Supply chain decision based on green investment subsidy and risk aversion.

Considering the risk aversion characteristics of supply chain members, how to effectively design the government subsidy strategy and green supply chain strategy is a realistic and urgent issue. Regarding this, we optimize and compare four three-stage Stackelberg game models between government and a two-echelon green supply chain, namely both manufacturer and retailer risk neutral (BN), manufacturer risk aversion while retailer risk neutral (MA), retailer risk aversion while manufacturer risk neutral (RA) and both manufacturer and retailer risk aversion (BA). The government as the leader decides the subsidy rate of green input cost with the goal of maximizing social welfare; the manufacturer as the first follower makes decisions on product greenness and wholesale price to maximize its own interests; and the retailer as the second follower determines retail prices to maximize its own interests. Employing mathematical reasoning and numerical simulation investigate thoroughly the effects of the government subsidies and the members' risk aversion. Results indicate that an appropriate government subsidy investment has a positive effect on optimal decisions and related benefits. Risk aversion is in favor of improvement of product greenness and social welfare while reduction of retail price. With the increase of manufacturer risk aversion, green subsidy investment rate and retailer expected revenue increase; on the contrary, the wholesale price and manufacturer expected revenue decrease. With the increase of retailer risk aversion, the wholesale price and manufacturer expected revenue increase, while green subsidy investment rate and retailer expected revenue decrease. In the model of BN, product greenness and social welfare are the lowest, while retail price is the highest. BA is opposite to BN. In the model of RA, green subsidy investment rate and retailer expected revenue the lowest, while wholesale price and manufacturer expected revenue the highest. RA is opposite to MA. The government should formulate appropriate subsidy policies to encourage manufacturers to produce green products and raise consumers' green awareness. Enterprises should control their own risk aversion and assess the risk aversion of the other party reasonably.

National Cohort Study of Long-Term Exposure to PM2.5 Components and Mortality in Medicare American Older Adults.

There is increasing evidence linking long-term fine particulate matter (PM2.5) exposure to negative health effects. However, the relative influence of each component of PM2.5 on health risk is poorly understood. In a cohort study in the contiguous United States between 2000 and 2017, we examined the effect of long-term exposure to PM2.5 main components and all-cause mortality in older adults who had to be at least 65 years old and enrolled in Medicare. We estimated the yearly mean concentrations of six key PM2.5 compounds, including black carbon (BC), organic matter (OM), soil dust (DUST), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+), using two independently sourced well-validated prediction models. We applied Cox proportional hazard models to evaluate the hazard ratios for mortality and penalized splines for assessing potential nonlinear concentration-response associations. Results suggested that increased exposure to PM2.5 mass and its six main constituents were significantly linked to elevated all-cause mortality. All components showed linear concentration-response relationships in the low exposure concentration ranges. Our research indicates that long-term exposure to PM2.5 mass and its essential compounds are strongly connected to increased mortality risk. Reductions of fossil fuel burning may yield significant air quality and public health benefit.

Disparities in ambient nitrogen dioxide pollution in the United States.

Average ambient concentrations of nitrogen dioxide (NO2), an important air pollutant, have declined in the United States since the enactment of the Clean Air Act. Despite evidence that NO2 disproportionately affects racial/ethnic minority groups, it remains unclear what drives the exposure disparities and how they have changed over time. Here, we provide evidence by integrating high-resolution (1 km × 1 km) ground-level NO2 estimates, sociodemographic information, and source-specific emission intensity and location for 217,740 block groups across the contiguous United States from 2000 to 2016. We show that racial/ethnic minorities are disproportionately exposed to higher levels of NO2 pollution compared with Whites across the United States and within major metropolitan areas. These inequities persisted over time and have worsened in many cases, despite a significant decrease in the national average NO2 concentration over the 17-y study period. Overall, traffic contributes the largest fraction of NO2 disparity. Contributions of other emission sources to exposure disparities vary by location. Our analyses offer insights into policies aimed at reducing air pollution exposure disparities among races/ethnicities and locations.

Incident dementia and long-term exposure to constituents of fine particle air pollution: A national cohort study in the United States.

Growing evidence suggests that fine particulate matter (PM2.5) likely increases the risks of dementia, yet little is known about the relative contributions of different constituents. Here, we conducted a nationwide population-based cohort study (2000 to 2017) by integrating the Medicare Chronic Conditions Warehouse database and two independently sourced datasets of high-resolution PM2.5 major chemical composition, including black carbon (BC), organic matter (OM), nitrate (NO3-), sulfate (SO42-), ammonium (NH4+), and soil dust (DUST). To investigate the impact of long-term exposure to PM2.5 constituents on incident all-cause dementia and Alzheimer's disease (AD), hazard ratios for dementia and AD were estimated using Cox proportional hazards models, and penalized splines were used to evaluate potential nonlinear concentration-response (C-R) relationships. Results using two exposure datasets consistently indicated higher rates of incident dementia and AD for an increased exposure to PM2.5 and its major constituents. An interquartile range increase in PM2.5 mass was associated with a 6 to 7% increase in dementia incidence and a 9% increase in AD incidence. For different PM2.5 constituents, associations remained significant for BC, OM, SO42-, and NH4+ for both end points (even after adjustments of other constituents), among which BC and SO42- showed the strongest associations. All constituents had largely linear C-R relationships in the low exposure range, but most tailed off at higher exposure concentrations. Our findings suggest that long-term exposure to PM2.5 is significantly associated with higher rates of incident dementia and AD and that SO42-, BC, and OM related to traffic and fossil fuel combustion might drive the observed associations.

Ambient volatile organic compounds in urban and industrial regions in Beijing: Characteristics, source apportionment, secondary transformation and health risk assessment.

Field measurements of volatile organic compounds (VOCs) were conducted simultaneously at an urban site and one industrial park site in Beijing in summer. The VOCs concentrations were 94.3 ± 157.8 ppbv and 20.7 ± 8.9 ppbv for industrial and urban sites, respectively. Alkanes and aromatics were the major contributors to VOCs in industrial site, while oxygenated volatile organic compounds (OVOCs) contributed most in urban site. The most abundant VOC species were n-pentane and formaldehyde for industrial site and urban site, respectively. The calculated ozone formation potential (OFP) and OH loss rates (LOH) were 621.1 ± 1491.9 ppbv (industrial site), 102.9 ± 37.3 ppbv (urban site), 22.0 ± 39.0 s-1 (industrial site) and 5.3 ± 2.2 s-1 (urban site), respectively. Based on the positive matrix factorization (PMF) model, solvent utilization I (34.1 %), solvent utilization II (27.9 %), mixture combustion source (19.3 %), OVOCs related source (9.6 %) and biogenic source (9.1 %) were identified in the industrial site, while OVOCs related source (27.8 %), vehicle exhaust (22.1 %), solvent utilization (19.3 %), coal combustion (16.0 %) and biogenic source (14.8 %) were identified in the urban site. The results of O3-VOCs-NOx sensitivity indicated that O3 formation were respectively under the VOC-limited and NOx-limited conditions in Beijing urban and industrial regions. Additionally, aromatics accounted remarkable SOA formation ability both in the two sites, and SOA potentials of xylene, toluene and ethylbenzene as the indicator species for the solvent utilization in industrial site were remarkable higher than those obtained in urban regions. The hazard index values in the industrial and urban sites were 1.72 and 3.39, respectively, suggesting a high non-carcinogenic risks to the exposed population. Formaldehyde had the highest carcinogenic risks in the two sites, and the cumulative carcinogenic risks in the industrial site and urban site were 1.95 × 10-5 and 1.21 × 10-5, respectively.

High-Quality Development of Science and Technology Finance and Logistics Industry in the Yangtze River Economic Belt: Coupling Analysis Based on Deep Learning Model.

Using the entropy method, the coupling coordination model, and the Tobit model, the coupling coordination degree of the high-quality development of science and technology finance and the logistics industry in the Yangtze River Economic Belt in China from 2009 to 2020 is measured, and its influencing factors are found. The study found that the overall coupling coordination degree of the Yangtze River Economic Belt has shown a rapid upward trend; the development gap of the interprovincial coupling coordination degree has a narrowing trend. Except for Sichuan Province, the average coupling coordination degree decreases from the downstream to the upstream; the mechanism analysis shows that the coupling effect of the two. There are scale effect, innovation effect, talent effect, and structure effect; the analysis of influencing factors shows that innovation effect and talent effect have the most obvious promoting effect on the coupled and coordinated development of the two. In addition, the upgrading of the industrial structure, the effective driving of science and technology, the improvement of the logistics foundation, and the further development of finance also have a positive effect on it. Finally, according to the conclusions, suggestions are put forward from five aspects: insisting on innovation, talent training, risk prevention, policy orientation, and industrial structure upgrading, so as to realize the further coupling of high-quality development of technology finance and logistics industry.

Low-Concentration Air Pollution and Mortality in American Older Adults: A National Cohort Analysis (2001-2017).

Mounting epidemiological evidence has documented the associations between long-term exposure to multiple air pollutants and increased mortality. There is a pressing need to determine whether risks persist at low concentrations including below current national standards. Air pollution levels have decreased in the United States, and better understanding of the health effects of low-level air pollution is essential for the amendment of National Ambient Air Quality Standards (NAAQS). A nationwide, population-based, open cohort study was conducted to estimate the association between long-term exposure to low-level PM2.5, NO2, O3, and all-cause mortality. The study population included all Medicare enrollees (ages 65 years or older) in the contiguous U.S. from 2001 to 2017. We further defined three low-exposure subcohorts comprised of Medicare enrollees who were always exposed to low-level PM2.5 (annual mean ≤12-µg/m3), NO2 (annual mean ≤53-ppb), and O3 (warm-season mean ≤50-ppb), respectively, over the study period. Of the 68.7-million Medicare enrollees, 33.1% (22.8-million, mean age 75.9 years), 93.8% (64.5-million, mean age 76.2 years), and 65.0% (44.7-million, mean age 75.6 years) were always exposed to low-level annual PM2.5, annual NO2, and warm-season O3 over the study period, respectively. Among the low-exposure cohorts, a 10-µg/m3 increase in PM2.5, 10-ppb increase in NO2, and 10-ppb increase in warm-season O3, were, respectively, associated with an increase in mortality rate ranging between 10 and 13%, 2 and 4%, and 12 and 14% in single-pollutant models, and between 6 and 8%, 1 and 3%, and 9 and 11% in tripollutant models, using three statistical approaches. There was strong evidence of linearity in concentration-response relationships for PM2.5 and NO2 at levels below the current NAAQS, suggesting that no safe threshold exists for health-harmful pollution levels. For O3, the concentration-response relationship shows an increasingly positive association at levels above 40-ppb. In conclusion, exposure to low levels of PM2.5, NO2, and warm-season O3 was associated with an increased risk of all-cause mortality.

Long-term exposure to PM2.5 major components and mortality in the southeastern United States.

BACKGROUND: Long-term exposure to fine particulate matter (PM2.5) mass has been associated with adverse health effects. However, the health effects of PM2.5 components have been less studied. There is a pressing need to better understand the relative contribution of components of PM2.5, which can lay the scientific basis for designing effective policies and targeted interventions. METHODS: We conducted a population-based cohort study, comprising all Medicare enrollees aged 65 or older in the southeastern United States from 2000 to 2016, to explore the associations between long-term exposure to PM2.5 major components and all-cause mortality among the elderly. Based on well-validated prediction models, we estimated ZIP code-level annual mean concentrations for five major PM2.5 components, including black carbon (BC), nitrate (NIT), organic matter (OM), sulfate (SO4), and soil particles. Data were analyzed using Cox proportional hazards models, adjusting for potential confounders. RESULTS: The cohort comprised 13,590,387 Medicare enrollees and a total of 107,191,652 person-years. In single-component models, all five major PM2.5 components were significantly associated with elevated all-cause mortality. The hazard ratios (HR) per interquartile range (IQR) increase in exposure were 1.027 (95% CI: 1.025-1.030), 1.012 (95% CI: 1.010-1.013), 1.018 (95% CI: 1.017-1.020), 1.021 (95% CI: 1.017-1.024), and 1.004 (95% CI: 1.003-1.006) for BC, NIT, OM, SO4, and soil particles, respectively. While the effect estimate of soil component was statistically significant, it is much smaller than those of combustion-related components. CONCLUSION: Our study provides epidemiological evidence that long-term exposure to major PM2.5 components is significantly associated with elevated mortality.

Long-Term Exposure to Low-Level NO2 and Mortality among the Elderly Population in the Southeastern United States.

BACKGROUND: Mounting evidence has shown that long-term exposure to fine particulate matter [PM ≤2.5µm in aerodynamic diameter (PM2.5)] and ozone (O3) can increase mortality. However, the health effects associated with long-term exposure to nitrogen dioxide (NO2) are less clear, in particular the evidence is scarce for NO2 at low levels that are below the current international guidelines. METHODS: We constructed a population-based full cohort comprising all Medicare beneficiaries (aged ≥65, N=13,590,387) in the southeastern United States from 2000 to 2016, and we then further defined the below-guideline cohort that included only those who were always exposed to low-level NO2, that is, with annual means below the current World Health Organization guidelines (i.e., ≤21 ppb). We applied previously estimated spatially and temporally resolved NO2 concentrations and assigned annual means to study participants based on their ZIP code of residence. Cox proportional hazards models were used to examine the association between long-term exposure to low-level NO2 and all-cause mortality, adjusting for potential confounders. RESULTS: About 71.1% of the Medicare beneficiaries in the southeastern United States were always exposed to low-level NO2 over the study period. We observed an association between long-term exposure to low-level NO2 and all-cause mortality, with a hazard ratio (HR)= 1.042 (95% CI: 1.040, 1.045) in single-pollutant models and a HR= 1.047 (95% CI: 1.045, 1.049) in multipollutant models (adjusting for PM2.5 and O3), per 10-ppb increase in annual NO2 concentrations. The penalized spline indicates a linear exposure-response relationship across the entire NO2 exposure range. Medicare enrollees who were White, female, and residing in urban areas were more vulnerable to long-term NO2 exposure. CONCLUSION: Using a large and representative cohort, we provide epidemiological evidence that long-term exposure to NO2, even below the national and global ambient air quality guidelines, was approximately linearly associated with a higher risk of mortality among older adults, independent of PM2.5 and O3 exposure. Improving air quality by reducing NO2 emissions, therefore, may yield significant health benefits. https://doi.org/10.1289/EHP9044.

Multiple Mutation Detection for Risk Assessment in Patients with Breast Cancer by Using Next-Generation Sequencing.

OBJECTIVE: Breast cancer is recognized as the most common cause of malignancy and cancer death worldwide; however, mutations in the cancer-related BRCA genes are detected in only 2-3% of patients with breast cancer. Because next-generation sequencing technology allows concurrent sequencing of numerous target genes, diverse cancer-susceptibility genes are now being evaluated, although their significance in clinical practice remains unclear. METHODS: In this study, we developed a sequencing panel containing the genes BRCA1, BRCA2, TP53, PIK3CA, ERBB2 (Her2), and PTEN, which are all associated with cancer risk in patients, and we enrolled 60 patients with breast cancer. RESULTS: Germline mutations were found to be carried by nine patients (15%): 3 in BRCA1, 5 in BRCA2, and 1 in TP53. The patients harboring these mutations are considered to face a high risk of developing malignant tumors, and cancer screening is thus recommended for the patients. CONCLUSION: This study demonstrates the feasibility of using Ion Torrent sequencing technology for reliably detecting gene mutations in clinical practice for guiding individualized drug therapy or combination therapies for breast cancer.

Tracking pesticide exposure to operating workers for risk assessment in seed coating with tebuconazole and carbofuran.

BACKGROUND: Coating seed with pesticides is an effective way to control plant pests, however, factory-based coating processes may carry a potential risk to operational workers of chemical exposure. To study the risk, carbofuran and tebuconazole were used to coat corn seed and their subsequent distribution on the bodies of workers was measured at manufacturers XFS and LS (Shanxi, China). Clothing was collected from workers during operations and analyzed using high-performance liquid chromatography. RESULTS: At XFS, dermal exposure to carbofuran was 4.83, 3.31 and 1.48 mg kg-1 , and exposure to tebuconazole was 6.88, 5.16 and 1.72 mg kg-1 for coating, packing and transport workers, respectively. At LS, dermal exposure to carbofuran was 2.32, 0.46 and 0.55 mg kg-1 , and exposure to tebuconazole was 1.69, 0.46 and 0.70 mg kg-1 , for coating, packing and transport workers, respectively. The level of pesticide exposure was significantly higher for seed-coating workers than for packing and transport workers. The main area of exposure was the hands for all workers and the lower limbs for packers; exposure was relatively uniform for pesticide handlers. Occupational risk was assessed based on margin of exposure (MOE). In seed-coating, the MOE was greater than 100 for tebuconazole, indicating no potential risk, but ranged from 0.25 to 2.88 for carbofuran, indicating the risk of a health impact. CONCLUSION: The level of exposure varied depending on type of operation undertaken and body parts of workers' body, but the risk of a health impact was highly associated with pesticide toxicity. This provides a guideline for workers in pesticide manufacturing to ensure safe operation of the seed-coating process. © 2021 Society of Chemical Industry.

Long-term effects of PM2·5 on neurological disorders in the American Medicare population: a longitudinal cohort study.

BACKGROUND: Accumulating evidence links fine particulate matter (PM2·5) to premature mortality, cardiovascular disease, and respiratory disease. However, less is known about the influence of PM2·5 on neurological disorders. We aimed to investigate the effect of long-term PM2·5 exposure on development of Parkinson's disease or Alzheimer's disease and related dementias. METHODS: We did a longitudinal cohort study in which we constructed a population-based nationwide open cohort including all fee-for-service Medicare beneficiaries (aged ≥65 years) in the contiguous United States (2000-16) with no exclusions. We assigned PM2·5 postal code (ie, ZIP code) concentrations based on mean annual predictions from a high-resolution model. To accommodate our very large dataset, we applied Cox-equivalent Poisson models with parallel computing to estimate hazard ratios (HRs) for first hospital admission for Parkinson's disease or Alzheimer's disease and related dementias, adjusting for potential confounders in the health models. FINDINGS: Between Jan 1, 2000, and Dec 31, 2016, of 63 038 019 individuals who were aged 65 years or older during the study period, we identified 1·0 million cases of Parkinson's disease and 3·4 million cases of Alzheimer's disease and related dementias based on primary and secondary diagnosis billing codes. For each 5 µg/m3 increase in annual PM2·5 concentrations, the HR was 1·13 (95% CI 1·12-1·14) for first hospital admission for Parkinson's disease and 1·13 (1·12-1·14) for first hospital admission for Alzheimer's disease and related dementias. For both outcomes, there was strong evidence of linearity at PM2·5 concentrations less than 16 µg/m3 (95th percentile of the PM2·5 distribution), followed by a plateaued association with increasingly larger confidence bands. INTERPRETATION: We provide evidence that exposure to annual mean PM2·5 in the USA is significantly associated with an increased hazard of first hospital admission with Parkinson's disease and Alzheimer's disease and related dementias. For the ageing American population, improving air quality to reduce PM2·5 concentrations to less than current national standards could yield substantial health benefits by reducing the burden of neurological disorders. FUNDING: The Health Effects Institute, The National Institute of Environmental Health Sciences, The National Institute on Aging, and the HERCULES Center.

HONO Budget and Its Role in Nitrate Formation in the Rural North China Plain.

Nitrous acid (HONO) is a major precursor of tropospheric hydroxyl radical (OH) that accelerates the formation of secondary pollutants. The HONO sources, however, are not well understood, especially in polluted areas. Based on a comprehensive winter field campaign conducted at a rural site of the North China Plain, a box model (MCM v3.3.1) was used to simulate the daytime HONO budget and nitrate formation. We found that HONO photolysis acted as the dominant source for primary OH with a contribution of more than 92%. The observed daytime HONO could be well explained by the known sources in the model. The heterogeneous conversion of NO2 on ground surfaces and the homogeneous reaction of NO with OH were the dominant HONO sources with contributions of more than 36 and 34% to daytime HONO, respectively. The contribution from the photolysis of particle nitrate and the reactions of NO2 on aerosol surfaces was found to be negligible in clean periods (2%) and slightly higher during polluted periods (8%). The relatively high OH levels due to fast HONO photolysis at the rural site remarkably accelerated gas-phase reactions, resulting in the fast formation of nitrate as well as other secondary pollutants in the daytime.

Allocation of Flood Drainage Rights Based on the PSR Model and Pythagoras Fuzzy TOPSIS Method.

To minimize losses caused by flooding of areas in a river basin, flood risk management may sacrifice the interests of some areas. Because of regional differences in natural and urban conditions, rankings of the urgencies of flood drainage rights allocations in different regions are of great practical significance to the realization of optimal allocations and reduction of damages. Based on the "pressure-state-response" (PSR) framework, this study designed an index system of flood drainage rights allocations in river basins for the comprehensive consideration of the different attributes of regional societies, environments, and technologies, as well as the differences in the quality of technical management and in the levels of social and economic development. A Pythagoras fuzzy TOPSIS method was used to evaluate the urgencies and determine the management of allocations in different areas. Eight cities in Jiangsu Province in the Huai River Basin were selected as the research objects. The results showed that pressure factors played dominant roles in the degrees of urgency. Among the cities, Nantong had the highest degree, followed by Taizhou, whereas Lianyungang had the lowest. The degrees in the central region of Jiangsu were higher than in the northern region.

Use of Fuzzy Analytic Hierarchy Process and Environmental Gini Coefficient for Allocation of Regional Flood Drainage Rights.

To solve the flood drainage conflict among different regions of the water basin when the flood occurs, it is of great significance to study the allocation of flood drainage rights. The allocation of flood drainage rights requires flood management departments to consider the influences of socioeconomic differences among different regions on flood control operations to realize sustainable development. Under the pattern of the total amount allocation of "watershed-administrative regions", the evaluation index system of flood drainage rights allocation incorporated four aspects: natural conditions, level of social development, level of economic development, and technology and management. The fuzzy analytic hierarchy process (FAHP) was used to calculate the weight coefficient of each allocation index and the initial distribution's proportion of the total amount in each region. Land area, population, gross domestic product (GDP), and sewage treatment capacity were selected as the evaluation indexes of the environmental Gini coefficient, and the environmental Gini coefficient method was used to evaluate and adjust the initial allocation of each region. Taking the allocation of flood drainage rights in the Taihu Basin as a case study, the final allocation results were obtained after initial allocation and feedback optimization. By evaluating the environmental Gini coefficient of each evaluation index, it is concluded that the final allocation could meet the requirements of fair allocation in each administrative region and be effectively implemented. Optimal allocation of the flood drainage rights in the Taihu Basin can contribute to overall flood control management, the reduction of flood disasters, and the stable development of society in the basin.

Extreme temperature and mortality: evidence from China.

The frequency, intensity, and duration of extreme temperature events are expected to rise in the future and increase the related health risks of human beings. Using a novel, nationwide dataset that links extreme temperature and mortality, we estimated the short-term and long-term effects of extreme temperature on mortality in China during 2002-2013. Both extreme hot and extreme cold had immediate and long-term effects on all-cause mortality. Annual deaths per 100,000 people due to extreme hot and cold in the long term were considerably larger compared to the short term. The change in cold spell duration indicator exhibited the greatest effects on annual deaths per 100,000 people among a set of extreme weather indicators. Furthermore, cities with low economic development levels were more vulnerable to extreme temperature, compared to cities with high economic development levels. Our results offer important policy implications for developing a regional-specific extreme weather plan to handle extreme temperature events in China.

Dynamic Quantitative Assessment of Motor Axon Sprouting after Direct Facial-Hypoglossal End-To-Side Neurorrhaphy in Rats.

BACKGROUND: End-to-side (ETS) neurorrhaphy is a promising procedure for peripheral nerve repair, yet controversies regarding the efficacy of this repair in facial nerve anastomosis for facial paralysis still exist. MATERIALS AND METHODS: Thirty rats were divided into three groups: intact control group, direct facial-hypoglossal ETS neurorrhaphy, and end-to-end (ETE) neurorrhaphy. Nerve regeneration was assessed with vibrissae motor performance, electrophysiological tests, retrograde labeling, and histomorphological analysis at 4 and 8 months postoperatively. RESULTS: Both ETS and ETE neurorrhaphies resulted in axonal regeneration and functional recovery of the recipient nerve but did not reach the level of intact controls. Significantly higher numbers of myelinated axons and labeled neurons giving regenerating fibers were found in group ETE compared with group ETS at both time points, consistent with the functional and electrophysiological recovery. Group ETS showed significantly smaller fiber diameter and thinner myelin thickness than group ETE at 4 months, but the difference became nonsignificant at 8 months. ETS neurorrhaphy had a very slight effect on the donor nerve, as determined electrophysiologically and histomorphologically. Sparsely distributed double-labeled neurons and relatively large amounts of single-labeled neurons contributing to reinnervation were found through double retrograde neuronal labeling in group ETS. Further quantitative analysis of the percentage of double-labeled neurons showed a pronounced tendency to decline from 19.8% at 4 months to 6.0% at 8 months postoperatively. CONCLUSION: Successful reinnervation after ETS neurorrhaphy could be achieved through both collateral sprouting and terminal sprouting, with the latter seeming to be the principal origin of motor nerve sprouting.

Doubly Robust Additive Hazards Models to Estimate Effects of a Continuous Exposure on Survival.

BACKGROUND: The effect of an exposure on survival can be biased when the regression model is misspecified. Hazard difference is easier to use in risk assessment than hazard ratio and has a clearer interpretation in the assessment of effect modifications. METHODS: We proposed two doubly robust additive hazards models to estimate the causal hazard difference of a continuous exposure on survival. The first model is an inverse probability-weighted additive hazards regression. The second model is an extension of the doubly robust estimator for binary exposures by categorizing the continuous exposure. We compared these with the marginal structural model and outcome regression with correct and incorrect model specifications using simulations. We applied doubly robust additive hazard models to the estimation of hazard difference of long-term exposure to PM2.5 (particulate matter with an aerodynamic diameter less than or equal to 2.5 microns) on survival using a large cohort of 13 million older adults residing in seven states of the Southeastern United States. RESULTS: We showed that the proposed approaches are doubly robust. We found that each 1 µg m increase in annual PM2.5 exposure was associated with a causal hazard difference in mortality of 8.0 × 10 (95% confidence interval 7.4 × 10, 8.7 × 10), which was modified by age, medical history, socioeconomic status, and urbanicity. The overall hazard difference translates to approximately 5.5 (5.1, 6.0) thousand deaths per year in the study population. CONCLUSIONS: The proposed approaches improve the robustness of the additive hazards model and produce a novel additive causal estimate of PM2.5 on survival and several additive effect modifications, including social inequality.

Long-term Exposure to PM2.5 and Mortality Among Older Adults in the Southeastern US.

BACKGROUND: Little is known about what factors modify the effect of long-term exposure to PM2.5 on mortality, in part because in most previous studies certain groups such as rural residents and individuals with lower socioeconomic status (SES) are under-represented. METHODS: We studied 13.1 million Medicare beneficiaries (age ≥65) residing in seven southeastern US states during 2000-2013 with 95 million person-years of follow-up. We predicted annual average of PM2.5 in each zip code tabulation area (ZCTA) using a hybrid spatiotemporal model. We fit Cox proportional hazards models to estimate the association between long-term PM2.5 and mortality. We tested effect modification by individual-level covariates (race, sex, eligibility for both Medicare and Medicaid, and medical history), neighborhood-level covariates (urbanicity, percentage below poverty level, lower education, median income, and median home value), mean summer temperature, and mass fraction of 11 PM2.5 components. RESULTS: The hazard ratio (HR) for death was 1.021 (95% confidence interval: 1.019, 1.022) per 1 µg m increase in annual PM2.5. The HR decreased with age. It was higher among males, non-whites, dual-eligible individuals, and beneficiaries with previous hospital admissions. It was higher in neighborhoods with lower SES or higher urbanicity. The HR increased with mean summer temperature. The risk associated with PM2.5 increased with relative concentration of elemental carbon, vanadium, copper, calcium, and iron and decreased with nitrate, organic carbon, and sulfate. CONCLUSIONS: Associations between long-term PM2.5 exposure and death were modified by individual-level, neighborhood-level variables, temperature, and chemical compositions.

Bayesian analysis of transformation latent variable models with multivariate censored data.

Transformation latent variable models are proposed in this study to analyze multivariate censored data. The proposed models generalize conventional linear transformation models to semiparametric transformation models that accommodate latent variables. The characteristics of the latent variables were assessed based on several correlated observed indicators through measurement equations. A Bayesian approach was developed with Bayesian P-splines technique and the Markov chain Monte Carlo algorithm to estimate the unknown parameters and transformation functions. Simulation shows that the performance of the proposed methodology is satisfactory. The proposed method was applied to analyze a cardiovascular disease data set.