Foraging animal origin food samples as passive indicators of dioxin-like POPs contamination in industry sites: Method development, characterisation and risk assessment.

Titanium dioxide (TiO2) is an important industrial chemical, and studies suggest its major production route - the chloride process could lead to the generation of unintentional dl-POPs. However, no relevant studies assessed the occurrence of dl-POPs associated with TiO2 production in the industrial zones, which is mostly due to the ultra-trace level distribution of these compounds in environmental compartments. The present study explored the novel possibility of utilising foraging animal-origin foods as sensitive indicators for addressing this challenge and generated a globally beneficial dataset by assessing the background levels of dl-POPs in the vicinity of a TiO2 production house in Southern India. Systematic sampling of foraging cow's milk and free-ranging hen's eggs was carried out from the study site, and the dl-POPs assessments were conducted utilising an in-house developed cost-effective GC-MS/MS-based analytical methodology. The median dl-POPs levels in milk and egg samples were about 3 times higher than the control samples collected from farm-fed animals and retail markets. The contaminant loads in the foraging animal-origin food samples were further traced to their presence in environmental compartments of soil and sediment and admissible degree of correlations were observed in congener fingerprints. Elevated health risks were inferred for the population in the industrial zones with weekly intakes weighing about 0.15-17 times the European Food Safety Authority-assigned levels. The consumption of foraging cow's milk was observed to have a higher contribution towards the hazard indices and cancer risk estimates and were significantly higher (p < 0.05) for children. The study also presents a critical validation of the GC-MS/MS-based method for the purpose of regulatory monitoring of dl-POPs, which could be of practical significance in economies in transition.

Characteristics of commercial determinants of health research on corporate activities: A scoping review.

INTRODUCTION: Business practices have influenced human health for centuries, yet an overarching concept to study these activities across nations, time periods, and industries (called 'the commercial determinants of health' (CDH)) has emerged only recently. The purpose of this review was to assess the descriptive characteristics of CDH research and to identify remaining research gaps. METHODS: We systematically searched four databases (Scopus, OVID Medline, Ovid Embase, and Ovid Global Health) on Sept 13, 2022 for literature using CDH terms that described corporate activities that have the potential to influence population health and/or health equity (n = 116). We evaluated the following characteristics of the literature: methods employed, industries studied, regions investigated, funders, reported conflicts of interest, and publication in open-access formats. RESULTS: The characteristics of the articles included that many were conceptual (50/116 articles; 43%) or used qualitative methods (37; 32%). Only eight articles (7%) used quantitative or mixed methods. The articles most often discussed corporate activities in relation to the food and beverage (51/116; 44%), tobacco (20; 17%), and alcohol industries (19; 16%), with limited research on activities occurring in other industries. Most articles (42/58 articles reporting a regional focus; 72%) focused on corporate activities occurring in high-income regions of the world. CONCLUSIONS: Our findings indicate that literature that has used CDH terms and described corporate practices that influence human health has primarily focused on three major industries in higher-income regions of the world. Qualitative methods were the most common empirical method for investigating these activities. CDH-focused investigations of corporate practices conducted by less-studied industries (e.g., social media) and in lower-income regions are recommended. Longitudinal quantitative studies assessing the associations between corporate practices and a range of health outcomes is also a necessary next step for this field.

Working with Industry.

In 1992, I completed a 9-year dual-degree program where I received both my DPM degree and a PhD in Bioengineering. Upon my graduation, it was apparent that "Industry" had an interest in me. Sponsored research and consulting opportunities where readily available, and I had to learn very quickly to sort the scientific from the sham, and the clinically worthwhile from the worthless. Partnering with Industry has provided me with another avenue to advance my profession, while helping to develop new treatment options that can potentially help many more patients then just the ones I see in my office.

Exploring pollutant joint effects in disease through interpretable machine learning.

Identifying the impact of pollutants on diseases is crucial. However, assessing the health risks posed by the interplay of multiple pollutants is challenging. This study introduces the concept of Pollutants Outcome Disease, integrating multidisciplinary knowledge and employing explainable artificial intelligence (AI) to explore the joint effects of industrial pollutants on diseases. Using lung cancer as a representative case study, an extreme gradient boosting predictive model that integrates meteorological, socio-economic, pollutants, and lung cancer statistical data is developed. The joint effects of industrial pollutants on lung cancer are identified and analyzed by employing the SHAP (Shapley Additive exPlanations) interpretable machine learning technique. Results reveal substantial spatial heterogeneity in emissions from CPG and ILC, highlighting pronounced nonlinear relationships among variables. The model yielded strong predictions (an R of 0.954, an RMSE of 4283, and an R2 of 0.911) and emphasized the impact of pollutant emission amounts on lung cancer responses. Diverse joint effects patterns were observed, varying in terms of patterns, regions (frequency), and the extent of antagonistic and synergistic effects among pollutants. The study provides a new perspective for exploring the joint effects of pollutants on diseases and demonstrates the potential of AI technology to assist scientific discovery.

Exploring the role of large language models in radiation emergency response.

In recent times, the field of artificial intelligence (AI) has been transformed by the introduction of large language models (LLMs). These models, popularized by OpenAI's GPT-3, have demonstrated the emergent capabilities of AI in comprehending and producing text resembling human language, which has helped them transform several industries. But its role has yet to be explored in the nuclear industry, specifically in managing radiation emergencies. The present work explores LLMs' contextual awareness, natural language interaction, and their capacity to comprehend diverse queries in a radiation emergency response setting. In this study we identify different user types and their specific LLM use-cases in radiation emergencies. Their possible interactions with ChatGPT, a popular LLM, has also been simulated and preliminary results are presented. Drawing on the insights gained from this exercise and to address concerns of reliability and misinformation, this study advocates for expert guided and domain-specific LLMs trained on radiation safety protocols and historical data. This study aims to guide radiation emergency management practitioners and decision-makers in effectively incorporating LLMs into their decision support framework.

[The effect of industrial factors on health of crew members of bulk-oil fleet].

The negative effect of oil vapors and oil products on health of crew of tanker fleet is a large-scale problem of shipping since safety of life and health of seamen is declared as essential value in implementation of production activity. The inert gases emitted during handling and transportation of oil products, in view of their toxicity, may result not only in acute intoxication but also in development of chronic diseases when inhaling harmful substances in moderate concentrations. The article considers main professional industrial factors that affect crew members of bulk-oil fleet, symptomatology of intoxication and initial care of crew members, application of personal cover when working with this type of cargo. The special attention is paid to chronic diseases developing against the background of negative effect of oil products on health of seamen. The recommendations of prevention and timely detection of their development are proposed.

Severe Work-Related Injuries in the Oil and Gas Extraction Industry - 32 Federal Occupational Safety and Health Administration Jurisdictions, United States, January 2015-July 2022.

The Occupational Safety and Health Administration (OSHA) severe injuries reports include work-related injuries from establishments under federal OSHA jurisdiction that result in an amputation, loss of an eye, or inpatient hospitalization. Data from 32 jurisdictions were examined to determine oil and gas extraction industry-specific severe industry trends during January 2015-July 2022, using the 2012 North American Industry Classification System (NAICS) codes for oil and gas extraction. During this period, a total of 2,101 severe work-related injuries were reported in this sector. Among these severe work-related injuries, well service contract workers' injuries included the highest number of amputations (417) and hospitalizations (1,194), accounting for 20% and 57%, respectively, of all severe injuries reported. Overall, 895 (43%) of all severe injuries reported involved upper extremities. Contract workers in the service and drilling subindustries (NAICS codes 213112 and 213111, respectively) experienced disproportionately more work-related injuries compared with those in the operation subindustry (NAICS code 211). These injuries could be preventable by including contractors in worksite safety plans that administer the hierarchy of controls, are within an effective safety management system, and provide consistent safety training on work equipment, personal protective equipment, and daily site safety meetings that increase safety culture.

Effect of Gamma and X-ray Irradiation on Polymers Commonly Used in Healthcare Products.

Synthetic organic polymers commonly are used in the construction of healthcare product and medical device components. Medical devices often are sterilized to ensure that they are free from viable microorganisms. A common technique to achieve this is using ionizing radiation, usually gamma. A trend exists in industrial sterilization to supplement gamma with alternative accelerator technologies (e.g., X-ray). In the current work, studies were performed to characterize polymer modifications caused by gamma and X-ray sterilization processes and to assess the comparative equivalency. The studies were developed to evaluate two key process parameters: dose and dose rate. Three commonly used polymers were selected: high-density polyethylene, low-density polyethylene, and polypropylene. Four grades of each family were chosen. The dose assessment involved sample exposures to both gamma and X-ray irradiation at two dose levels (30 and 55 kGy). All other processing conditions, including dose rate, were controlled at standard processing levels akin to each sterilization technology. The dose rate assessment expanded on each dose level by introducing two additional dose rate parameters. Subsequent laboratory testing used techniques to characterize physico-chemical properties of the polymers to ascertain equivalency across test groups. Initial results indicated positive levels of equivalency between gamma and X-ray irradiation.

Decomposition of the site-level energy consumption and carbon dioxide emissions of the iron and steel industry.

Identifying the key factors influencing energy consumption and CO2 emissions is necessary for developing effective energy conservation and emission mitigation policies. Previous studies have focused mainly on decomposing changes in energy consumption and CO2 emissions at the national, regional, or sectoral levels, while the perspective of site-level decomposition has been neglected. To narrow this gap in research, a site-level decomposition of energy- and carbon-intensive iron and steel sites is discussed. In this work, the logarithmic mean Divisia index (LMDI) method is used to decompose the changes in the energy consumption and CO2 emissions of iron and steel sites. The results show that the production scale significantly contributes to the increase in both energy consumption and CO2 emissions, with cumulative contributions of 229.63 and 255.36%, respectively. Energy recovery and credit emissions are two key factors decreasing site-level energy consumption and CO2 emissions, with cumulative contributions to the changes in energy consumption and CO2 emissions of -158.30 and -160.45%, respectively. A decrease in energy, flux, and carbon-containing material consumption per ton of steel promotes direct emission reduction, and purchased electricity savings greatly contribute to indirect emission reduction. In addition, site products and byproducts promote an increase in credit emissions and ultimately inhibit an increase in the total CO2 emissions of iron and steel sites.

Identifying dynamic risk spillovers between crude oil and downstream industries: China's futures market perspective.

Interactions between crude oil and its downstream products are crucial but complex. The main purpose of this study is to examine the risk spillover relationships between the crude oil futures market and the petrochemical downstream futures market in the context of the COVID-19 epidemic in China. By combining the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model and the Diebold-Yilmaz spillover index based on time-varying parameter-vector autoregression (TVP-VAR-DY), we investigate the dynamic correlations between Shanghai crude oil futures (INE) and the downstream futures in China's petrochemical industry chain. At the same time, we also incorporate the representative global crude oil futures (BRENT and WTI) in our study as a comparative analysis. Our results show a significant positive correlation between three crude oil futures and China's downstream future products, with a more pronounced link observed between INE and the downstream futures market. Moreover, the correlation between crude oil futures and various downstream products exhibits heterogeneity; that is, direct derivatives of crude oil show higher sensitivity to price fluctuations compared to products with longer production chains. Furthermore, the spillover results indicate that the international crude oil futures, particularly BRENT, primarily function as spillover transmitters, while INE mainly serves as the recipient. In the post-pandemic period, the international crude oil market still exhibits a high spillover effect, and the spillover effect of INE to polyvinyl chloride, pure terephthalic acid, and bitumen futures increased, reflecting market recovery in China to some extent. These results provide potential insights for policymakers, financial institutions, industry participants, and investors, emphasizing the importance of enhanced risk management, diversified investment strategies, and attention to market dynamics.

Machine learning modeling and additive explanation techniques for glutathione production from multiple experimental growth conditions of Saccharomyces cerevisiae.

Glutathione (GSH) production is of great industrial interest due to its essential properties. This study aimed to use machine learning (ML) methods to model GSHproduction under different growth conditions of Saccharomyces cerevisiae, namely cultivation time, culture volume, pressure, and magnetic field application. Different ML and regression models were evaluated for their statistics to select the most robust model. Results showed that eXtreme Gradient Boosting (XGB) was the best predictive performance model. From the best model, additive explanation techniques were used to identify the feature importance of process. According to variable analysis, the best conditions to obtain the highest GSH concentrations would be cultivation times of 72-96 h, low magnetic field intensity (3.02 mT), low pressure (0.5 kgf.cm-2), and high culture volume (3.5 L). XGB use and additive explanation techniques proved promising for determining process optimization conditions and selecting the essential process variables.

Understanding nitrogen dynamics in the Brazilian beef industry: A comprehensive decadal analysis.

Brazil stands as a prominent beef producer and exporter, witnessing major transformations and expansions in its production chain over the past 20 years. These changes have prompted concerns regarding waste generation and environmental pressure. This study employs material flow analysis (MFA) to quantify nitrogen flows throughout the cattle slaughter process and subsequent beef consumption in Brazil, spanning from 2011 to 2021. The analysis encompasses co-production streams like leather, tallow, viscera, and blood. Nitrogen use efficiency (NUE) and the nitrogen cascade indicator (NCI) were used to evaluate efficiency and nitrogen accumulation in the production chain. Nitrogen inputs in the system increased by 8.47 %, while beef production rose by 7.29 %. In contrast, per capita beef consumption decreased by 1.29 kg, despite an overall consumption increase of 2.84 %, attributed to population growth in Brazil. Beef exports witnessed a notable surge of 86.03 %. Conversely, human excreta and food waste losses experienced increments of 10.88 % and 2.84 %, respectively. Examining NUE reveals the highest values during the slaughter phase (90 %), followed by processing, transportation, and storage stages (79-88 %). The consumption phase exhibited the lowest NUE values (29-34 %). Regarding the cumulative nitrogen effect, the NCI varied between 77 % and 82 % throughout the study period. This highlights opportunities for enhancing nitrogen use efficiency, particularly by addressing food waste at the consumer level. Notably, the study observes nitrogen accumulation across the Brazilian beef production chain, potentially contributing to the nitrogen cascade effect and heightening environmental pressure. Recognizing these dynamics provides avenues for targeted improvements, emphasizing the need to address nitrogen-related challenges and enhance sustainability in the beef production and consumption landscape.

Sociodemographic inequities in the burden of carcinogenic industrial air emissions in the United States.

BACKGROUND: Industrial facilities are not located uniformly across communities in the United States, but how the burden of exposure to carcinogenic air emissions may vary across population characteristics is unclear. We evaluated differences in carcinogenic industrial pollution among major sociodemographic groups in the United States and Puerto Rico. METHODS: We evaluated cross-sectional associations of population characteristics including race and ethnicity, educational attainment, and poverty at the census tract level with point-source industrial emissions of 21 known human carcinogens using regulatory data from the US Environmental Protection Agency. Odds ratios and 95% confidence intervals comparing the highest emissions (tertile or quintile) to the referent group (zero emissions [ie, nonexposed]) for all sociodemographic characteristics were estimated using multinomial, population density-adjusted logistic regression models. RESULTS: In 2018, approximately 7.4 million people lived in census tracts with nearly 12 million pounds of carcinogenic air releases. The odds of tracts having the greatest burden of benzene, 1,3-butadiene, ethylene oxide, formaldehyde, trichloroethylene, and nickel emissions compared with nonexposed were 10%-20% higher for African American populations, whereas White populations were up to 18% less likely to live in tracts with the highest emissions. Among Hispanic and Latino populations, odds were 16%-21% higher for benzene, 1,3-butadiene, and ethylene oxide. Populations experiencing poverty or with less than high school education were associated with up to 51% higher burden, irrespective of race and ethnicity. CONCLUSIONS: Carcinogenic industrial emissions disproportionately impact African American and Hispanic and Latino populations and people with limited education or experiencing poverty thus representing a source of pollution that may contribute to observed cancer disparities.

Respiratory Exposure to Highly Fluorinated Chemicals via Application of Ski Wax and Related Health Effects.

PURPOSE: Waxes containing per- and polyfluoroalkyl substances (PFAS) are applied to the base of skis and snowboards ("skis") to reduce friction with the snow surface and improve glide. PFAS exposure can adversely impact cardiometabolic, thyroid, liver, kidney, reproductive, and immune health and are associated with increased risk of certain cancers. In the present review, we summarize the state of the science on PFAS exposure from fluorinated ski wax use, including acute respiratory health effects and PFAS concentrations in biological and environmental media collected from ski waxing settings. RECENT FINDINGS: Perfluoroalkyl carboxylic acid (PFCA) concentrations in serum and air collected from professional wax technicians and the rooms where waxes are applied are among the highest of any occupation investigated to date, including the fluorochemical industry. High airborne concentrations of fluorotelomer alcohols contribute to high body burdens of certain PFCAs among ski waxers. Fluorinated ski waxes are a significant source of PFAS exposure for people waxing skis and/or spending time in areas where waxing occurs. We highlight recommendations for future research, policy, and technologies needed to address PFAS exposures from fluorinated wax use.

The hidden linkage of corporate efficiency and green innovation with human resource management practices: a newly perspective from China.

It is disappointing that despite having access to human resources at very little cost, rising countries' administrations are so ineffective. It is often believed that an organization's unheralded employees hold the keys to its success or failure. A person's mood and demeanor may be influenced by a variety of factors. Human resource management (HRM) methods have been created and used by scientists all over the globe in an effort to maximize the potential of their most important asset. Eco-friendly inventions are crucial to the survival of humanity and the prosperity of enterprises throughout the world. Therefore, the purpose of this research is to look at how green innovation affects both the environment and businesses. Green process metrics and green product metrics, for example, may have an impact on green innovation, which is why these metrics are important to track. The second primary goal of this research is to learn how the commitment and HR practices of top management shape the link between green innovation and economic and environmental success. A self-reported poll was taken by 370 employees in China's manufacturing industry. A partial least square structural equation modelling was used to examine the data collected between April 2021 and February 2022. This research employed confirmatory component analysis, a standard technique of structural equation modelling (SEM) for examining both overt and covert variables and indicators, to assess the reflecting indicators measurement model. The findings suggest that HRM has an effect on green innovation that is both positive and statistically significant. The environment and the economy benefit greatly from green innovations. Relationships between HRM and green innovation have no unfavorable implications on business results or the environment. However, human resource management has the potential to boost organizations' prosocial impact. In a three-way interaction (moderated moderation) model, organizational success is found to have a significant role, whereas environmental and organizational success play just a little one. To improve economic and environmental outcomes across all sectors, this study adds to the existing body of knowledge and argues for the wider implementation of green innovation practices. Human resource managers play a crucial role in developing a company's culture and values. The findings suggest that with leadership's blessing, green technologies may spread across a company.

Carpal tunnel syndrome among Manitoba workers: Results from the Manitoba Occupational Disease Surveillance System.

BACKGROUND: Carpal tunnel syndrome (CTS) is associated with occupational high-force repetitive tasks and vibration. This project examines the relationship between CTS and work to: (1) identify jobs and industries with increased CTS risk; (2) explore whether there is a sex difference in the risk of CTS after controlling for occupation; and (3) determine whether any observed relationships persist after excluding Workers Compensation Board (WCB) accepted time-loss CTS claims. METHODS: We linked 95.5% of time-loss WCB claims from 2006 to 2019 to provincial administrative health data. The cohort included 143,001 unique person-occupation combinations. CTS cases were defined as at least two medical claims for (ICD-9 354) within a 12-month period or a surgical claim for CTS from 2 years before the WCB claim to 3 years after. WCB accepted CTS time-loss claims not identified by the medical claims were also included. RESULTS: A total of 4302 individuals (3.0%) met the CTS definition. Analysis revealed that the hazard ratios (HRs) of CTS vary considerably with occupation. Sex-based differences in CTS risks were observed, both in low- and high-risk occupations. In many occupations with increased HR, the HR remained elevated after excluding accepted time-loss WCB cases. CONCLUSIONS: The risk of developing CTS varied with occupation. Job titles with ergonomic risk factors had higher risks than those with lower exposures. This finding remained after eliminating time-loss compensated WCB cases, suggesting that all cases of CTS in high risk jobs are not identified in WCB statistics. Female workers in some job titles had excess CTS cases compared to male workers within the same job title.

Mapping the Lobbying Footprint of Harmful Industries: 23 Years of Data From OpenSecrets.

Policy Points Our research reveals the similarities and differences among the lobbying activities of tobacco, alcohol, gambling, and ultraprocessed food industries, which are often a barrier to the implementation of public health policies. Over 23 years, we found that just six organizations dominated lobbying expenses in the tobacco and alcohol sectors, whereas the gambling sector outsourced most of their lobbying to professional firms. Databases like OpenSecrets are a useful resource to monitor the commercial determinants of health. CONTEXT: Commercial lobbying is often a barrier to the development and implementation of public health policies. Yet, little is known about the similarities and differences in the lobbying practices of different industry sectors or types of commercial actors. This study compares the lobbying practices of four industry sectors that have been the focus of much public health research and advocacy: tobacco, alcohol, gambling, and ultraprocessed foods. METHODS: Data on lobbying expenditures and lobbyist backgrounds were sourced from the OpenSecrets database, which monitors lobbying in the United States. Lobbying expenditure data were analyzed for the 1998-2020 period. We classified commercial actors as companies or trade associations. We used Power BI software to link, analyze, and visualize data sets. FINDINGS: We found that the ultraprocessed food industry spent the most on lobbying ($1.15 billion), followed by gambling ($817 million), tobacco ($755 million), and alcohol ($541 million). Overall, companies were more active than trade associations, with associations being least active in the tobacco industry. Spending was often highly concentrated, with two organizations accounting for almost 60% of tobacco spending and four organizations accounting for more than half of alcohol spending. Lobbyists that had formerly worked in government were mainly employed by third-party lobby firms. CONCLUSIONS: Our study shows how comparing the lobbying practices of different industry sectors offers a deeper appreciation of the diversity and similarities of commercial actors. Understanding these patterns can help public health actors to develop effective counterstrategies.