Comprehensive Impact Assessment Research Articles

EFFECT OF FUEL SUBSIDY REMOVAL ON THE NIGERIAN ECONOMY: A STUDY OF ADAMAWA CENTRAL SENATORIAL DISTRICT

The paper examined the effect of fuel subsidy removal on the Nigerian Economy: A study of Adamawa Central Senatorial District. The economic development of a society is vital for the welfare, and satisfaction of the needs of members of the society. Since Nigeria’s independence in 1960 to the current political dispensation, several efforts were made to accelerate economic development. However, in spite of several policies initiated and implemented in Nigeria, the country appears to be at the economic crossroad and faces a dilemma of economic development. Fuel subsidy is one of such policies initiated and implemented in Nigeria. The federal government operated fuel subsidy with the aim of making petroleum products available to cushion the effect of actual market prices of the product on the general populace for several decades. Recently, the removal of fuel subsidy has generated mixed reactions in the political process. The study utilized primary and secondary sources of data generation. Data were obtained from published and unpublished materials like books, magazines, journals, newspapers etc. The study revealed that the removal of the fuel subsidy has been met with considerable skepticism and concern among the public because government has not adequately addressed the implications of this policy change, particularly regarding transparency, social equity, and its economic benefits. The study therefore recommends the need to conduct comprehensive impact assessments before implementing policy changes, like subsidy removal, is essential. These assessments should involve stakeholder consultations, particularly with communities that would be directly affected. Understanding the potential socio-economic implications of such changes can help the government make informed decisions and develop strategies that mitigate negative impacts on vulnerable populations.

Capturing the health and well-being impact of climate change: a health impact assessment in Wales

Abstract Climate change is one of the biggest threats to global health in the 21st century and is likely to impact on health through a range of factors (societal, economic or environmental). The need to take action on climate and nature emergencies in order to protect population health and well-being and prevent negative impacts are becoming more urgent. Public Health Wales carried out a comprehensive mixed-method Health Impact Assessment (HIA) of climate change in Wales. HIA is a systematic process which considers the impact of a policy on the health and well-being of a population. It appraised the potential impacts of climate change on health and inequalities in Wales. This involved participatory workshops, engagement with stakeholders, statistical data, systematic literature reviews and case studies. The HIA findings indicate significant potential impacts across the determinants of health and mental well-being. For example, air quality, flooding, economic productivity, working conditions, access to services and community resilience. Impacts were identified across population groups, settings, and areas including urban and rural contexts, outdoor workers, children and young people, older people, schools, hospitals and workplaces. These findings have been beneficial to inform decision-makers to prepare for climate change plans and policies using a preventative evidence-informed approach. The work has demonstrated the value of HIA for significant, complex policies by mobilising a range of evidence through a transparent process, resulting in government and organizational action and transferrable learning for others. Key messages • HIA is a beneficial tool to identify at a granular level the health impacts of climate change. • The HIA has been used by the government of Wales and organisations to respond to and plan for climate change.

Elucidating the role of MLL1 nsSNPs: Structural and functional alterations and their contribution to leukemia development.

The Mixed lineage leukemia 1 (MLL1) gene, located on chromosome 11q23, plays a pivotal role in histone lysine-specific methylation and is consistently associated with various types of leukemia. Non-synonymous Single Nucleotide Polymorphisms (nsSNPs) have been tied to numerous diseases, including cancers, and have become valuable cancer biomarkers. There's a notable gap in studies probing the influence of SNPs on MLL1 protein structure, function, and subsequent modifications. We utilized an array of bioinformatics tools, including PredictSNP, InterPro, ConSurf, I-Mutant2.0, MUpro, Musitedeep, Project HOPE, RegulomeDB, Mutpred2, and both CScape and CScape Somatic, to meticulously analyze the consequences of nsSNPs in the MLL1 gene. Out of 2,097 nsSNPs analyzed, 62 were determined to be significantly pathogenic by the PredictSNP tool, with ten crucial MLL1 functional domains identified using InterPro. Additionally, 50 of these nsSNPs had high conservation scores, hinting at potential effects on protein structure and function, while 32 were found to undermine MLL1 protein stability. Notably, four nsSNPs were deemed oncogenic, with two identified as cancer drivers. The nsSNP, D2724G, between the MLL1 protein's FY-rich domains, could disrupt proteolytic cleavage, altering gene expression patterns and potentially promoting cancer. Our research provides a comprehensive assessment of nsSNPs' impact in the MLL1 protein structure and function and consequently on leukemia development, suggesting potential avenues for personalized treatment, early detection, improved prognosis, and a deeper understanding of hematological malignancy genesis.

The impact of exposure assessment on associations between air pollution and cardiovascular mortality risks in the city of Rio de Janeiro, Brazil

Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM2.5) and ozone (O3) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012–2016. PM2.5 and O3 exposure levels (from the date of death to seven prior days [lag0–7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM2.5 than O3. PM2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.

Advancing Economical and Environmentally Conscious Electrification: A Comprehensive Framework for Microgrid Design in Off‐Grid Regions

AbstractThe design of renewable energy systems traditionally emphasizes life cycle costs, often focusing primarily on emissions rather than a comprehensive life cycle impact assessment. This research proposes a four‐tier methodology to balance cost‐effectiveness and sustainability in the electrification of remote areas. Tier 1 focuses on understanding the community context by analyzing electrical load profiles, meteorological data, and component specifications for microgrid design. Tier 2 evaluates the feasibility of various systems, optimizing them through cost analysis and Multi‐Criteria Decision‐Making (MCDM) to rank alternatives. Tier 3 assesses environmental impacts using life cycle assessment, ranking alternatives based on environmental criteria. Tier 4 integrates cost and environmental rankings to determine the most suitable energy configurations, followed by sensitivity analysis to ensure robust decision‐making. The methodology is validated through a case study of an unelectrified remote community, demonstrating that the PV‐Wind Turbine‐Biomass Generator‐Converter configuration is the most robust alternative, proving to be the optimal choice in 50% of the analyzed scenarios, achieving a Cost of Energy of 0.213 USD/kWh while minimizing environmental impact across all 18 criteria considered over a 25‐year life cycle. This novel framework offers a scalable approach to designing renewable energy systems, enhancing sustainable electrification efforts in developing regions.

Molecular properties of dissolved organic matter leached from microplastics during photoaging process

The occurrence of dissolved organic matter (DOM) derived from microplastics (MPs) and its effect on aquatic systems has attracted great interest recently. However, the photoaging effect on the molecular structure of MP-derived DOM (MP-DOM) remains unclear. This paper presents the characteristics of DOM leached from three commercial MPs, i.e., polyethylene (PE), polypropylene (PP) and polyethylene terephthalate (PET) under UV irradiation. With prolonged aging periods, the surface roughness and oxygen-containing groups on the surface of MPs increase as more DOM leachate is generated. Moreover, the dissolved organic carbon (DOC) content of the leached DOM from PET MPs varies from 0.52 mg/L to 2.25 mg/L, which is higher than PE and PP MPs, due to the larger increased surface reaction area and the cleavage of the benzene ring. According to the excitation-emission matrix and parallel factor analysis (EEM-PARAFAC), the plastic-derived protein/phenolic-like components (C1 and C3) in MP-DOM were changed into photo-induced humic-like components (C2), which were closely related to the intermediates during photo-oxidation. High-performance liquid chromatography-mass spectrometry (HPLC−MS) analysis further identified that the highest proportion of antioxidants (24.8 %∼34.6 %) was contained in MP-DOM. Plasticizers, intermediate additives, and antimicrobial agents were also detected in DOM leachate. Correlation analysis identified that the composition of leached DOM was positively correlated with the surface roughness, the carbonyl index (CI), and the chemical groups of MPs. Moreover, a partial least square structural equation model (PLS−SEM) analysis further verified that the change of morphology and the chemical structure of MPs could affect the DOM structures and fractions directly. This study provides an in-depth understanding of the composition of MP-derived DOM during the aging process, as well as a comprehensive environmental impact assessment of MPs.

A Comprehensive Assessment of the Environmental Impact of Different Infant Feeding Types: The Observational Study GREEN MOTHER.

To observe and compare the environmental impacts of different types of infant feeding, considering the use of formula, infant feeding accessories, potentially increased maternal dietary intake during breastfeeding (BF) and food consumption habits. An observational cross-sectional multicentre study conducted in the Barcelona Metropolitan Area of the Catalan Institute of Health. Data were collected from 419 postpartum women on infant feeding type (formula milk and accessories), maternal dietary intake (24-h register) and food consumption habits from November 2022 to April 2023. The environmental impacts (climate change (CC), water consumption and water scarcity) of the infant feeding types and maternal diet were calculated using the IPCC, ReCiPE and AWARE indicators, respectively. The differences in impacts were calculated by Kruskal-Wallis test. Significant differences for the three environmental impacts were observed. The CC impact of formula milk and feeding accessories was 0.01 kg CO2eq for exclusive BF, 1.55 kg CO2eq for mixed feeding and 4.98 kg CO2eq for formula feeding. While BF mothers consumed an extra 238 kcal, no significant differences were found related to maternal diet across feeding types. Exclusive BF was the most sustainable type of infant feeding, considering formula and infant feeding accessories. In our study, the difference between the impacts of BF and non-BF mothers' diet was insignificant. Offer informative and educational support for midwives and other healthcare professionals on BF and a healthy, sustainable diet to transfer this knowledge to the general public. Raise the general public's awareness about BF and a healthy, sustainable diet. To reduce environmental impacts through behavioural changes. STROBE. Patients of the Catalan Health Service reviewed the content of the data collection tools. (for the whole GREEN MOTHER project): NCT05729581 (https://clinicaltrials.gov).

Environmental impact assessment of a direct methanol fuel cell and strategic mitigation guidelines

Direct methanol fuel cells (DMFCs) are gaining attention as a viable technology for portable and remote applications due to the benefits of methanol as fuel. However, the environmental implications of this technology have not been thoroughly evaluated. This study aims to conduct a comprehensive assessment of the environmental impact of a DMFC throughout its entire life cycle, and based on the findings, propose guidelines for minimizing the impact. To eliminate any potential biases, a two-step design methodology is applied. The first step involves obtaining the optimal preliminary design, for which a genetic algorithm is implemented. The second step is to conduct the environmental impact study on that optimal configuration. As a study case, a DMFC for a highly demanding application, such as an unmanned aerial vehicle, is selected, using green methanol as fuel. The results reveal that extraction and production stage has the greatest effect on the environment (74.1%), compared to use (25.8%) and transport stages (0.1%). Among the components of the stack, the catalysts have the most significant environmental footprint, 93.3% of the total impact of the stack during the extraction and production stage, while bipolar plates represent only 5.9%, despite comprising 86% of the stack’s mass.

Building shape optimization based on interconnected embodied and operational energy and carbon impacts

Strategic building design decisions informed by a comprehensive life cycle impact assessment hold substantial potential in addressing global energy consumption and carbon emissions, with buildings accounting for 40% of energy consumption and 37% of emissions. While building operational energy (OE) has traditionally received greater attention, the dynamic trade-offs between OE and embodied energy (EE) in building design are often overlooked. Design decisions, such material selection and building shape, can present conflicting considerations between OE and EE. Addressing these impacts in isolation may fail to achieve comprehensive reductions in energy consumption and carbon emissions. This study highlights the necessity of a holistic approach to design decisions such as building shape and material selection, emphasizing the importance of considering both OE and EE simultaneously. Our literature review confirms a gap in studies that consider these factors together in the context of building shape optimization. To analyze the interconnectivity of building shape design, material choice, and the trade-offs between OE and EE, we devised two parametric test cases with identical features but using two different insulation materials: hemp-based and glass wool. The analysis allows us to (1) evaluate the impact of integrating total lifecycle impact on building shape design optimization, in comparison to designs that focus solely on OE; (2) assess how the selection of materials, specifically hemp-based versus glass wool insulation, influences optimized building shape and carbon emissions reduction; and explore the benefits of bio-based materials by analyzing performance variations in the two insulations case studies. Our findings reveal that although OE typically has a larger impact over a building’s lifetime, the optimal building shape can still vary significantly based on the EE contribution. The benefit of bio-based material is context-dependent, varying with factors such as the building shape discussed in this paper, as well as other factors such as climate. In our test cases, we observed that shape variations resulted in up to a 17.9% change in OE due to different building shapes, and a 60.7% variation in the envelope’s surface area, while the building area remained unchanged. This expanded understanding will facilitate more informed and sustainable decision-making in the construction and design industries, addressing the often-overlooked interconnectivity of OE and EE.

Integrating artificial intelligence into ERP systems: advantages, disadvantages and prospects

Objective: to identify the key benefits and potential risks associated with the use of artificial intelligence in ERP systems to improve decision-making processes, management efficiency and operational performance of various sectors, including commercial and non-profit organizations. Methods: systematic literature review, empirical data analysis, analytical and experimental research methods. Results: the key directions of artificial intelligence implementation in ERP-systems are reflected, providing improvement of operational efficiency, customer relations, as well as optimization of business processes, data management, supply chain and personnel management, automation of operations related to finance, optimization of customer relations; implementation of artificial intelligence in ERP-systems reduces inventory management costs, improves the accuracy of forecasting andinventory optimization, accelerates financial analysis and increases the accuracy of budgeting, resulting in reduced budget planning time; it also increases productivity by optimizing necessary production processes and reducing equipment downtime. However, there are also risks of confidential data leakage, unauthorized access to data; job losses due to automation of tasks; and vulnerability to cyberattacks. Scientific novelty: the little-studied directions of artificial intelligence integration in ERP-systems are analyzed; an integrative approach to the application of artificial intelligence in ERP-systems is proposed, which combines methods of machine learning, natural language processing and predictive analytics and provides a comprehensive assessment of the complex impact on the business processes’ efficiency. Practical significance: the formulated directions for solving the identified problems of artificial intelligence integration in ERP-systems can be implemented in practice, as they will enable to better take into account local requirements and laws.

Cumulative collision risk and population-level consequences of industrial wind-power plant development for two vulture species: A quantitative warning

Prioritizing renewable energy generation over the conservation of natural habitats and species on a large spatial scale, leads to the paradox of impacting biodiversity to mitigate climate change. In this study, we aim at quantifying the long-term demographic impact of the excess mortality caused by collisions with wind turbines on the populations of two vulture species of conservation concern. Using long-term monitoring data and Integrated Population Models (IPMs), we quantified demographic parameters and projected population trends under various wind power development scenarios. Our findings indicate that even under our most optimistic scenarios, annual collision mortality could reach up to 30 % of the current Cinereous vulture population and 7 % of the Griffon vulture population. Without further wind power expansion, both vulture populations are predicted to remain stable or increase over the next 20 years. However, the addition of 85 wind turbines is likely to drive the Cinereous vulture to local extinction within 18 years and significantly slow the growth of the Griffon vulture population. Scenarios involving larger numbers of turbines could result in the extinction of both species within two to five years for Cinereous vultures and up to 20 years for Griffon vultures, depending on space use intensity. Our results underscore the vulnerability of long-lived species to excess mortality and highlight the need for comprehensive Environmental Impact Assessments (EIAs) that incorporate population dynamics analyses. Effective conservation strategies must include rigorous pre- and post-construction monitoring, the availability of monitoring data, and cumulative impact assessments that consider the entire foraging range of these species. Additionally, strategic planning to avoid critical vulture habitats and implementing mitigation measures in buffer zones are essential. This study emphasizes the necessity of integrating biodiversity considerations into renewable energy planning to balance the goals of energy production and wildlife conservation.

Assessing the sustainability of Blue Economy activities using an ecosystem and life cycle-based approach: Possibilities, challenges and implications for an informed policy making

The global ocean faces increasing exploitation to meet the demand of a rapidly growing globalisation. Human marine activities are leading to local environmental pressures/benefits, for example on marine ecosystems and their services, but also through their value chains on terrestrial ecosystem services, and to global pressures such as global warming. Effective management of marine activities is essential for the conservation of the natural environment. There is a growing need for holistic sustainability assessment tools capable of quantifying environmental impacts at various geographical scales, alongside evidence-informed policies. This study examines the evolving marine policy landscape, identifies key legislation that supports the sustainable growth of the Blue Economy, traces its historical development, and explores the integration of ecosystem services assessment and life cycle assessment as methodologies for assessing environmental sustainability within this legislation. The review shows that current legislation falls short in providing instructions on how to measure sustainability impacts in a consistent way, i.e., which methods/indicators to use. Therefore, this study supports evidence-informed policy-making by proposing a quantitative and comprehensive environmental sustainability impact assessment methodology, integrating both ecosystem and life-cycle based methods, to a Belgian multi-use case study involving offshore wind energy and mussel farming. Considering the impacts that were possible to assess and the limits of the methodology used, the value of the positive impacts of the MUOF was +61.3 M€ y−, while the negative ones were −4.0 M€ y−1, resulting in a net handprint of +57.0 M€ y−1, primarily attributed to the benefits of the local ecosystem service ‘offshore renewable energy’ However, such a solution is not necessarily scalable, due to cumulative impacts. An analysis was conducted to identify areas for enhancing the methodology to more effectively meet policy needs. The study highlights the importance of using scientifically grounded methods to inform policy decisions.

Incorporating Privacy by Design Principles in the Modification of AI Systems in Preventing Breaches across Multiple Environments, Including Public Cloud, Private Cloud, and On-prem

The rapid integration of artificial intelligence (AI) across various sectors has significantly amplified privacy concerns, particularly with the growing reliance on cloud environments. Existing methods often fall short of effectively preventing privacy breaches due to inadequate risk assessment and mitigation strategies. These limitations highlight the necessity for more robust solutions, indicating the importance of Privacy by Design (PbD) principles. This study addresses these gaps by proposing a comprehensive approach to incorporating PbD principles into AI systems to prevent breaches across public, private, and on-prem environments. The proposed work utilizes logistic regression analysis to identify significant predictors of privacy breaches, revealing that both the environment (B = -1.142, p < .001) and severity of vulnerabilities (B = 0.932, p < .01) play crucial roles. Additionally, a strong positive correlation (r = 0.791) between breach detection rates and PbD effectiveness is observed, indicating the need for enhanced detection mechanisms. To support the empirical findings, this study also reviews existing case studies. It conducts a thematic analysis to provide a deeper understanding of the practical challenges and solutions associated with PbD implementation, particularly in healthcare and smart city applications. These analyses serve to supplement the empirical evidence and demonstrate the effectiveness of PbD over other existing methods. The study concludes that implementing PbD principles is critical for achieving robust privacy protection, and the study recommends prioritizing advanced breach detection mechanisms, comprehensive privacy impact assessments, continuous stakeholder engagement, and investment in privacy-enhancing technologies to address privacy risks effectively.

Asian Low-Carbohydrate Diet with Increased Whole Egg Consumption Improves Metabolic Outcomes in Metabolic Syndrome: A 52-Week Intervention Study

BackgroundThe low-carbohydrate-ketogenic diet, an effective strategy to address metabolic syndrome (MetS) and obesity has raised concerns about high-fat consumption on atherogenic lipoproteins. ObjectiveThe aim of this study was to compare the Asian ketogenic diet (AKD), which incorporates balanced protein and fat intake from Asian foods, with a balanced low-caloric diet (BLC) in individuals diagnosed with MetS. MethodsA 52-wk randomized clinical trial included 3 parallel groups: AKD with increased whole egg intake [egg yolk Asian ketogenic diet (Yolk-AKD, n = 28)], yolk-free ketogenic diet with egg white supplementation [egg white Asian ketogenic diet (White-AKD, n = 26)], and BLC (n = 22). Primary outcomes were anthropometric and metabolic changes. ResultsThe AKD groups achieved significant reductions in weight and waist circumference (P < 0.05). Compared with the BLC group, the AKD groups demonstrated significant improvements in insulin resistance at week 6 and in triglyceride concentrations at weeks 12 (Yolk-AKD) and 35 (White-AKD) (P < 0.05). The AKD groups experienced improvements in hormones associated with insulin sensitivity and appetite, whereas only the Yolk-AKD group had a significant decrease in inflammation-related hormones (P < 0.05). From weeks 35–52, the AKD maintained reductions in anthropometric measurements, blood pressure, improved glucose tolerance, enhanced lipid profiles, and better liver function compared with the BLC. ConclusionsThe AKD proved safe and effective, yielding various metabolic improvements in individuals with MetS compared with the BLC. Emphasizing a low-saturated fat diet while disregarding dietary cholesterol, this approach holds promise for MetS and obesity management. The inclusion of both White-AKD and Yolk-AKD groups allowed for a comprehensive assessment of the AKD's impact, elucidating the differential effects of whole egg consumption on metabolic outcomes. Further studies are warranted.This trial was registered at clinicaltrials.gov as NCT04608136.

Regulatory Framework for Gold Mining in Ghana: An Analysis of Damongo’s Mining Sector

This study offers a comprehensive analysis of the regulatory framework governing gold mining in Ghana, with a specific focus on Damongo, a rapidly growing mining hub in the Northern Region. Ghana's gold mining sector, a major contributor to the nation's economy, faces significant challenges despite its economic benefits. These challenges include severe environmental degradation, mercury contamination, and social issues exacerbated by inadequate regulatory enforcement. This article examines the existing regulatory framework, which includes key legislative acts such as the Minerals and Mining Act, 2006, and the Environmental Protection Agency Act, 1994, alongside a network of regulatory institutions like the Ministry of Lands and Natural Resources and the Minerals Commission. Utilizing Damongo as a case study, this research reveals critical inefficiencies in the local regulatory system, particularly in combating illegal mining activities and managing environmental and social impacts. Findings indicate that while gold mining has stimulated economic growth and provided employment opportunities, it has also led to negative consequences such as increased health problems, social vices, and reduced agricultural productivity. The study underscores the need for more robust regulatory practices, improved institutional capacity, and enhanced community involvement in environmental governance. Comparative insights from regulatory practices in other jurisdictions, such as Australia and Canada, highlight the potential benefits of adopting stricter environmental regulations, comprehensive impact assessments, and better coordination among regulatory agencies. The article concludes with recommendations for strengthening Ghana’s regulatory framework, including increased investment in regulatory institutions, improved enforcement mechanisms, and the promotion of sustainable mining practices. This study aims to contribute to the ongoing discourse on mining regulation and sustainability, providing actionable insights for policymakers and stakeholders involved in the governance of Ghana’s gold mining sector.

Enhancing solar still performance with hybrid nanofluid: a comprehensive assessment of energy, exergy, economics, and environmental impact using a novel fractional model

Enhancing solar still performance with hybrid nanofluid: a comprehensive assessment of energy, exergy, economics, and environmental impact using a novel fractional model

Chemical exposome and children health: Identification of dose-response relationships from meta-analyses and epidemiological studies

BackgroundHealth impact assessment studies quantifying the impact of the chemical exposome on children's health generally consider a small fraction of the exposome. Synthetizing available dose-response relationships is an essential step to fill this gap. We reviewed the literature for dose-response relationships relating the chemical exposome with children health. MethodWe focused on 78 substance-outcome pairs for which the level of evidence had previously been classified as ‘likely’ or ‘very likely’. We searched for dose-response relationships for these pairs from meta-analyses and, if none was available, from single epidemiological studies, from which we conducted meta-analyses whenever possible. ResultsWe identified dose-response relationships for 50 of the 78 prioritized substance-outcome pairs (64%). Dose-response relationships stemmed from meta-analyses for 21 pairs, from de novo meta-analyses for 1 pair and single studies for 28 pairs. Dose-response relationships were available for tobacco (fetal and infant death, congenital heart defects, birth outcomes, orofacial clefts, respiratory health), lead (asthma, cognition, delayed puberty onset and iron deficiency anaemia), polychlorobiphenyls (PCBs) (cognition, respiratory infections and birth outcomes), bisphenol A (cognition), hexachlorobenzene (HCB) (respiratory health), Polybrominated diphenyl ethers (neurodevelopment), DDT (hypospadias, cryptorchidism, miscarriage), pesticides (neurodevelopment), methylmercury (cognition), PFAS (immune system, birth weight, behavior, miscarriage), arsenic (cognition, birth weight, death, respiratory health), cadmium (cognition, birth weight), manganese (behavior), sodium (blood pressure) and thallium (birth weight). For 28 of the 78 substance-outcome pairs (36%), no dose-response relationship was available from epidemiological studies in children. ConclusionsWe identified dose-response relationships for 50 substance-outcome pairs, corresponding to 20 chemicals and 17 health outcomes. These can be used to perform more comprehensive quantitative health impact assessment of the exposome on child health. We also identified 28 substance-outcome pairs corresponding to ‘likely’ or ‘very likely’ effects for which research generating dose-response functions in children would be relevant.

Temperature evolution of laser-ignited micrometric iron particles: A comprehensive experimental data set and numerical assessment of laser heating impact

This study examines the effects of laser heating on the ignition and critical combustion characteristics, such as temperature and burn time, of individual iron particles. It provides time-dependent temperature profiles of laser-ignited particles across a broad spectrum of particle size distributions and oxygen concentrations obtained from experiments, which are a useful database for further development and validation of iron particle combustion models. The herein reported datasets significantly complement those existing in the literature. In the current study, the raw data are thoroughly re-evaluated using refined approaches. For the experimental canonical configuration of single iron particle combustion, an ignition system based on laser heating provides several advantages in overcoming temperature field uncertainties and facilitating controlled environments for optical diagnostics. Despite the inherent uncertainties in laser heating, associated with non-uniform intensity profiles and particle size variations, this study addresses the critical question of how these uncertainties affect in situ measurements of particle temperature and time to reach peak temperature. This study, conducted using a numerical model, reveals a dependence of the particle temperature after laser heating on particle size. However, this dependence does not significantly impact the key parameters of iron-particle combustion, such as the maximum temperature and burn time of the laser-ignited iron particle. The study also presents a comparison between the simulated particle temperature histories and those derived from two-color pyrometry measurements for a wide range of particle size distributions and oxygen concentrations. Notably, by implementing a laser-heating sub-model into an iron particle combustion model, assuming external-diffusion-limited oxidation only up to stoichiometric FeO, the temperature evolution up to the maximum temperature is reasonably captured for a wide range of particle sizes (20–53μm) and oxygen volumetric fractions (14–21vol% O2 mixed with N2). However, with increasing oxygen concentration, the external-diffusion limited model significantly overestimates the heating rate and subsequently the maximum particle temperature.

Scenarios for the long-term efficacy of amyloid-targeting therapies in the context of the natural history of Alzheimer's disease.

Recent clinical trials of amyloid beta (Aβ)-targeting therapies in Alzheimer's disease (AD) have demonstrated a clinical benefit over 18 months, but their long-term impact on disease trajectory is not yet understood. We propose a framework for evaluating realistic long-term scenarios. Results from recent phase 3 trials of Aβ-targeting antibodies were integrated with an estimate of the long-term patient-level natural history trajectory of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score to explore realistic long-term efficacy scenarios. Three distinct long-term efficacy scenarios were examined, ranging from conservative to optimistic. These extrapolations of positive phase 3 trials suggested treatments delayed onset of severe dementia by 0.3 to 0.6 years (conservative), 1.1 to 1.9 years (intermediate), and 2.0 to 4.2 years (optimistic). Our study provides a common language for long-term impact of disease-modifying treatments. Our work calls for studies with longer follow-up and results from early intervention trials to provide a comprehensive assessment of these therapies' true long-term impact. We present long-term scenarios of the efficacy of AD therapies. In this framework, scenarios are defined relative to the natural history of AD. Long-term projections with different levels of optimism can be compared. It provides a common language for expressing beliefs about long-term efficacy.

Evaluation of working conditions in the production system

The paper analyzes methods for assessing professional risk, emphasizing that the primary method is job certification. Job certification establishes the compliance of the workplace with regulatory characteristics for specific risk factors in the production environment. The analysis reveals that the existing methodology for job certification does not provide insights into changes in the parameters of hazardous and harmful factors in the production environment, and consequently, changes in working conditions between planned certifications. The study advocates for a comprehensive assessment of the collective impact of all factors in the production environment and work processes on the human body. This is achieved through hygienic risk factor assessment. The paper highlights the appropriateness of quantitatively assessing working conditions in points, considering the simultaneous influence of multiple hazardous factors. A procedure for point-based assessment of working conditions is proposed, and the applicability of Haber's Law to determine the cumulative dose of a harmful factor in the body is demonstrated.