Potential causal links of long-term exposure to PM2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10-year cohort study in South China.

There is a lack of evidence from cohort studies on the causal association of long-term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10-year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO4 2-), nitrate (NO3 -), and ammonium (NH4 +) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10-year follow-up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02-1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4 +, OM, NO3 -, and SO4 2- was associated with HRs of 1.36 (95%CI: 1.13-1.65), 1.35 (95%CI: 1.07-1.70), 1.33 (95%CI: 1.11-1.59), 1.32 (95%CI: 1.06-1.64), 1.31 (95%CI: 1.08-1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long-term exposure to PM2.5 and its components and the risk of NPC recurrence.

The efficacy and safety of adding PD-1 blockade to induction chemotherapy and concurrent chemoradiotherapy (IC-CCRT) for locoregionally advanced nasopharyngeal carcinoma: an observational, propensity score-matched analysis.

BACKGROUND: Despite the success of PD-1 blockade in recurrent/metastatic nasopharyngeal carcinoma (NPC), its effect for locoregionally advanced NPC (LANPC) remains unclear. This study aimed to evaluate the benefit of adding PD-1 blockade to the current standard treatment (gemcitabine and cisplatin IC  plus cisplatin CCRT ) for LANPC patients. METHODS: From January 2020 to November 2022, 347 patients with non-metastatic high-risk LANPC (stage III-IVA, excluding T3-4N0) were included. Of the 347 patients, 268 patients were treated with standard treatment (IC-CCRT), and 79 received PD-1 blockade plus IC-CCRT (PD-1 group). For the PD-1 group, PD-1 blockade was given intravenously once every 3 weeks for up to 9 cycles (3 induction and 6 adjuvant). The primary endpoint was disease-free survival (DFS) (i.e. freedom from local/regional/distant failure or death). The propensity score matching (PSM) with the ratio of 1:2 was performed to control confounding factors. RESULTS: After PSM analysis, 150 patients receiving standard treatment and 75 patients receiving additional PD-1 blockade remained in the current analysis. After three cycles of IC, the PD-1 group had significantly higher rates of complete response (defined as disappearance of all target lesions; 24% vs. 9%; P = 0.006) and complete biological response (defined as undetectable cell-free Epstein-Barr virus DNA, cfEBV DNA; 79% vs. 65%; P = 0.046) than that in the standard group. And the incidence of grade 3-4 toxicity during IC was 47% in the PD-1 group and 41% in the standard group, with no significant difference (P = 0.396). During follow-up period, additional PD-1 blockade to standard treatment improved 3-year DFS from 84 to 95%, with marginal statistical significance (HR, 0.28; 95%CI, 0.06-1.19; P = 0.064). CONCLUSION: Additiaonl PD-1 blockade to gemcitabine and cisplatin IC and adjuvant treatment results in significant improvement in tumor regression, cfEBV DNA clearance, superior DFS, and comparable toxicity profiles in high-risk LANPC patients.

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.

BACKGROUND: Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance. METHODS: Based on the surveillance data of infectious diarrhea cases, relevant symptoms and meteorological factors of Guangzhou from 2016 to 2021, we developed four base prediction models using artificial neural networks (ANN), Long Short-Term Memory networks (LSTM), support vector regression (SVR) and extreme gradient boosting regression trees (XGBoost), which were then ensembled using stacking to obtain the final prediction model. All the models were evaluated with three metrics: mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE). RESULTS: Base models that incorporated symptom surveillance data and weekly number of infectious diarrhea cases were able to achieve lower RMSEs, MAEs, and MAPEs than models that added meteorological data and weekly number of infectious diarrhea cases. The LSTM had the best prediction performance among the four base models, and its RMSE, MAE, and MAPE were: 84.85, 57.50 and 15.92%, respectively. The stacking ensembled model outperformed the four base models, whose RMSE, MAE, and MAPE were 75.82, 55.93, and 15.70%, respectively. CONCLUSIONS: The incorporation of symptom surveillance data could improve the predictive accuracy of infectious diarrhea prediction models, and symptom surveillance data was more effective than meteorological data in enhancing model performance. Using stacking to combine multiple prediction models were able to alleviate the difficulty in selecting the optimal model, and could obtain a model with better performance than base models.

The joint impact of PM2.5 constituents on the risk of cerebrovascular diseases hospitalization: A large community-based cohort study.

Air pollution poses significant health risks to urban areas, with limited focus on the chronic association of PM2.5 and its constituents on cerebrovascular diseases (CERs), especially regarding the joint associations. This study explores the individual and joint associations between PM2.5 constituents and CER hospitalization risks through a cohort analysis of 36,271 adults in the Pearl River Delta, South China, from 2015 to 2020. Cox proportional hazards regression and quantile-based g-computation models were used to quantify the individual and joint associations of annual mean concentrations of PM2.5 constituents with hospitalization for CERs. 1151 participants were hospitalized due to CERs during the five-year follow-up period. Joint associations analyses identified that one quartile increase in co-exposure may result in hazard ratios of 1.530 (1.441-1.623), 1.840 (1.710-1.980), and 1.609 (1.491-1.737) for CERs, total, and ischemic stroke hospitalization, respectively. The adverse effect was primarily driven by organic matter and chlorine. Men, those with a history of tobacco or alcohol use or with low residential greenness, were more susceptible to CERs hospitalization following PM2.5 constituents co-exposure. Upcoming strategies should focus on monitoring and regulating PM2.5 constituents, encouraging healthy lifestyles, and enhancing urban greenery.

Risk of stroke admission after long-term exposure to PM1: Evidence from a large cohort in South China.

BACKGROUND: Limited attention has been paid to the health effects of long-term PM1 exposure on stroke admission. Current investigations exploring the long-term PM exposure effect are largely based on observational studies, and PM generally is not allocated randomly to participants. Using traditional regression models might confuse messaging and hinder policy recommendations for pollution control and disease prevention policies. METHODS: We conducted a cohort study among 36,271 adults from one of the largest cities in China in 2015 and followed up through 2020. Hazard ratios of stroke admissions following long-term PM1 exposure were estimated via a causal inference approach, marginal structural time-varying Cox proportional hazard model, accounting for multiple confounders. Additionally, several sensitivity analyses and impact modification analyses were carried out. RESULTS AND DISCUSSION: Associations with 1 µg/m3 increase in long-term PM1 were identified for total (HR, 1.079; 95 %CI, 1.012-1.151) and ischemic stroke admissions (HR, 1.092; 95 %CI, 1.018-1.171). The harmful associations varied with exposure duration, initially increasing and then decreasing. The 2-3 years cumulative exposure was associated with a 3.3-5.4 % raised risk for total stroke. For every 1 µg/m³ increase in long-term PM1 exposure, females exhibited a higher risk of both total and ischemic stroke (13 % and 16 %) than men (4 % and 5 %). Low-exposure individuals (whose annual PM1 concentrations were under the third quartile among the annual concentrations for all the participants) exhibited greater sensitivity to PM1 effects (total stroke: 1.079 vs. 1.107; ischemic stroke: 1.092 vs. 1.116). The results underline the importance of safeguarding low-exposed people in highly polluted areas and suggest that long-term PM1 exposure may increase stroke admission risk, warranting attention to vulnerable groups.

How long-term PM exposure may affect all-site cancer mortality: Evidence from a large cohort in southern China.

BACKGROUND: Evidence of a potential causal link between long-term exposure to particulate matter (PM) and all-site cancer mortality from large population cohorts remained limited and suffered from residual confounding issues with traditional statistical methods. AIMS: We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods. METHODS: We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality. RESULTS: With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results. CONCLUSION: This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.

Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China.

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 µg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 µg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.

PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting clinical pregnancy outcomes from intrauterine insemination (IUI) and identifying significant factors affecting IUI pregnancy in a large Chinese population. METHODS: RESULTS: A total of 11 variables, including eight from female (age, body mass index, duration of infertility, prior miscarriage, and spontaneous abortion), hormone levels (anti-Müllerian hormone, follicle-stimulating hormone, luteinizing hormone), and three from male (smoking, semen volume, and sperm concentration), were identified as the significant variables associated with IUI clinical pregnancy in our Chinese dataset. The RF-based prediction model presents an area under the receiver operating characteristic curve (AUC) of 0.716 (95% confidence interval, 0.6914-0.7406), an accuracy rate of 0.6081, a sensitivity rate of 0.7113, and a specificity rate of 0.505. Importance analysis indicated that semen volume was the most vital variable in predicting IUI clinical pregnancy. CONCLUSIONS: The machine learning-based IUI clinical pregnancy prediction model showed a promising predictive efficacy that could provide a potent tool to guide selecting targeted infertile couples beneficial from IUI treatment, and also identify which parameters are most relevant in IUI clinical pregnancy.

The association between outdoor light at night exposure and adult obesity in Northeastern China.

Previous studies have linked exposure to light at night (LAN) with various health outcomes, but evidence is limited for the LAN-obesity association. Thestudy analysed data from 24,845 participants of the 33 Communities Chinese Health Study and obesity (BMI ≥28 kg/m2) was defined according to the Working Group on Obesity in China. The Global Radiance Calibrated Nighttime Lights data were used to estimate participants' LAN exposure. The mixed-effect regression models examined the LAN-BMI and LAN-obesity association. We found that higher LAN exposure was significantly associated with greater BMI and higher risk of obesity. Changes of BMI and the odds ratios (ORs) of obesity and 95% confidence intervals (CIs) for 2nd, 3rd, and 4th against the 1st quartile of LAN exposure were 0.363 (0.208, 0.519), 0.364 (0.211, 0.516) and 0.217 (0.051, 0.383); 1.228 (1.099, 1.371), 1.356 (1.196, 1.538) and 1.269 (1.124, 1.433), respectively. Age and regular exercise showed significant modification effects on the LAN-obesity association.

Associations Between Ambient Extreme Heat Exposure and Emergency Department Visits Related to Kidney Disease.

RATIONALE & OBJECTIVE: Extreme heat exposure is associated with multiple diseases. However, our current understanding of the specific impact of extreme heat exposure on kidney disease is limited. STUDY DESIGN: Case-crossover study. SETTING & PARTICIPANTS: 1,114,322 emergency department (ED) visits with a principal diagnosis of kidney disease were identified in New York state, 2005-2013. EXPOSURE: Extreme heat exposure was defined as when the daily temperature exceeded the 90th percentile temperature of that month during the study period in the county. OUTCOME: ED visits with a principal diagnosis of kidney disease and its subtypes (ICD-9 [International Classification of Diseases, Ninth Revision] codes 580-599, 788). ANALYTICAL APPROACH: Extreme heat exposure on the ED visit days was compared with extreme heat exposure on control days using a conditional logistic regression model, controlling for humidity, air pollutants, and holidays. The excess risk of kidney disease was calculated for a week (lag days 0-6) after extreme heat exposure during the warm season (May through September). We also stratified our estimates by sociodemographic characteristics. RESULTS: Extreme heat exposure was associated with a 1.7% (lag day 0) to 3.1% (lag day 2) higher risk of ED visits related to kidney disease; this association was stronger with a greater number of extreme heat exposure days in the previous week. The association with extreme heat exposure lasted for an entire week and was stronger in the transitional months (ie, May and September; excess rates ranged from 1.8% to 5.1%) rather than the summer months (June through August; excess rates ranged from 1.5% to 2.7%). The strength of association was greater among those with ED visits related to acute kidney injury, kidney stones, and urinary tract infections. Age and sex may modify the association between extreme heat exposure and ED visits. LIMITATIONS: Individual exposure to heat-how long people were outside or whether they had access to air conditioning-was unknown. CONCLUSIONS: Extreme heat exposure was significantly associated with a dose-dependent greater risk of ED visits for kidney disease.

Potential Gains in Health-Adjusted Life Expectancy by Reducing Burden of Noncommunicable Diseases in 188 Countries: A Population-Based Study.

OBJECTIVES: This article quantifies the potential gains in health-adjusted life expectancy for people aged 30 to 70 years (HALE[30-70]) by examining the reductions in disability in addition to premature mortality from noncommunicable diseases (NCDs). METHODS: We extracted data from the Global Burden of Disease Study 2019 for 4 major NCDs (cancers, cardiovascular diseases, chronic respiratory diseases, and diabetes mellitus) in 188 countries from 2010 to 2019. Estimates of the potential gains in HALE[30-70] were based on a counterfactual analysis involving 3 alternative future scenarios: (1) achieve Sustainable Development Goals target 3.4 but do not make any progress on disability reduction, (2) achieve Sustainable Development Goals target 3.4 and eliminate NCD-related disability, and (3) eliminate all NCD-related mortality and disability. RESULTS: In all scenarios, the high-income group has the greatest potential gains in HALE[30-70], above the global average. For all specific causes, potential gains in HALE[30-70] decrease as income levels fall. Across these 3 scenarios, the potential gains in HALE[30-70] globally of reducing premature mortality for 4 major NCDs are 3.13 years, 4.53 years, and 7.32 years, respectively. In scenario A, all income groups have the greatest potential gains in HALE[30-70] from diabetes and chronic respiratory diseases. In scenarios B and C, the high-income group has the greatest potential gains in HALE[30-70] from cancer intervention, and the other income groups have the greatest potential gains in HALE[30-70] from cardiovascular diseases intervention. CONCLUSION: Reducing premature death and disability from 4 major NCDs at once and attaching equal importance to each lead to a sizable improvement in HALE[30-70].

Impact of heat on all-cause and cause-specific mortality: A multi-city study in Texas.

BACKGROUND: Studies on the health effects of heat are particularly limited in Texas, a U.S. state in the top 10 highest number of annual heat-related deaths per capita from 2018 to 2020. This study assessed the effects of heat on all-cause and cause-specific mortality in 12 metropolitan statistical areas (MSAs) across Texas from 1990 to 2011. METHODS: First, we determined the heat thresholds for each MSA above which the relation between temperature and mortality is linear. We then conducted a distributed lag non-linear model for each MSA, followed by a random effects meta-analysis to estimate the pooled effects for all MSAs. We repeated this process for each mortality cause and age group to achieve the effect estimates. RESULTS: We found a 1 °C temperature increase above the heat threshold is associated with an increase in the relative risk of all-cause mortality of 0.60% (95%CI [0.39%, 0.82%]) and 1.10% (95%CI [0.65%, 1.56%]) for adults older than 75. For each MSA, the relative risk of mortality for a 1 °C temperature increase above the heat threshold ranges from 0.10% (95%CI [0.09%, 0.10%]) to 1.29% (95%CI [1.26%, 1.32%]). Moreover, elevated temperatures showed a slight decrease in cardiovascular mortality (0.37%, 95%CI [-0.35%, 1.09%]) and respiratory disease (1.97%, 95%CI [-0.11%, 4.08%]), however this effect was not considered statistically significant.. CONCLUSION: Our study found that high temperatures can significantly impact all-cause mortality in Texas, and effect estimates differ by MSA, age group, and cause of death. Our findings generate critical information on the impact of heat on mortality in Texas, providing insights for policymakers on resource allocation and strategic intervention to reduce heat-related health effects.

Potential impact of ambient temperature on maternal blood pressure and hypertensive disorders of pregnancy: A nationwide multicenter study based on the China birth cohort.

Limited evidence exists regarding the association between ambient temperature and blood pressure (BP) level of pregnant women. To investigate the associations of ambient temperature with maternal BP and hypertensive disorders of pregnancy (HDP), we studied 105,063 participants in 38 centers of 17 provinces from November 2017 to December 2021. BP was measured with standardized automated digital sphygmomanometers. Ambient temperature was classified into five classes as very hot, moderate hot, mild, moderate cold, and very cold. Generalized linear mixed models were used to investigate the ambient temperature-BP/HDP associations, controlling for multiple covariates. No significant associations of first-trimester ambient temperature with maternal BP and HDP prevalence were observed. Compared with mild temperature, second-trimester very cold and second-trimester moderate cold were statistically associated with the increase of 1.239 mmHg (95% CI: 0.908, 1.569) and 0.428 mmHg (95% CI: 0.099, 0.757) for second-trimester systolic blood pressure (SBP), respectively. Similar trends were also observed in the association between second-trimester cold exposure and second-trimester diastolic blood pressure (DBP), in the association between second-trimester cold exposure and third-trimester SBP/DBP as well as in the association between third-trimester cold exposure and third-trimester SBP/DBP although some estimates were not statistically significant. Furthermore, in the second and third trimester, very cold [second trimester: adjusted odds ratio (aOR) = 1.298; third trimester: aOR = 1.236) and moderate cold (second trimester: aOR = 1.208; third trimester: aOR = 1.146) exposures also increased the odds of HDP, and these associations were stronger among participants aged ≥35 years or from North China. The second and third trimesters are the critical exposure windows for ambient temperature exposure-BP/HDP associations. During this period, exposure to cold ambient temperature was associated with elevated BP as well as increased HDP prevalence among most Chinese pregnant women, those aged ≥35 years or from North China being more vulnerable.

Association between long-term ambient ozone exposure and attention-deficit/hyperactivity disorder symptoms among Chinese children.

BACKGROUND: Although ozone exposure has neurological toxicity, it remains unclear whether it was associated with an increased risk of attention-deficit/hyperactivity disorders (ADHD) among childhood. METHODS: We matched the four-year average ozone concentration with questionnaire data for 35,103 children aged 3-12 years from seven cities in Liaoning, China, 2012-2013. Using mixed-effect logistic regression models, we assessed the association of ozone concentration with multiple ADHD indicators using the Conners Abbreviated Symptom Questionnaire (C-ASQ), including explicit attention-deficit/hyperactivity symptoms (ADHD; score ≥15), attention-deficit/hyperactivity disorder tendencies (ADHD-T; 11 ≤ score ≤14), and attention-deficit/hyperactivity problems (ADHP; score ≥11). Results were also stratified by sociodemongraphics. RESULTS: After adjusting for covariates, we found that each interquartile range (IQR) increase in ozone concentration was associated with an increased risk of ADHD, ADHD-T, and ADHP (P < 0.001) with an odds ratio of 1.12 (95% confidence interval, 1.04-1.21), 1.08 (1.03-1.13), and 1.09 (1.05-1.14), respectively. Additionally, we found greater effect estimates in children who reported longer exercise time (vs those with limited exercise time) with odds ratio of 1.18 (1.07-1.31) vs 1.06 (0.96-1.17) for ADHD, 1.13 (1.06-1.21) vs 1.03 (0.96-1.10) for ADHD-T, and 1.15 (1.08-1.21) vs 1.04 (0.98-1.10) for ADHP. Non-breastfed children were also shown to be more vulnerable to ADHD with an odds ratio of 1.22 (1.09-1.36) compared with 1.06 (0.96-1.16) among the rest. CONCLUSIONS: Long-term ozone exposure may be associated with increased ADHD among children. Additional studies are needed to validate our findings and support policies and interventions to address this growing public health concern.

Is COPD mortality in South China causally linked to the long-term PM1 exposure? Evidence from a large community-based cohort.

BACKGROUND: Long-term ambient particulate matter (PM) exposure has been found associated with chronic obstructive pulmonary disease (COPD) mortality in an increasing body of research. However, limited evidence was available on the potential causal links between PM1 and COPD mortality, especially in highly exposed areas. OBJECTIVES: To examine the COPD mortality risk following long-term ambient PM1 exposure in south China. METHODS: The cohort included 580,757 participants recruited during 2009-2015. Satellite-based annual concentrations of PM1 were estimated at a spatial resolution of 1 km × 1 km and assigned to each participant based on their residential addresses. We analyzed the potential causal links between time-varying PM1 exposure and COPD mortality using marginal structural cox models within causal frameworks. Stratified analyses were also performed to identify the potential susceptible groups. RESULTS: The annual average PM1 concentration continuously decreased over time. After adjusting for confounders, each 1 µg/m3 increase in PM1 concentration corresponded to an 8.1 % (95% confidence interval: 6.4-9.9 %) increment in the risk of COPD mortality. The impact of PM1 was more pronounced among the elderly and those with low exercise frequency, with a 1.9-6.9 % higher risk than their counterparts. We further observed a 0.1-9.7 % greater risk among those who lived in lower greenness settings. Additionally, we observed higher effect estimates in participants with long-term low PM1 exposure compared to the general population. CONCLUSIONS: COPD mortality risk significantly increased following long term ambient PM1 exposure, particularly among groups with certain demographics or long-term low exposure.

Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China.

BACKGROUND: Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited. AIMS: We examined the potential causal links between PM exposure and the CVD mortality in South China. METHODS: 580,757 participants were recruited during 2009-2015 and followed up through 2020. Satellite-based annual concentrations of PM2.5, PM10, and PMcoarse (i.e., PM10 - PM2.5) at 1 km2 spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality. RESULTS: For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 µg/m3 increase in the annual average concentration of PM2.5, PM10, and PMcoarse were 1.033 (1.028-1.037), 1.028 (1.024-1.032), and 1.022 (1.012-1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM2.5 and PM10. Significant association between PMcoarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM10 concentrations below 70 µg/m3 were more vulnerable to PM2.5-, PM10- and PMcoarse-CVD mortality risks. CONCLUSION: This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

COVID-19 Symptoms and Deaths among Healthcare Workers, United States.

We evaluated whether demographics and COVID-19 symptoms predicted COVID-19 deaths among healthcare workers (HCWs) in the United States by comparing COVID-19 deaths in HCWs with 3 control groups (HCW nondeaths, non-HCW deaths, and non-HCW nondeaths) using a case-control design. We obtained patient-level data of 33 variables reported during January 1, 2020-October 12, 2021, in all US states. We used logistic regression analysis while controlling for confounders. We found that persons who were >50 years of age, male, Black, or Asian experienced significantly more deaths than matched controls. In addition, HCWs who died had higher risks for the most severe clinical indicators. We also found that the most indicative symptoms were preexisting medical conditions, shortness of breath, fever, cough, and gastrointestinal symptoms. In summary, minority, male, and older HCWs had greater risk for COVID-19 death. Severe clinical indicators and specific symptoms may predict COVID-19-related deaths among HCWs.

Role of m6A RNA methylation in the development of hepatitis B virus-associated hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the most common liver malignancy that can be developed from hepatitis B and cirrhosis. Many pathophysiological alterations, including hepatitis B virus (HBV) DNA integration, oxidative stress, cytokine release, telomerase homeostasis, mitochondrial damage, epigenetic modification, and tumor microenvironment, are involved in the biological process from hepatitis B to cirrhosis and HCC. N6-methyladenosine (m6A), as an epitranscriptomic modification of RNAs, can regulate the stability, splicing, degradation, transcription, and translation of downstream target RNAs in HBV and liver cancer cells. m6A regulators (writers, erasers, and readers) play an important role in the pathogenesis of HBV-associated HCC by regulating cell proliferation, apoptosis, migration, autophagy, differentiation, inflammation, angiogenesis, and tumor microenvironment. This review summarizes the current progress of m6A methylation in the molecular mechanisms, biological functions, and potential clinical implications of HBV-associated HCC.

Measuring students' exposure to particulate matter (PM) pollution across microenvironments and seasons using personal air monitors.

Particulate matter (PM) pollution is a significant concern in public health, yet children's exposure is not adequately characterized. This study evaluated PM exposures among primary school-aged children in NYS across different microenvironments. This study helps fill existing knowledge gaps by characterizing PM exposure among this population across seasons and microenvironments. Sixty students were recruited from randomly selected public primary schools representing various socioeconomic statuses. Individual real-time exposure to PM2.5 was measured continuously using AirBeam personal monitors for 48 h. Children were consistently exposed to higher PM2.5 concentrations in the fall (median: fall = 2.84, spring = 2.31, winter = 0.90 µg/m3). At school, 2.19% of PM2.5 measurements exceeded the EPA annual fine particle standard, 12 µg/m3 (winter = 7.38%, fall = 2.39%, spring = 1.38%). In classrooms, PM1-4 concentrations were higher in spring and overnight, while PM7-10 concentrations were higher in fall and school hours. At home, 37.2% of fall measurements exceeded EPA standards (spring = 10.39%, winter = 4.37%). Overall, PM2.5 levels in classrooms and during transportation never rose above the EPA standard for any significant length of time. However, PM2.5 levels routinely exceeded these standards at home, in the fall, and the evening. More extensive studies are needed to confirm these results.

Impact of cumulative cisplatin dose in childhood nasopharyngeal carcinoma based on neoadjuvant chemotherapy response in the intensity-modulated radiotherapy era: a real-world study.

BACKGROUND: We aimed to comprehensively investigate the optimal cumulative cisplatin dose during concurrent chemoradiotherapy (CC-CCD) for locoregionally advanced nasopharyngeal carcinoma (CA-LANPC) with different tumor responses after neoadjuvant chemotherapy (NAC). METHODS: Patients with CA-LANPC who underwent NAC followed by cisplatin-based concurrent chemoradiotherapy were retrospectively analyzed. Evaluation of tumor response in patients was conducted by Response Evaluation Criteria for Solid Tumor (RECIST) 1.1 after two to four cycles NAC. Multivariate Cox proportional hazards models were used for prognosis. Recursive partitioning analysis (RPA) was conducted to classify participates and predict disease-free survival (DFS). RESULTS: One hundred and thirty-two patients with favorable response after NAC were included. The median CC-CCD was 163 mg/m2 (IQR, 145-194 mg/m2), and 160 mg/m2 was selected as the cutoff point to group patients into low and high CC-CCD groups (< 160 vs. ≥ 160 mg/m2). There was significant improvement in 5-year DFS (91.2% vs. 72.6%; P = 0.003) for patients receiving high CC-CCD compared to those receiving low CC-CCD. Multivariate analysis revealed that CC-CCD, T stage, and Epstein-Barr virus (EBV) DNA were independent prognostic factors for DFS (P < 0.05 for all). Patients were further categorized into two prognostic groups by RPA: the low-risk group (T1-3 disease with regardless of EBV DNA, and T4 disease with EBV DNA < 4000 copy/mL), and the high-risk group (T4 disease with EBV DNA ≥ 4000 copy/mL). Significant 5-year DFS improvement was observed for the high-risk group (P = 0.004) with high CC-CCD. However, DFS improvement was relatively insignificant in the low-risk group (P = 0.073). CONCLUSIONS: CC-CCD was a positive prognostic factor for responders after NAC in CA-LANPC. Furthermore, CC-CCD ≥ 160 mg/m2 could significantly improve DFS in the high-risk group with CA-LANPC, but the benefit of high CC-CCD in the low-risk group needs further study.