Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach

Predictive toxicology of chemical mixtures using proteome-wide thermal profiling and protein target properties

Our capability to predict the impact of exposure to chemical mixtures on environmental and human health is limited in comparison to the advances on the chemical characterization of the exposome. Current approaches, such as new approach methodologies, rely on the characterization of the chemicals and the available toxicological knowledge of individual compounds. In this study, we show a new methodological approach for the assessment of chemical mixtures based on a proteome-wide identification of the protein targets and revealing the relevance of new targets based on their role in the cellular function. We applied a proteome integral solubility alteration assay to identify 24 protein targets from a chemical mixture of 2,3,7,8-tetrachlorodibenzo-p-dioxin, alpha-endosulfan, and bisphenol A among the HepG2 soluble proteome, and validated the chemical mixture-target interaction orthogonally. To define the range of interactive capability of the new targets, the data from intrinsic properties of the targets were retrieved. Introducing the target properties as criteria for a multi-criteria decision-making analysis called the analytical hierarchy process, the prioritization of targets was based on their involvement in multiple pathways. This methodological approach that we present here opens a more realistic and achievable scenario to address the impact of complex and uncharacterized chemical mixtures in biological systems.

Long-term exposures to low concentrations of source-specific air pollution, road-traffic noise, and systemic inflammation and cardiovascular disease biomarkers

OBJECTIVES

Air pollution and traffic noise are detrimental to cardiovascular health. However, the effects of different sources of these exposures on cardiovascular biomarkers remain unclear. We explored the associations of long-term exposure to source-specific air pollution (vehicular exhausts and residential woodsmoke) at low concentrations and road-traffic noise with systemic inflammation and cardiovascular disease biomarkers.

MATERIAL AND METHODS

Modeled outdoor exposure to fine particulate matter (aerodynamic diameter ≤ 2.5 μm; PM2.5) from vehicular exhausts and residential woodsmoke, nitrogen dioxide (NO2) from road traffic, and road-traffic noise were linked to the home addresses of the participants (Finnish residents aged 25-74) in the FINRISK study 1997-2012. The participants were located in the cities of Helsinki, Vantaa, and the region of Turku, Finland. The outcomes were high-sensitivity C-reactive protein (CRP), a biomarker for systemic inflammation, and cardiovascular disease biomarkers N-terminal pro-B-type natriuretic peptide (NT-proBNP) and troponin I. We performed cross-sectional analyses with linear and additive models and adjusted for potential confounders.

RESULTS

We found no association between PM2.5 from vehicular exhausts (% CRP difference for 1 μg/m3 increase in PM2.5: -0.9, 95% confidence interval, CI: -7.2, 5.8), or from residential woodsmoke (% difference: -8.1, 95% CI: -21.7, 7.9) and CRP (N = 4147). Road-traffic noise > 70 dB tended to be positively associated with CRP (% CRP difference versus noise reference category of ≤ 45 decibels: 18.3, 95% CI: -0.5, 40.6), but the association lacked significance and robustness (N = 7142). Otherwise, we found no association between road-traffic noise and CRP, nor between NO2 from road traffic and NT-proBNP (N = 1907) or troponin I (N = 1951).

CONCLUSION

Long-term exposures to source-specific, fairly low-level air pollution from vehicular exhausts and residential woodsmoke, or road-traffic noise were not associated with systemic inflammation and cardiovascular disease biomarkers in this urban area.

New health index derived from oxidative potential and cell toxicity of fine particulate matter to assess its potential health effect

Toxicological data and exposure levels of fine particulate matters (PM2.5) are necessary to better understand their health effects. Simultaneous measurements of PM2.5 oxidative potential (OP) and cell toxicity in urban areas (Beijing, China and Gwangju, Korea) reveal their dependence on chemical composition. Notably, acids (Polar), benzocarboxylic acids, and Pb were the chemical components that affected both OP and cell toxicity. OP varied more significantly among different locations and seasons (winter and summer) than cell toxicity. Using the measured OP, cell toxicity, and PM2.5 concentration, a health index was developed to better assess the potential health effects of PM2.5. The health index was related to the sources of PM2.5 derived from the measured chemical components. The contributions of secondary organic aerosols and dust to the proposed health index were more significant than their contributions to PM2.5 mass. The developed regression equation was used to predict the health effect of PM2.5 without further toxicity measurements. This new index could be a valuable health metric that provides information beyond just the PM2.5 concentration level.

Health benefits from substituting raw biomass fuels for charcoal and briquette fuels: In vitro toxicity analysis

PM_2.5 (particulate matters with diameter ≤ 2.5 μm) from biomass fuel combustion has been identified as a major cause of cardiopulmonary diseases. Briquette and charcoal are two representative processed fuels that exhibit different emission characteristics. This study compared three types of biomass fuels (maize straw, wheat straw, and wood branches) and their respective processed fuels in terms of their emission factors (EFs). The bioreactivity of human alveolar epithelial (A549) cells to exposure to various fuel-emitted PM_2.5 was assessed. The EFs of lactic dehydrogenase (LDH) and interleukin-6 (IL-6) were calculated to compare actual cytotoxicity. The PM_2.5 EFs of maize and wheat straw were higher than those of wood branches, and following the processes of briquetting and carbonization, the EFs of PM_2.5 and chemical components were effectively reduced. Cell membrane damage and inflammatory responses were observed after A549 cell exposure to PM_2.5 extracts. The expression of bioreactivity to briquettes and charcoals was lower than that to raw fuels. The EFs of LDH and IL-6 were also significantly reduced after briquetting and carbonization. This underscores the necessity of fuel treatment for reducing cytotoxicity. The crucial chemical components that contributed to cell oxidative and inflammatory responses were identified, including organic and elemental carbon, water-soluble ions (e.g., K⁺, Mg²⁺, and Ca²⁺), metals (e.g., Fe, Cr, and Ni), and high-molecular-weight PAHs. This study elucidated the similarities and differences of PM_2.5 emissions and cytotoxicity of three types of biomass fuel and demonstrated the positive effects of fuel treatment on reducing adverse pulmonary effects.

Prediction of Molecular Initiating Events for Adverse Outcome Pathways Using High-Throughput Identification of Chemical Targets

The impact of exposure to multiple chemicals raises concerns for human and environmental health. The adverse outcome pathway method offers a framework to support mechanism-based assessment in environmental health starting by describing which mechanisms are triggered upon interaction with different stressors. The identification of the molecular initiating event and the molecular interaction between a chemical and a protein target is still a challenge for the development of adverse outcome pathways. The cellular response to chemical exposure studied with omics could not directly identify the protein targets. However, recent mass spectrometry-based methods are offering a proteome-wide identification of protein targets interacting with s but unrevealing a molecular initiating event from a set of targets is still dependent on available knowledge. Here, we directly coupled the target identification findings from the proteome integral solubility alteration assay with an analytical hierarchy process for the prediction of a prioritized molecular initiating event. We demonstrate the applicability of this combination of methodologies with a test compound (TCDD), and it could be further studied and integrated into AOPs. From the eight protein targets identified by the proteome integral solubility alteration assay after analyzing 2824 human hepatic proteins, the analytical hierarchy process can select the most suitable protein for an AOP. Our combined method solves the missing links between high-throughput target identification and prediction of the molecular initiating event. We anticipate its utility to decipher new molecular initiating events and support more sustainable methodologies to gain time and resources in chemical assessment.

Health risk assessment and source apportionment of PM2.5-bound toxic elements in the industrial city of Siheung, Korea

The emission sources and their health risks of fine particulate matter (PM_2.5) in Siheung, Republic of Korea, were investigated as a middle-sized industrial city. To identify the PM_2.5 sources with error estimation, a positive matrix factorization model was conducted using daily mean speciated data from November 16, 2019, to October 2, 2020 (95 samples, 22 chemical species). As a result, 10 sources were identified: secondary nitrate (24.3%), secondary sulfate (18.8%), traffic (18.8%), combustion for heating (12.6%), biomass burning (11.8%), coal combustion (3.6%), heavy oil industry (1.8%), smelting industry (4.0%), sea salts (2.7%), and soil (1.7%). Based on the source apportionment results, health risks by inhalation of PM_2.5 were assessed for each source using the concentration of toxic elements portioned. The estimated cumulative carcinogenic health risks from the coal combustion, heavy oil industry, and traffic sources exceeded the benchmark, 1E-06. Similarly, carcinogenic health risks from exposure to As and Cr exceeded 1E-05 and 1E-06, respectively, needing a risk reduction plan. The non-carcinogenic risk was smaller than the hazard index of one, implying low potential for adverse health effects. The probable locations of sources with relatively higher carcinogenic risks were tracked. In this study, health risk assessment was performed on the elements for which mass concentration and toxicity information were available; however, future research needs to reflect the toxicity of organic compounds, elemental carbon, and PM_2.5 itself.

The influence of PM2.5 exposure on kidney diseases

The harm of air pollution to public health has become a research hotspot, especially atmospheric fine-particulate matter (PM_2.5). In recent years, epidemiological investigations have confirmed that PM_2.5 is closely related to chronic kidney disease and membranous nephropathy Basic research has demonstrated that PM_2.5 has an impact on the normal function of the kidneys through accumulation in the kidney, endothelial dysfunction, abnormal renin-angiotensin system, and immune complex deposition. Moreover, the mechanism of PM_2.5 damage to the kidney involves inflammation, oxidative stress, apoptosis, DNA damage, and autophagy. In this review, we summarized the latest developments in the effects of PM_2.5 on kidney disease in human and animal studies, so as to provide new ideas for the prevention and treatment of kidney disease.

Source contributions to multiple toxic potentials of atmospheric organic aerosols

Fine particulate matter (PM_2.5) in the atmosphere is of high priority for air quality management efforts to address adverse health effects in human. We believe that emission control policies, which are traditionally guided by source contributions to PM mass, should also consider source contributions to PM health effects or toxicity. In this study, we estimated source contributions to the toxic potentials of organic aerosols (OA) as measured by a series of chemical and in-vitro biological assays and chemical mass balance model. We selected secondary organic aerosols (SOA), vehicles, biomass open burning, and cooking as possible important OA sources. Fine particulate matter samples from these sources and parallel atmospheric samples from diverse locations and seasons in East Asia were collected for the study. The source and atmospheric samples were analyzed for chemical compositions and toxic potentials, i.e. oxidative potential, inflammatory potential, aryl hydrocarbon receptor (AhR) agonist activity, and DNA-damage, were measured. The toxic potentials per organic carbon (OC) differed greatly among source and ambient particulate samples. The source contributions to oxidative and inflammatory potentials were dominated by naphthalene-derived SOA (NapSOA), followed by open burning and vehicle exhaust. The AhR activity was dominated by open burning, followed by vehicle exhaust and NapSOA. The DNA damage was dominated by vehicle exhaust, followed by open burning. Cooking and biogenic SOA had smaller contributions to all the toxic potentials. Regarding atmospheric OA, urban and roadside samples showed stronger toxic potentials per OC. The toxic potentials of remote samples in summer were consistently very weak, suggesting that atmospheric aging over a long time decreased the toxicity. The toxic potentials of the samples from the forest and the experimentally generated biogenic SOA were low, suggesting that toxicity of biogenic primary and secondary particles is relatively low.

Development of a Novel Integrated CCSD-ITARA-MARCOS Decision-Making Approach for Stackers Selection in a Logistics System

The main goal of this paper is to propose a Multiple-Criteria Decision-Making (MCDM) approach that will facilitate decision-making in the field of logistics—i.e., in the selection of the optimal equipment for performing a logistics activity. For defining the objective weights of the criteria, the correlation coefficient and the standard deviation (CCSD method) are applied. Furthermore, for determining the semi-objective weights of the considered criteria, the indifference threshold-based attribute ratio analysis method (ITARA) is used. In this way, by combining these two methods, the weights of the criteria are determined with a higher degree of reliability. For the final ranking of the alternatives, the measurement of alternatives and ranking according to the compromise solution method (MARCOS) is utilized. For demonstrating the applicability of the proposed approach, an illustrative case study pointing to the selection of the best manual stacker for a small warehouse is performed. The final results are compared with the ones obtained using the other proved MCDM methods that confirmed the reliability and stability of the proposed approach. The proposed integrated approach shows itself as a suitable technique for applying in the process of logistics equipment selection, because it defines the most influential criteria and the optimal choice with regard to all of them in a relatively easy and comprehensive way. Additionally, conceiving the determination of the criteria with the combination of objective and semi-objective methods enables defining the objective weights concerning the attitudes of the involved decision-makers, which finally leads to more reliable results.