Current frameworks for environmental and health assessment of hydrocarbon streams and products are flexible and ready for alternative non crude oil-based feeds.

Hazard and risk assessment of complex petroleum-derived substances has been in a state of continuous improvement since the 1970s, with the development of approaches that continue to be applied and refined. Alternative feeds are defined here as those coming into a refinery or chemical plant that are not hydrocarbons from oil and gas extraction such as biologically derived oils, pyrolysis oil from biomass or other, and recycled materials. These feeds are increasingly being used for production of liquid hydrocarbon streams, and hence, there is a need to assess these alternatives, subsequent manufacturing and refining processes and end products for potential risk to humans and the environment. Here we propose a tiered, problem formulation-driven framework for assessing the safety of hydrocarbon streams and products derived from alternative feedstocks in use. The scope of this work is only focused on petrochemical safety assessment, though the principles may be applicable to other chemistries. The framework integrates combinations of analytical chemistry, in silico and in vitro tools, and targeted testing together with conservative assumptions/approaches to leverage existing health, environmental, and exposure data, where applicable. The framework enables the identification of scenarios where de novo hazard and/or exposure assessments may be needed and incorporates tiered approaches to do so. It can be applied to enable decisions efficiently and transparently and can encompass a wide range of compositional space in both feedstocks and finished products, with the objective of ensuring safety in manufacturing and use.

Screening tools to evaluate the neurotoxic potential of botanicals: building a strategy to assess safety.

AREAS COVERED: This paper outlines the selection of NAMs, including in vitro assays using primary rat cortical neurons, zebrafish embryos, and Caenorhabditis elegans. These assays aim to assess neurotoxic endpoints such as neuronal activity and behavioral responses. Microelectrode array recordings of rat cortical neurons provide insights into the impact of botanical extracts on neuronal function, while the zebrafish embryos and C. elegans assays evaluate neurobehavioral responses. The paper also provides an account of the selection of botanical case studies based on expert judgment and existing neuroactivity/toxicity information. The proposed battery of assays will be tested with these case studies to evaluate their utility for neurotoxicity screening. EXPERT OPINION: The complexity of botanicals necessitates the use of multiple NAMs for effective neurotoxicity screening. This paper discusses the evaluation of methodologies to develop a robust framework for evaluating botanical safety, including complex neuronal models and key neurodevelopmental process assays. It aims to establish a comprehensive screening framework.

(Non)targeted Chemical Analysis and Risk Assessment of Organic Contaminants in Darkibor Kale Grown at Rural and Urban Farms.

This study investigated the presence and human hazards associated with pesticides and other anthropogenic chemicals identified in kale grown in urban and rural environments. Pesticides and related compounds (i.e., surfactants and metabolites) in kale samples were evaluated using a nontargeted data acquisition for targeted analysis method which utilized a pesticide mixture containing >1,000 compounds for suspect screening and quantification. We modeled population-level exposures and assessed noncancer hazards to DEET, piperonyl butoxide, prometon, secbumeton, terbumeton, and spinosyn A using nationally representative estimates of kale consumption across life stages in the US. Our findings indicate even sensitive populations (e.g., pregnant women and children) are not likely to experience hazards from these select compounds were they to consume kale from this study. However, a strictly nontargeted chemical analytical approach identified a total of 1,822 features across all samples, and principal component analysis revealed that the kale chemical composition may have been impacted by agricultural growing practices and environmental factors. Confidence level 2 compounds that were ≥5 times more abundant in the urban samples than in rural samples (p < 0.05) included chemicals categorized as "flavoring and nutrients" and "surfactants" in the EPA's Chemicals and Products Database. Using the US-EPA's Cheminformatics Hazard Module, we identified that many of the nontarget compounds have predicted toxicity scores of "very high" for several end points related to human health. These aspects would have been overlooked using traditional targeted analysis methods, although more information is needed to ascertain whether the compounds identified through nontargeted analysis are of environmental or human health concern. As such, our approach enabled the identification of potentially hazardous compounds that, based on their hazard assessment score, merit follow-up investigations.

Computer-assisted multifactorial method development for the streamlined separation and analysis of multicomponent mixtures in (Bio)pharmaceutical settings.

The (bio)pharmaceutical industry is rapidly moving towards complex drug modalities that require a commensurate level of analytical enabling technologies that can be deployed at a fast pace. Unsystematic method development and unnecessary manual intervention remain a major barrier towards a more efficient deployment of meaningful analytical assay across emerging modalities. Digitalization and automation are key to streamline method development and enable rapid assay deployment. This review discusses the use of computer-assisted multifactorial chromatographic method development strategies for fast-paced downstream characterization and purification of biopharmaceuticals. Various chromatographic techniques such as reversed-phase liquid chromatography (RPLC), hydrophilic interaction liquid chromatography (HILIC), ion exchange chromatography (IEX), hydrophobic interaction chromatography (HIC), and supercritical fluid chromatography (SFC) are addressed and critically reviewed. The most significant parameters for retention mechanism modelling, as well as mapping the separation landscape for optimal chromatographic selectivity and resolution are also discussed. Furthermore, several computer-assisted approaches for optimization and development of chromatographic methods of therapeutics, including linear, nonlinear, and multifactorial modelling are outlined. Finally, the potential of the chromatographic modelling and computer-assisted optimization strategies are also illustrated, highlighting substantial productivity improvements, and cost savings while accelerating method development, deployment and transfer processes for therapeutic analysis in industrial settings.

Mass spectrometry of polymers: A tutorial review.

Ever since the inception of synthetic polymeric materials in the late 19th century, the number of studies on polymers as well as the complexity of their structures have only increased. The development and commercialization of new polymers with properties fine-tuned for specific technological, environmental, consumer, or biomedical applications requires powerful analytical techniques that permit the in-depth characterization of these materials. One such method with the ability to provide chemical composition and structure information with high sensitivity, selectivity, specificity, and speed is mass spectrometry (MS). This tutorial review presents and exemplifies the various MS techniques available for the elucidation of specific structural features in a synthetic polymer, including compositional complexity, primary structure, architecture, topology, and surface properties. Key to every MS analysis is sample conversion to gas-phase ions. This review describes the fundamentals of the most suitable ionization methods for synthetic materials and provides relevant sample preparation protocols. Most importantly, structural characterizations via one-step as well as hyphenated or multidimensional approaches are introduced and demonstrated with specific applications, including surface sensitive and imaging techniques. The aim of this tutorial review is to illustrate the capabilities of MS for the characterization of large, complex polymers and emphasize its potential as a powerful compositional and structural elucidation tool in polymer chemistry.

High-speed countercurrent chromatography with offline detection by electrospray mass spectrometry and nuclear magnetic resonance detection as a tool to resolve complex mixtures: A practical approach using Coffea arabica leaf extract.

INTRODUCTION: Many secondary metabolites isolated from plants have been described in the literature owing to their important biological properties and possible pharmacological applications. However, the identification of compounds present in complex plant extracts has remained a great scientific challenge, is often laborious, and requires a long research time with high financial cost. OBJECTIVES: The aim of this study was to develop a method that allows the identification of secondary metabolites in plant extracts with a high degree of confidence in a short period of time. MATERIAL AND METHODS: In this study, an ethanolic extract of Coffea arabica leaves was used to validate the proposed method. Countercurrent chromatography was chosen as the initial step for extraction fractionation using gradient elution. Resulting fractions presented a variation of compounds concentrations, allowing for statistical total correlation spectroscopy (STOCSY) calculations between liquid chromatography coupled with high-resolution tandem mass spectrometry (LC-HRMS/MS) and NMR across fractions. RESULTS: The proposed method allowed the identification of 57 compounds. Of the annotated compounds, 20 were previously described in the literature for the species and 37 were reported for the first time. Among the inedited compounds, we identified flavonoids, alkaloids, phenolic acids, coumarins, and terpenes. CONCLUSION: The proposed method presents itself as a valid alternative for the study of complex extracts in an effective, fast, and reliable way that can be reproduced in the study of other extracts.

Wrangling Whole Mixtures Risk Assessment: Recent Advances in Determining Sufficient Similarity.

Human health risk assessments for complex mixtures can address real-world exposures and protect public health. While risk assessors typically prefer whole mixture approaches over component-based approaches, data from the precise exposure of interest are often unavailable and surrogate data from a sufficiently similar mixture(s) are required. This review describes recent advances in determining sufficient similarity of whole, complex mixtures spanning the comparison of chemical features, bioactivity profiles, and statistical evaluation to determine "thresholds of similarity". Case studies, including water disinfection byproducts, botanical ingredients, and wildfire emissions, are used to highlight tools and methods. Limitations to application of sufficient similarity in risk-based decision making are reviewed and recommendations presented for developing best practice guidelines.

Assessment of the contribution of surfactants to mixture toxicity in French surface waters.

Surfactants are widely used 'down-the-drain' chemicals with the potential to occur at high concentrations in local water bodies and to be part of unintentional environmental mixtures. Recently, increased regulatory focus has been placed on the impacts of complex mixtures in aquatic environments and the substances that are likely to drive mixture risk. This study assessed the contribution of surfactants to the total mixture pressure in freshwater ecosystems. Environmental concentrations, collated from existing French monitoring data, were combined with estimated ecotoxicological thresholds to calculate hazard quotients (HQ) for each substance, and hazard indices (HI) for each mixture. Two scenarios were investigated to correct for concentrations below the limit of quantification (LOQ) in the dataset. The first (best-case) scenario assumed all values

Comprehensive Two-Dimensional Gas Chromatography with Peak Tracking for Screening of Constituent Biodegradation in Petroleum UVCB Substances.

Petroleum substances, as archetypical UVCBs (substances of unknown or variable composition, complex reaction products, or biological substances), pose a challenge for chemical risk assessment as they contain hundreds to thousands of individual constituents. It is particularly challenging to determine the biodegradability of petroleum substances since each constituent behaves differently. Testing the whole substance provides an average biodegradation, but it would be effectively impossible to obtain all constituents and test them individually. To overcome this challenge, comprehensive two-dimensional gas chromatography (GC × GC) in combination with advanced data-handling algorithms was applied to track and calculate degradation half-times (DT50s) of individual constituents in two dispersed middle distillate gas oils in seawater. By tracking >1000 peaks (representing ∼53-54% of the total mass across the entire chromatographic area), known biodegradation patterns of oil constituents were confirmed and extended to include many hundreds not currently investigated by traditional one-dimensional GC methods. Approximately 95% of the total tracked peak mass biodegraded after 64 days. By tracking the microbial community evolution, a correlation between the presence of functional microbial communities and the observed progression of DT50s between chemical classes was demonstrated. This approach could be used to screen the persistence of GC × GC-amenable constituents of petroleum substance UVCBs.

Geological context and human exposures to element mixtures in mining and agricultural settings in Colombia.

Anthropogenic and natural sources contribute to chemical mixtures in air, water, and soil, posing potential risks to the environment and human health. To understand the interplay between element profiles in the human body, geographical location, and associated economic activities, we carried out an observational analytic cross-sectional study. The study recruited 199 participants from three municipalities, two of which had gold-mining as their primary economic activity, while the other was dedicated to agricultural and other local activities not related to mining. The concentrations of a total of 30 elements in human hair samples and 21 elements in environmental soil samples were measured using various spectrometry techniques. Unsupervised clustering analysis using Self-Organizing Maps was applied to human hair samples to analyze element concentrations. Distinct clusters of individuals were identified based on their hair element profiles, which were mapped to geographical location and economic activities. While higher levels of heavy metals (Ag, As, Hg, and Pb) were observed in individuals engaged in mining activities in certain clusters, individuals in agricultural areas show higher concentrations of elements found in pesticides (Ba and Sr). However, the elemental composition of hair is influenced not only by the anthropogenic activities but also by the inherent geological context where people live. Our findings highlight the significance of accounting for environmental factors when evaluating human health risks, as the intricate mixture of elements can yield valuable insights for targeted health interventions.

Micronuclei frequency and exposure to chemical mixtures in three Colombian mining populations.

The Colombian mining industry has witnessed significant growth. Depending on the scale and mineral extracted, complex chemical mixtures are generated, impacting the health of occupationally exposed populations and communities near mining projects. Increasing evidence suggests that chromosomal instability (CIN) is an important link between the development of certain diseases and exposure to complex mixtures. To better understand the effects of exposure to complex mixtures we performed a biomonitoring study on 407 healthy individuals from four areas: three located in municipalities exploiting different-scale mining systems and a reference area with no mining activity. Large, medium, and small-scale mining systems were analyzed in Montelibano (Córdoba), artisanal and small-scale mining (ASGM) in Nechí (Antioquia), and a closed mining system in Aranzazu (Caldas). The reference area with no mining activity was established in Montería (Córdoba). ICP-MS measured multi-elemental exposure in hair, and CIN was evaluated using the cytokinesis-block micronucleus technique (MNBN). Exposure to mixtures of chemical elements was comparable in workers and residents of the mining areas but significantly higher compared to reference individuals. In Montelibano, increased MNBN frequencies were associated with combined exposure to Se, Hg, Mn, Pb, and Mg. This distinct pattern significantly differed from other areas. Specifically, in Nechí, Cr, Ni, Hg, Se, and Mg emerged as the primary contributors to elevated frequencies of MNBN. In contrast, a combination of Hg and Ni played a role in increasing MNBN in Aranzazu. Interestingly, Se consistently correlated with increased MNBN frequencies across all active mining areas. Chemical elements in Montelibano exhibit a broader range compared to other mining zones, reflecting the characteristics of the high-impact and large-scale mining in the area. This research provides valuable insights into the effects of exposure to chemical mixtures, underscoring the importance of employing this approach in the risk assessment of communities, especially those from residential areas.

Geospatial pattern of topsoil pollution and multi-endpoint toxicity in the petrochemical area of Augusta-Priolo (eastern Sicily, Italy).

The present study was aimed at identifying geospatial patterns of pollutants including concentrations and toxicity as complex environmental mixtures, in topsoil samples close to petrochemical facilities in the heavily industrialized area of Augusta and Priolo in south-eastern Sicily (Italy). Elemental analysis of soil was conducted by ICP-MS for 23 metals and 16 rare earth elements (REEs). Organic analyses were primarily focused on polycyclic aromatic hydrocarbons (PAHs) (16 parent homologs) and total aliphatic hydrocarbons (C10 - C40). Topsoil samples were tested for toxicity in multiple bioassay models including: 1) developmental defects and cytogenetic anomalies in sea urchin Sphaerechinus granularis early life stages; 2) growth inhibition of diatom Phaeodactylum tricornutum; 3) mortality in nematode Caenorhabditis elegans; and 4) induction of mitotic abnormalities in onion Allium cepa. Samples collected at sites closest to defined petrochemical facilities were highest in select pollutants and correlated with biological effects in different toxicity endpoints. A noteworthy finding was the increased level of total REEs in sites closest to petrochemical facilities, suggesting their contributions to identifying petrochemical sources of pollutants to the environment. The combined data obtained in the different bioassays allowed exploration of geospatial patterns of effect in biota as a function of contaminant levels. In conclusion, this study provides consistent data of soil toxicity, metal and REE contamination at Augusta-Priolo sampling sites, and may provide an appropriate baseline for epidemiological studies on high incidences of congenital birth defects in the area and identification of at-risk localities.

A Temporal Graph Model to Predict Chemical Transformations in Complex Dissolved Organic Matter.

Dissolved organic matter (DOM) is a complex mixture of thousands of natural molecules that undergo constant transformation in the environment, such as sunlight induced photochemical reactions. Despite molecular level resolution from ultrahigh resolution mass spectrometry (UHRMS), trends of mass peak intensities are currently the only way to follow photochemically induced molecular changes in DOM. Many real-world relationships and temporal processes can be intuitively modeled using graph data structures (networks). Graphs enhance the potential and value of AI applications by adding context and interconnections allowing the uncovering of hidden or unknown relationships in data sets. We use a temporal graph model and link prediction to identify transformations of DOM molecules in a photo-oxidation experiment. Our link prediction algorithm simultaneously considers educt removal and product formation for molecules linked by predefined transformation units (oxidation, decarboxylation, etc.). The transformations are further weighted by the extent of intensity change and clustered on the graph structure to identify groups of similar reactivity. The temporal graph is capable of identifying relevant molecules subject to similar reactions and enabling to study their time course. Our approach overcomes previous data evaluation limitations for mechanistic studies of DOM and leverages the potential of temporal graphs to study DOM reactivity by UHRMS.

Earlier biomarkers in fish evidencing stress responses to metal and organic pollution along the Doce River Basin.

The Doce River Basin (DRB) represents a well-described watershed in terms of contamination by metals, especially after a major environmental disaster of a mining tailing dam failure. Despite the massive mortality of the ichthyofauna, very few studies addressed the risks to the health of wild fish exposed to complex mixtures of pollutants from multiple sources. The present study proposed to investigate earlier responses of fish for assessing the impacts of multiple sources of pollution, considering: different niches of fish and target organs; and the influence of seasonality, associated with their probable sources of pollution. To achieve that, fish were collected along the DRB, and biomarkers responses were assessed in target organs and correlated with the levels of inorganic and organic contaminants. As one of the most prominent responses, fishes from the Upper DRB showed the highest expression of the metallothionein and oxidative stress parameters which were related to the higher levels of metals in this region due to the proximity of mining activities. On the other hand, higher levels of DNA damage and increased AChE activity from fish sampled in the Mid and Lower DRB were more associated with organic contaminants, from other sources of pollution than mining residues. The integrated biomarker responses also revealed seasonal variations, with higher values in fishes from the dry season, and pelagic fish showing greater variation within the seasons. The multivariate analysis integrating suitable biomarkers with chemical data represented an adequate strategy for assessing the ecological risks in the DRB, allowing the identification of distinct spatio-temporal impacts from multiple sources of contaminants. The continued exposure of the ichthyofauna representing future risks reinforces the need for ecological restoration and the protection of the fauna from the Doce River.

Chemical Element Mixtures and Kidney Function in Mining and Non-Mining Settings in Northern Colombia.

The exposure to chemical mixtures is a problem of concern in developing countries and it is well known that the kidney is the major target organ for toxic elements. This cross-sectional study aimed to estimate the individual and composite mixture effect of a large number of chemical elements on kidney function in gold-mining and surrounding non-mining populations in northeast Colombia. We measured concentrations of 36 chemical elements in hair as indicators of chronic exposure from 199 adult participants. We estimated the effect of exposure to mixtures of chemical elements on estimated glomerular filtration rate (eGFR) using weighted quantile sum regression (WQS). The WQS index of the mixture was associated with reduced eGFR (Coefficient -2.42; 95%CI: -4.69, -0.16) being Be, Cd, Pb, As, and Mn, the principal contributors of the toxic mixture. Mining activities and Hg concentration were not associated with decreased kidney function. Our results suggest that complex mixtures of chemical elements, mainly heavy metals, act as nephrotoxic in these populations and therefore the analysis of chemical element mixtures is a better approach to identify environmental and occupational chemical risks for kidney damage.

Hormesis mediates platelet-rich plasma and wound healing.

Platelet-rich plasma (PRP) has become an accepted and general wound healing approach with an extremely wide range of applications. Despite considerable diversity in the composition of platelet-rich plasma products that are applied in specific wound healing usage, it is widely recognised that such diverse platelet-rich plasma complex mixtures routinely display hormetic-like biphasic concentrations that are independent of the tissue treated and endpoints measured. The present paper is the first to place the area of platelet-rich plasma-biomedical research and applications within an hormetic framework. The platelet-rich plasma area is also unique as it represents the application of the hormetic concept to the issue of complex biological mixtures.

Hepatoprotective Activity of Lignin-Derived Polyphenols Dereplicated Using High-Resolution Mass Spectrometry, In Vivo Experiments, and Deep Learning.

Chronic liver diseases affect more than 1 billion people worldwide and represent one of the main public health issues. Nonalcoholic fatty liver disease (NAFLD) accounts for the majority of mortal cases, while there is no currently approved therapeutics for its treatment. One of the prospective approaches to NAFLD therapy is to use a mixture of natural compounds. They showed effectiveness in alleviating NAFLD-related conditions including steatosis, fibrosis, etc. However, understanding the mechanism of action of such mixtures is important for their rational application. In this work, we propose a new dereplication workflow for deciphering the mechanism of action of the lignin-derived natural compound mixture. The workflow combines the analysis of molecular components with high-resolution mass spectrometry, selective chemical tagging and deuterium labeling, liver tissue penetration examination, assessment of biological activity in vitro, and computational chemistry tools used to generate putative structural candidates. Molecular docking was used to propose the potential mechanism of action of these structures, which was assessed by a proteomic experiment.

How Well Do We Handle the Sample Preparation, FT-ICR Mass Spectrometry Analysis, and Data Treatment of Atmospheric Waters?

FT-ICR MS (Fourier-transform ion cyclotron resonance mass spectrometry) analysis has shown great potential to aid in the understanding of the extremely high molecular diversity of cloud water samples. The main goal of this work was to determine the differences in terms of formula assignment for analytical (i.e., measurement replicates) and experimental replicates of a given cloud water sample. The experimental replicates, obtained by solid phase extraction, were also compared to the results obtained for freeze-dried samples to evaluate whether the presence of salts interferes with the analysis. Two S/N ratios, generally adopted for atmospheric samples, were evaluated, and three different algorithms were used for assignment: DataAnalysis 5.3 (Bruker), Composer (Sierra Analytics), and MFAssignR (Chemical Advanced Resolution Methods Lab). In contrast to other works, we wanted to treat this comparison from the point of view of users, who usually must deal with a simple list of m/z ratios and intensity with limited access to the mass spectrum characteristics. The aim of this study was to establish a methodology for the treatment of atmospheric aqueous samples in light of the comparison of three different software programs, to enhance the possibility of data comparison within samples.

Ultrafast 2D NMR for the analysis of complex mixtures.

2D NMR is extensively used in many different fields, and its potential for the study of complex biochemical or chemical mixtures has been widely demonstrated. 2D NMR gives the ability to resolve peaks that overlap in 1D spectra, while providing both structural and quantitative information. However, complex mixtures are often analysed in situations where the data acquisition time is a crucial limitation, due to an ongoing chemical reaction or a moving sample from a hyphenated technique, or to the high-throughput requirement associated with large sample collections. Among the great diversity of available fast 2D methods, ultrafast (or single-scan) 2D NMR is probably the most general and versatile approach for complex mixture analysis. Indeed, ultrafast NMR has undergone an impressive number of methodological developments that have helped turn it into an efficient analytical tool, and numerous applications to the analysis of mixtures have been reported. This review first summarizes the main concepts, features and practical limitations of ultrafast 2D NMR, as well as the methodological developments that improved its analytical potential. Then, a detailed description of the main applications of ultrafast 2D NMR to mixture analysis is given. The two major application fields of ultrafast 2D NMR are first covered, i.e., reaction/process monitoring and metabolomics. Then, the potential of ultrafast 2D NMR for the analysis of hyperpolarized mixtures is described, as well as recent developments in oriented media. This review focuses on high-resolution liquid-state 2D experiments (including benchtop NMR) that include at least one spectroscopic dimension (i.e., 2D spectroscopy and DOSY) but does not cover in depth applications without spectral resolution and/or in inhomogeneous fields.

The Path to UVCB Ecological Risk Assessment: Grappling with Substance Characterization.

Substances of unknown or variable composition, complex reaction products, and biological materials (UVCBs) pose a unique challenge to regulators and to product registrants, who are required to characterize their fate, exposure, hazard, and potential risks to human health and the environment. To address these challenges and ensure an efficient and fit-for-purpose process, it is proposed that the ecological risks of UVCBs be assessed following a tiered strategy. The development of this approach required exploring how substance composition ties into hazard and exposure information and determining the extent to which a UVCB needs to be characterized to ensure a robust risk assessment. The present study highlights the key aspects of this new method. It presents how a tiered substance characterization approach can be integrated into broader UVCB risk-assessment schemes to encourage an examination of data needs before a full substance characterization is performed. The first tier of the characterization process, Tier 0, is a fundamental step that includes data from basic, lower-resolution compositional analyses. Tier 0 assessments can be used to inform hazard and exposure for any substance of interest. The need for more sophisticated, higher-tier characterization is determined by the level of uncertainty of the risk assessment. The next step will integrate a tiered exposure assessment into the characterization scheme featured in the present study, to create a more complete risk-assessment framework. Environ Toxicol Chem 2022;41:2649-2657. © 2022 Her Majesty the Queen in Right of Canada, Health and Environmental Sciences Institute and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Environment and Climate Change Canada.