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 assess the association between temperature and risk of animal injury, and identifying vulnerable populations.Methods:Based on a time-stratified case-crossover design, the number of animal injuries monitored in hospitals of Guangdong Provincial Injury Surveillance System in 2011 and 2015-2016 was included, and the daily meteorological data were derived from the fifth generation of European ReAnalysis-Land, which was produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression combined with a distributed lagged nonlinear model was applied to analyze the association of temperature and animal-specific injuries. We also conducted stratified analysis by region, sex, age, occupation, and location of injury occurrence.Results:There was an almost linear relationship between temperature and the occurrence of animal injury. The excess risk ( ER) of animal injury was 2.65% (95% CI: 2.27%-3.04%) for a 1 ℃ rise in temperature with much higher risk of occurrence ( ER=9.34%, 95% CI: 7.57%-11.13%) for non-mammalian injury than that for mammalian injuries ( ER=2.30%, 95% CI: 1.90%-2.70%). Stratified analysis revealed that the occurrence of animal injury was more susceptible to temperature influences in urban ( ER=2.78%, 95% CI: 2.35%-3.21%), female ( ER=2.71%, 95% CI: 2.16%-3.27%), the elderly aged 60 years and above ( ER=3.05%, 95% CI: 1.65%- 4.47%), farmer ( ER=4.66%, 95% CI: 3.03%-6.32%) and agricultural area ( ER=10.63%, 95% CI: 7.57%-13.79%) than their correspondents. In terms of mammalian injury, dog bites showed the highest risk ( ER=2.71%, 95% CI: 2.12%-3.30%). In terms of non-mammalian,snake injuries were highly influenced by temperature ( ER=16.74%, 95% CI: 11.33%-22.40%). Conclusions:The ambient temperature rises could increase the risk of animal injury with much higher risk for non-mammalian than that for mammalian injuries. Our findings suggest that global warming may increase the risk and disease burden from animal injuries.

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 assess the association between temperature and risk of animal injury, and identifying vulnerable populations.Methods:Based on a time-stratified case-crossover design, the number of animal injuries monitored in hospitals of Guangdong Provincial Injury Surveillance System in 2011 and 2015-2016 was included, and the daily meteorological data were derived from the fifth generation of European ReAnalysis-Land, which was produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression combined with a distributed lagged nonlinear model was applied to analyze the association of temperature and animal-specific injuries. We also conducted stratified analysis by region, sex, age, occupation, and location of injury occurrence.Results:There was an almost linear relationship between temperature and the occurrence of animal injury. The excess risk ( ER) of animal injury was 2.65% (95% CI: 2.27%-3.04%) for a 1 ℃ rise in temperature with much higher risk of occurrence ( ER=9.34%, 95% CI: 7.57%-11.13%) for non-mammalian injury than that for mammalian injuries ( ER=2.30%, 95% CI: 1.90%-2.70%). Stratified analysis revealed that the occurrence of animal injury was more susceptible to temperature influences in urban ( ER=2.78%, 95% CI: 2.35%-3.21%), female ( ER=2.71%, 95% CI: 2.16%-3.27%), the elderly aged 60 years and above ( ER=3.05%, 95% CI: 1.65%- 4.47%), farmer ( ER=4.66%, 95% CI: 3.03%-6.32%) and agricultural area ( ER=10.63%, 95% CI: 7.57%-13.79%) than their correspondents. In terms of mammalian injury, dog bites showed the highest risk ( ER=2.71%, 95% CI: 2.12%-3.30%). In terms of non-mammalian,snake injuries were highly influenced by temperature ( ER=16.74%, 95% CI: 11.33%-22.40%). Conclusions:The ambient temperature rises could increase the risk of animal injury with much higher risk for non-mammalian than that for mammalian injuries. Our findings suggest that global warming may increase the risk and disease burden from animal injuries.

Arthritis, encompassing osteoarthritis (OA), rheumatoid arthritis (RA), and gouty arthritis (GA), is a prevalent inflammatory disease that significantly impacts quality of life. Natural products (NPs), derived from animals, plants, marine organisms, and microorganisms, have demonstrated beneficial effects in arthritis treatment both domestically and internationally. These natural compounds offer advantages in drug discovery due to their skeletal diversity, structural complexity, and multi-effect, multi-target, and low-toxicity properties compared to conventional small-molecule medicines. However, unclear mechanisms have hindered the development and clinical application of NPs. This review summarizes recent experimental studies from the past decade on natural medicine for arthritis treatment, emphasizing key NPs with therapeutic effects on OA, RA, and GA. It examines the effects and molecular mechanisms of NPs acting on different cells to treat arthritis. Furthermore, this review provides insights into the future prospects of NP research in this field, which is crucial for advancing NP-based arthritis treatments.
Humans ; Biological Products/therapeutic use* ; Animals ; Arthritis, Rheumatoid/drug therapy* ; Arthritis, Gouty/drug therapy* ; Arthritis/drug therapy* ; Osteoarthritis/drug therapy*

To comprehensively assess the true visual function of clinical dry eye patients and the comprehensive impact of blinking characteristics on functional vision of the human eye,an intelligent vision measurement system has been designed and developed to detect and analyze blinks from the side.The system employs deep learning keypoint recognition technology to analyze eyelid features from a lateral perspective.It presents the data of identified key points for the upper and lower eyelids in a line chart format and annotates the trough of each blink.By setting benchmark values,the system automatically calculates the proportion of complete and incomplete blinks in the tested individuals.The results indicate that the system is stable in performance and accurate in measurement,successfully achieving the anticipated design objectives.It thereby provides reliable technical support for future clinical applications.

Alzheimer's disease （AD） is one of the most common diseases in the elderly population. Its etiology involves multiple pathogenic factors and pathological links such as abnormal deposition of β amyloid protein （Aβ）， hyperphosphorylation of Tau protein， abnormalities of the cholinergic system， oxidative stress， and inflammatory response. However， its specific pathogenesis has not been clarified， and no specific therapeutic drugs have been found. In recent years， more and more studies have paid attention to the potential of chemical components of traditional Chinese medicine （TCM） in the treatment of AD. However， the diversity and complexity of the chemical components of TCM may have a positive impact on multiple pathological links of AD. Researchers have isolated many active components from TCMs， and the effects of treating AD have been confirmed by modern pharmacological studies. Through literature analysis， this article found that the main chemical components of TCM with anti-AD effects were saponins （31%）， flavonoids （24%）， polysaccharides （20%）， lactones （8%）， alkaloids （7%）， phenols （3%）， and other compounds （7%）. Among them， ginsenoside， notoginsenoside， epimedium flavones， puerarin， baicalein， schisandra polysaccharide， angelica polysaccharide， ganoderma lucidum polysaccharide， pachyman， huperzine A， berberine， andrographolide， curcumin， emodin， and gastrodin have been extensively studied in terms of their anti-AD effects， and their mechanisms of pharmacological action have been involved in many aspects of AD pathogenesis. This article reviews the anti-AD activities and possible mechanisms of chemical components of TCM， so as to provide a reference for the development of new drugs for the prevention and treatment of AD.

Background Air pollution is a major public health concern. Air Quality Health Index (AQHI) is a very important air quality risk communication tool. However, AQHI is usually constructed by single-pollutant model, which has obvious disadvantages. Objective To construct an AQHI based on the joint effects of multiple air pollutants (J-AQHI), and to provide a scientific tool for health risk warning and risk communication of air pollution. Methods Data on non-accidental deaths in Yunnan, Guangdong, Hunan, Zhejiang, and Jilin provinces from January 1, 2013 to December 31, 2018 were obtained from the corresponding provincial disease surveillance points systems (DSPS), including date of death, age, gender, and cause of death. Daily meteorological (temperature and relative humidity) and air pollution data (SO₂, NO₂, CO, PM_2.5, PM₁₀, and maximum 8 h O₃ concentrations) at the same period were respectively derived from China Meteorological Data Sharing Service System and National Urban Air Quality Real-time Publishing Platform. Lasso regression was first applied to select air pollutants, then a time-stratified case-crossover design was applied. Each case was matched to 3 or 4 control days which were selected on the same days of the week in the same calendar month. Then a distributed lag nonlinear model (DLNM) was used to estimate the exposure-response relationship between selected air pollutants and mortality, which was used to construct the AQHI. Finally, AQHI was classified into four levels according to the air pollutant guidance limit values from World Health Organization Global Air Quality Guidelines (AQG 2021), and the excess risks (ERs) were calculated to compare the AQHI based on single-pollutant model and the J-AQHI based on multi-pollutant model. Results PM_2.5, NO₂, SO₂, and O₃ were selected by Lasso regression to establish DLNM model. The ERs for an interquartile range (IQR) increase and 95% confidence intervals (CI) for PM_2.5, NO₂, SO₂ and O₃ were 0.71% (0.34%–1.09%), 2.46% (1.78%–3.15%), 1.25% (0.9%–1.6%), and 0.27% (−0.11%–0.65%) respectively. The distribution of J-AQHI was right-skewed, and it was divided into four levels, with ranges of 0-1 for low risk, 2-3 for moderate risk, 4-5 for high health risk, and ≥6 for severe risk, and the corresponding proportions were 11.25%, 64.61%, 19.33%, and 4.81%, respectively. The ER (95%CI) of mortality risk increased by 3.61% (2.93–4.29) for each IQR increase of the multi-pollutant based J-AQHI , while it was 3.39% (2.68–4.11) for the single-pollutant based AQHI . Conclusion The J-AQHI generated by multi-pollutant model demonstrates the actual exposure health risk of air pollution in the population and provides new ideas for further improvement of AQHI calculation methods.