-10.

The rapid development of artificial intelligence （AI） technology provides new opportunities for the modernisation of traditional Chinese medicine （TCM） diagnosis. By analysing the foundation， research progress and difficulties of the combination of AI and TCM diagnosis， it is concluded that AI has made remarkable development in intelligence-driven modernization of TCM tongue diagnosis， pulse diagnosis， listening and smelling diagnosis and text processing， and there are useful explorations in the field of constructing data-driven TCM diagnostic model and multidisciplinary integration of TCM diagnostic models. However， the current integration of AI technology in TCM diagnosis still faces many challenges， such as the scarcity and uneven quality of clinical data， the limited ability of AI algorithms to express TCM thinking model of syndrome differentiation and empirical knowledge， and the possible existence of ethical and privacy issues. By systematically sorting out the current research status and development direction of AI-empowered TCM diagnostics， it is proposed to promote the application of AI technology in TCM diagnostics in four aspects， namely， strengthening the construction of TCM big data and talent cultivation， encouraging cross-disciplinary cooperation， improving the legal and ethical framework， and promoting the popularity of the technology in primary care， so as to enhance the modernisation of TCM diagnostics.

Objective:To evaluate the association between heatwaves and fall-related mortality.Methods:A total of 61 421 fall-related mortality from 2013 to 2022 in 7 provinces of China were included in a time-stratified case-crossover design, with daily meteorological data derived from the fifth generation European Reanalysis dataset produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression chimeric distributed lag nonlinear model was used to analyze the association between heatwaves and fall-related mortality and stratified analysis was conducted according to gender and age.Results:Heatwaves were associated with an increased risk of fall-related morality. The risk of fall-related mortality during heatwaves was higher than during non-heatwave periods ( OR=1.11, 95% CI: 1.05-1.18). The attributable fraction of fall-related motality due to heatwaves was 10.25% (95% CI: 4.49%-15.36%). For each 1 ℃ increase above the heatwave threshold, the risk of fall-related mortality increased by 34% ( OR=1.34, 95% CI: 1.02-1.76). The effect of heatwave duration on fall-related mortality was not statistically significant. Stratified analyses indicated that women experienced a higher risk of fall-related mortality during heatwaves ( OR=1.13, 95% CI: 1.04-1.22) compared to man ( OR=1.10, 95% CI: 1.04-1.17). Conclusions:Heatwave increases the risk of fall-related mortality, and the intensity of heatwaves modify this risk. Women are vulnerable populations.

Objective:To evaluate the impact of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality and calculate the attributable mortality burden.Methods:This study collected road traffic mortality data from the Disease Surveillance System in Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces from 2013 to 2018. A time-stratified case-crossover design was used in this study, with the death date for each case serving as the case day. Control days were selected from the same year, month, and day of the week as the case day. A conditional logistic regression model was employed to estimate the cumulative associations of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality (lag 0-1 day) and to calculate the attributable fractions (AF).Results:Compared to non-heatwave days, the excess risk ( ER) of road traffic mortality on daytime heatwave days, nighttime heatwave days, and compound heatwave days was 5.3% (95% CI: 0.5%-10.2%), 4.9% (95% CI: 0.5%-9.4%) and 7.5% (95% CI: 2.3%- 12.9%), with corresponding AF of 5.0% (95% CI: 0.5%-9.3%), 4.7% (95% CI: 0.5%-8.6%), and 6.9% (95% CI: 2.3%-11.4%), respectively. Stratified analysis showed that the risk of traffic mortalities caused by daytime heatwaves was higher in females ( ER=15.7%, 95% CI: 5.8%-26.5%) than in males ( ER=1.8%, 95% CI: -3.6%-7.4%). Elderly individuals over 64 years old ( ER=10.9%, 95% CI: 0.3%- 22.6%) had a higher risk of road traffic mortalities from compound heatwaves than those under 45 years old ( ER=2.6%, 95% CI: -5.4%-11.2%). The risk of road traffic injury mortality from motor vehicle accidents caused by compound heatwaves ( ER=16.6%, 95% CI:2.4%-32.7%) was higher than that from non-motor vehicle accidents ( ER=5.7%, 95% CI:0.1%-11.5%). Conclusions:Short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves was associated with an increased risk of road traffic mortality, with the strongest association observed for compound heatwaves. The mortality burden attributable to compound heatwaves was higher than that for daytime and nighttime heatwaves. Heatwaves were more significantly associated with road traffic mortality risk among females, elderly individuals over 64 years old, and motor vehicle accidents.

Objective:To explore the risk fall death associated with compound hot extremes.Methods:This study collected data on fall deaths in Guangdong, Hunan, and Zhejiang Provinces from 2013 to 2018 and matched their exposure to meteorological data. Based on a time-stratified case-crossover design, a conditional logistic regression model embedded with a cross-basis function of the distributed lag nonlinear model was applied to estimate the risk of fall to death due to compound hot extremes.Results:Compared with regular days, compound hot extremes significantly increased the risk of death from falls ( OR=1.19, 95% CI: 1.09-1.30), and women ( OR=1.27, 95% CI: 1.11-1.45) and the elderly age 65 and above ( OR=1.24, 95% CI: 1.12-1.39) were more sensitive to compound hot extremes. The maximum duration of compound hot extremes was 7 days, and the maximum intensity was 6.2 ℃, and the duration and intensity were proportional to the risk of death from falls. The risk of death from falls increased by 12% ( OR=1.12, 95% CI: 1.06-1.18) each day, increasing in duration after linearization. The risk of death from falls increased by 16% ( OR=1.16, 95% CI: 1.10-1.22) for each 1 ℃ increase in linearized intensity. Conclusion:Compound hot extremes increase the risk of death cases from falls.