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.

Background Injury poses a serious threat to human health. As global warming continues to intensify, there is an urgent need to explore the impact of temperature changes on injury deaths. However limited research has focused on this issue. Objective To investigate the relationship between daily mean temperature change (Tm) and injury death, as well as to estimate the associated future death burden in Hunan Province. Methods We employed an individual-level, time-stratified case-crossing design to establish a conditional logistic regression model to analyze the exposure-response relationship between daily mean temperature change and injury death in Hunan Province from 2013 to 2018. Consequently, we conducted subgroup analysis of gender, age group, and injury type. Finally, we estimated the excess burden of injury death attributable to temperature changes under a sustainable development path [low emission scenario (SSP1-2.6)], regional competition path [high emission scenario (SSP3-7.0)], or fossil fuel development path [very high emission scenario (SSP5-8.5)]. Results The study collected 155577 injury deaths in Hunan Province. The results indicated that for each 1 ℃ increment in daily mean temperature, the cumulative excess risk (CER) of injury mortality among Hunan residents increased by 0.71% (95%CI: 0.53%, 0.90%). Notably, the CER for intentional injuries (1.06%, 95%CI: 0.51%, 1.61%) was higher than that for unintentional injuries (0.66%, 95%CI: 0.46%, 0.87%). Warmer temperatures were positively associated with CER of mortality due to drowning, falls, transport injuries, assaults, and suicides, while they were negatively associated with mortality due to poisoning. Compared with 2010–2019, for 2090–2099, the excess mortality rate (EMR) due to ambient temperature increase in Hunan Province under the SSP5-8.5 scenario (14.62/100000, 95%CI: 10.81/100000, 18.40/100000) would be higher than that of the SSP3-7.0 scenario (10.28/100000, 95%CI: 7.58/100000, 12.97/100000) and the SSP1-2.6 scenario (3.35/100000, 95%CI: 2.46/100000, 4.23/100000); the EMR would be around 2.5 times among men (20.64/100000, 95%CI: 14.44/100000, 26.8/100000) than that among women (8.33/100000, 95%CI: 3.98/100000, 12.6/100000). Among unintentional injuries, the leading contributors to EMR would be drowning (4.46/100000), falls (3.96/100000), and transport injuries (2.96/100000). And among intentional injuries, the EMR for suicide (2.08/100000) would be higher than that for assault (0.47/100000). Conclusion Climate warming will increase the total burden of injury-related deaths among residents in Hunan Province, especially in the absence of effective mitigation strategies and measures. It is necessary to strengthen the prevention and control of severe injuries closely related to temperature changes, such as drowning, falls, traffic, and suicides injuries, in order to reduce injury deaths associated with climate change.

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.

Objective:To investigate the expression of DARS2 and its clinical significance in colorectal cancer.Methods:In this study, bioinformatics tools, especially gene expression profile interactive analysis 2 (GEPIA2), were used to conduct an in-depth analysis of DARS2 expression in colorectal cancer tissues. Immunohistochemical staining was carried out in 108 colorectal cancer specimens and 30 normal colorectal tissues obtained from the First Affiliated Hospital of Nanchang University, Nanchang, China. Colorectal cancer cell lines (HCT116 and SW480) were transfected with small interfering RNA (siRNA) and DARS2 overexpression plasmid to examine the effects of DARS2 knockdown and overexpression on cell function. To assess the effects on cell function, CCK8 and transwell migration assays were used to assess proliferation and cell motility, respectively. Additionally, protein immunoblotting was employed to scrutinize the expression of proteins associated with the epithelial-mesenchymal transition of colorectal cancer cells.Results:DARS2 exhibited a pronounced upregulation in expression within colorectal cancer tissues compared to their normal epithelial counterparts. Furthermore, DARS2 expression was higher in colorectal cancer of stage Ⅲ-Ⅳ than those of stage Ⅰ-Ⅱ, exhibiting a significant correlation with N staging, M staging, and pathological staging ( P<0.05). Kaplan-Meier analyses showed a decreased overall survival rate in colorectal cancer with DARS2 expression compared to those without DARS2 expression ( P<0.05). In the siRNA transfection group, there was a significant reduction in cell proliferation and migration ( P<0.01 and P<0.05, respectively). Conversely, the transfection of DARS2 overexpression plasmids substantially increased both cell proliferation and migration ( P<0.05). Additionally, immunoblotting revealed that DARS2 knockdown led to an upregulation of E-cadherin expression and a downregulation of N-cadherin and vimentin expression. In contrast, DARS2 overexpression resulted in increased N-cadherin and vimentin expression, coupled with reduction in E-cadherin expression. Conclusions:There is a strong association between DARS2 expression and colorectal cancer progression. Silencing DARS2 inhibits cell proliferation and migration, exerting a discernible influence on the epithelial-mesenchymal transition process.

Objective To investigate the predictive value of inflammatory cells and clinical features in the prognosis of immune checkpoint inhibitors (ICIs) treating non-small cell lung cancer (NSCLC).Methods The data of 163 cases of stage Ⅲ and Ⅳ NSCLC patients treated with the ICIs in this hospital from January 1,2017 to December 31,2022 were collected.The CT examination was conducted after 6-8 weeks treatment.The pa-tients were divided into the objective remission group[complete remission (CR)+partial remission (PR)]and non-objective remission group[stable disease (SD)+progressed disease (PD)],disease control group (CR+PR+SD) and non-disease control group (PD),persistent clinical benefit group (DCB) and non-DCB group.The differences in clinical features and inflammatory cells indicators were compared among the differ-ent groups.The receiver operating characteristic (ROC) curve was adopted to evaluate the predictive efficiency of the inflammatory cells indicators for DCB.The influencing factors analysis of progression free survival (PFS) time and overall survival (OS) time adopted the Cox regression analysis.Results The lymphocyte count (ALC) in the disease control group was higher than that in the non-disease control group.The neutro-phil to lymphocyte ratio (NLR),platelet-lymphocyte ratio (PLR) and mononuclear lymphocyte ratio (MLR) were lower than those in the non-disease control group.The proportions of squamous cell carcinoma,stage Ⅲ,ECOG score 0-1 point,adverse reactions in the DCB group were higher than those in the non-DCB group (P<0.05),the PLT count,NLR,PLR and MLR were lower than those in the non-DCB group (P<0.05). The ROC curve analysis results showed that PLT,NLR,PLR and MLR could serve as the indicators for pre-dicting DCB,the area under of ROC curve (AUC) was 0.633,0.602,0.635 and 0.604 respectively,the opti-mal cut off values were 187×109/L (P=0.004),5.0 (P=0.026),235 (P=0.003) and 0.35 (P=0.024) re-spectively.The multivariate Cox regression analysis showed that non-squamous carcinoma including adenocar-cinoma (HR=1.565,95％CI:1.057-2.316) and other pathologic types (HR=2.285,95％CI:1.326-3.936),ECOG score 2-3 points (HR=2.375,95％CI:1.652-3.415),AMC≥0.65×109/L (HR=1.847,95％CI:1.160-2.938) and PLR≥235 (HR=1.557,95％CI:1.016-2.386) were the independent risk factors for short PFS.The ECOG score 2-3 points (HR=4.615,95％CI:2.882-7.391),AMC≥0.65×109/L (HR=5.161,95％CI:2.984-8.925) and PLR ≥235 (HR=1.732,95％CI:1.059-2.833) were the independent risk fac-tors for short OS (P<0.05),and having adverse reactions (HR=0.472,95％CI:0.294-0.757) was the independ-ent protective factor for short OS (P<0.05).Conclusion Lower PLT,AMC,NLR,MLR and PLR,higher ALC,squamous cell carcinoma,TNM stage Ⅲ,ECOG score 0-1 point and immunotherapy related adverse reactions could prompt that the prognosis is good in ICIs treating advanced NSCLC.PLT,NLR,PLR and MLR could serve as the indicators for predicting DCB.

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.