1
|
Hörchner S, Forberg C, Oehlmann J, Oetken M. Wastewater treatment plant effluents as an obstacle to the full recovery of restored river sections. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2025; 378:126483. [PMID: 40398805 DOI: 10.1016/j.envpol.2025.126483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2024] [Revised: 02/12/2025] [Accepted: 05/18/2025] [Indexed: 05/23/2025]
Abstract
Freshwater ecosystems are impacted by multiple human activities, with chemical pollution emerging as a significant concern alongside well-documented stressors like climate change. While river restorations have been conducted to improve the structural condition of rivers, their ecological efficacy proved to be limited and potentially masked by chemical pollution. Conventional wastewater treatment plants (WWTPs) are unable to fully eliminate pollutants, resulting in insufficient water quality in aquatic systems, particularly in small, sensitive rivers with low dilution capacities, posing growing risks to biodiversity. This study investigated the ecotoxicological impact of WWTP effluents on downstream restored river sections. Despite the implementation of restoration measures, these river sections remained in a degraded ecological condition, likely due to the presence of chemical pollution originating from upstream WWTPs. In vitro bioassays were used to assess baseline toxicity, estrogenicity, and dioxin-like activity in water and sediment samples. Due to the complex pollution pattern, it was not possible to attribute the observed effects to the WWTPs alone. However, the results indicate that WWTP discharges act as a stressor on a larger spatial scale and may hinder ecological recovery in restored sections by prevailing toxicity levels. WWTP effluents, along with pollution from e.g. agricultural runoff, are likely obstacles to improving aquatic biodiversity. To support biodiversity recovery, integrated management approaches are necessary, focusing on reducing the impact of WWTP discharges through advanced treatment technologies alongside hydromorphological restoration efforts.
Collapse
Affiliation(s)
- Sarah Hörchner
- Department Aquatic Ecotoxicology, Goethe University Frankfurt, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany; Competence Center Water Hesse, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany.
| | - Christian Forberg
- Department Aquatic Ecotoxicology, Goethe University Frankfurt, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany; Department Evolutionary Ecology and Environmental Toxicology, Goethe University Frankfurt, Max-von-Laue-Str. 13, Frankfurt am Main, 60438Germany
| | - Jörg Oehlmann
- Department Aquatic Ecotoxicology, Goethe University Frankfurt, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany; Competence Center Water Hesse, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany
| | - Matthias Oetken
- Department Aquatic Ecotoxicology, Goethe University Frankfurt, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany; Competence Center Water Hesse, Max-von-Laue-Str. 13, Frankfurt am Main, 60438, Germany
| |
Collapse
|
2
|
Ronda K, Gauthier J, Singaravadivel K, Costa PM, Downey K, Wolff WW, Lysak DH, Pellizzari J, Meulen OV, Steiner K, Jenne A, Bastawrous M, Ng Z, Haber A, Goerling B, Busse V, Busse F, Elliot C, Mabury S, Ateia M, Muir DCG, Letcher RJ, Krishnamurthy K, Kleywegt S, Jobst KJ, Simpson MJ, Simpson AJ. NMR as a Discovery Tool: Exploration of Industrial Effluents Discharged Into the Environment. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2025. [PMID: 40360259 DOI: 10.1002/mrc.5527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2025] [Accepted: 04/28/2025] [Indexed: 05/15/2025]
Abstract
NMR provides unprecedented molecular information, urgently needed by environmental researchers and policy makers. However, NMR is underutilized in environmental sciences due to the lack of available technologies, limited environmental-specific training opportunities, and easy-to-use workflows. NMR has considerable potential as a discovery tool for novel pollutants, and by-products, exemplified by the recent discovery of the degradation by-product of a rubber additive, 6PPD-quinone, now considered one of the most toxic compounds presently known. This work represents a proof-of-concept case study highlighting the use of NMR to profile effluents from 38 industries across Ontario, Canada. Wastewater effluents from various industrial sectors were analyzed using several 1D and 2D 1H/13C NMR and 19F experiments and were screened both unconcentrated and after lyophilization. Common species could be identified using human metabolic NMR databases, but environmental-specific NMR databases desperately need further development. An example of manually identifying unusual NMR signatures is included; these resulted from phosphinic and phosphonic acids originating from the electroplating industry, for which the environmental impacts are not well understood. Basic 1H NMR quantification is performed using ERETIC, while an optimized approach combining relaxation agents and steady-state-free-precession 19F NMR, to reduce detection limits (at 500 MHz) to sub-ppb (< 1 μg/L) in under 15 min, is demonstrated. The future potential of benchtop NMR (80 MHz) is also considered. This paper represents a guide to others interested in applying NMR spectroscopy to environmental media and demonstrates the potential of NMR as a complementary tool to assist MS in environmental pollutant and by-product discovery.
Collapse
Affiliation(s)
- Kiera Ronda
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Jeremy Gauthier
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| | - Khanisha Singaravadivel
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Peter M Costa
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Katelyn Downey
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - William W Wolff
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Daniel H Lysak
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Jacob Pellizzari
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Owen Vander Meulen
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Katrina Steiner
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Amy Jenne
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Monica Bastawrous
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | - Zainab Ng
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
| | | | | | | | - Falko Busse
- Bruker Switzerland AG, Faellanden, Switzerland
| | | | - Scott Mabury
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| | - Mohamed Ateia
- Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas, USA
| | - Derek C G Muir
- Canada Centre for Inland Waters, Environment and Climate Change Canada, Burlington, ON, Canada
| | - Robert J Letcher
- Ecotoxicological and Wildlife Health Division, Environment and Climate Change Canada, National Wildlife Research Centre, Carleton University, Ottawa, ON, Canada
| | | | - Sonya Kleywegt
- Technical Assessment and Standards Development Branch, Ontario Ministry of the Environment, Conservation and Parks, Toronto, ON, Canada
| | - Karl J Jobst
- Department of Chemistry, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Myrna J Simpson
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| | - Andre J Simpson
- Environmental NMR Centre, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, ON, Canada
- Department of Chemistry, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
3
|
Sun J, Zhang K, Zhang H. Predicting sorption of diverse organic compounds in soil-water systems: Meta-analysis, machine learning modeling, and global soil mapping. JOURNAL OF HAZARDOUS MATERIALS 2025; 488:137480. [PMID: 39908761 DOI: 10.1016/j.jhazmat.2025.137480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2024] [Revised: 01/18/2025] [Accepted: 02/02/2025] [Indexed: 02/07/2025]
Abstract
In recent decades, the environmental detection of various organic compounds (OCs) has highlighted the limitations of conventional soil-water sorption models, which simplify complex experimental conditions and often overlook OCs with polyfunctional and ionizable structures. To address these shortcomings, we compiled a comprehensive soil-water sorption dataset encompassing 20,945 data points for 419 OCs with various functional groups and 1037 different soils. Meta-analysis of the dataset revealed the trends of soil sorption associated with OC substructures, soil properties, and solution conditions. Machine learning models employing the XGBoost algorithm, in conjunction with MACCS fingerprints and experimental conditions, were developed to cover the entire spectrum of speciation for cationic, neutral, and anionic species. Among these, the individual models tailored to each speciation achieved an overall root-mean-square-error value of 0.32 for log Kd. Model interpretation revealed that the models correctly understood the contributions of various substructures, such as multiple aromatic rings and nitrogen or oxygen atoms, to sorption. The models were also found to accurately capture isotherm nonlinearity and the pH effect on the sorption of ionizable OCs. Finally, utilizing soil properties from the Harmonized World Soil Database, the models predicted the sorption of diverse OCs based on global soil properties under simulated environmental scenarios.
Collapse
Affiliation(s)
- Jiachun Sun
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Kai Zhang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Huichun Zhang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
| |
Collapse
|
4
|
Rigutto G, Galkina E, Hayes LV, Bălan SA. Identifying Potential Chemicals of Concern in Children's Products in a Regulatory Context: A Systematic Evidence Mapping Approach. ENVIRONMENTAL HEALTH PERSPECTIVES 2025; 133:56001. [PMID: 40152882 PMCID: PMC12063794 DOI: 10.1289/ehp15394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 02/04/2025] [Accepted: 03/20/2025] [Indexed: 03/29/2025]
Abstract
BACKGROUND Children's vulnerability to chemical toxicant exposures demands strong consideration of the chemical composition of products designed for and marketed toward them. Inadequacies in health-protective legislation and lack of mandatory ingredient disclosure in most children's products have created significant gaps in protection and oversight. Scientific literature can provide insight into the chemical constituency of children's products that may be useful for prioritizing future regulatory efforts. OBJECTIVE We aimed to present a proof of concept for applying systematic evidence mapping methodology to identify which chemicals of potential concern have been reported in the scientific literature to be present in products marketed toward children, compile a compendium of data to inform future regulatory efforts, and identify research needs. METHODS We conducted a broad, all-encompassing survey of the available literature from four databases to identify chemicals present in children's products. Using systematic evidence mapping methodologies, we constructed a database of children's products and their chemical constituents (termed "product-chemical combinations") based on a broad survey of current and relevant environmental health literature. Our study focused on chemicals listed on the California Safer Consumer Products Program's Candidate Chemicals List, which includes chemicals with one or more known hazard traits. We then conducted an exploratory data analysis of product category and product-chemical combination frequencies to identify common chemicals in specific products. RESULTS Our systematic evidence mapping identified 206 potentially hazardous chemicals in children's products, 170 of which were found in toys. In total, we found 1,528 distinct product-chemical combinations; 582 product-chemical combinations included chemicals known to be hazardous or potentially hazardous. Ortho-phthalates in plastic toys, parabens in children's creams and lotions, and bisphenols in both baby bottles and teethers were the most frequently encountered product-chemical combinations of potential concern. DISCUSSION The frequently reported presence of endocrine-disrupting chemicals in multiple types of children's products raises concerns for aggregate exposures and reveals gaps in regulatory protections for this sensitive subpopulation. Our reproducible and systematic evidence-based approach serves as a case study that can guide other prioritization efforts for transparent regulatory action aimed at improving the safety of chemicals in consumer products. https://doi.org/10.1289/EHP15394.
Collapse
Affiliation(s)
- Gabrielle Rigutto
- Safer Consumer Products Program, California Department of Toxic Substances Control, Sacramento, California, USA
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, California, USA
| | - Elena Galkina
- Safer Consumer Products Program, California Department of Toxic Substances Control, Berkeley, California, USA
| | - Logan V. Hayes
- Safer Consumer Products Program, California Department of Toxic Substances Control, Sacramento, California, USA
| | - Simona Andreea Bălan
- Safer Consumer Products Program, California Department of Toxic Substances Control, Berkeley, California, USA
| |
Collapse
|
5
|
Lara-Martín PA, Schinkel L, Eberhard Y, Giger W, Berg M, Hollender J. Suspect and Nontarget Screening of Organic Micropollutants in Swiss Sewage Sludge: A Nationwide Survey. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:7688-7698. [PMID: 40198312 DOI: 10.1021/acs.est.4c13217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/10/2025]
Abstract
The increasing amount of sewage sludge generated during wastewater treatment poses both growing management challenge and environmental issues. Sludge with many co-occurring contaminants is often destined to land application which raises concern regarding human and environmental health. It is also a good integrator in time and space and can provide valuable information on consumption pattern and change over time. Here, we have conducted suspect and nontarget screening (SNTS) in sludge from 29 wastewater treatment plants (WWTPs) covering 30% of the Swiss population. Over 500 contaminants were identified and up to 382 quantified, with concentrations ranging from a few ng/g to several thousand ng/g, which translated into total annual loads of approximately 5 g of micropollutants per Swiss citizen. The distribution of detected substances was dominated by pharmaceuticals in terms of number of compounds (>250) and personal care products in terms of concentration (e.g., 75 μg/g for linoleic acid). Homologous series analysis revealed the presence of multiple classes of surfactants among those compounds with the highest signal intensities in sludge. Principal component analysis and hierarchical clustering showed that spatial distribution of contaminants across Switzerland was not homogeneous, while Pearson correlation indicated that changes can be attributed to different anaerobic digestion times in WWTPs.
Collapse
Affiliation(s)
- Pablo A Lara-Martín
- Department of Physical Chemistry, Institute of Marine Research (INMAR), International Campus of Excellence of the Sea (CEIMAR), Faculty of Marine and Environmental Sciences, University of Cadiz, Puerto Real 11510, Spain
| | - Lena Schinkel
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Yves Eberhard
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Walter Giger
- Giger Research Consulting, 8049 Zürich, Switzerland
| | - Michael Berg
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Juliane Hollender
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
- Institute of Biogeochemistry and Pollutant Dynamics (IBP), ETH Zurich, 8092 Zurich, Switzerland
| |
Collapse
|
6
|
Shi X, Sobek A, Benskin JP. Multidimensional-Constrained Suspect Screening of Hydrophobic Contaminants Using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Ion Mobility-Mass Spectrometry. Anal Chem 2025; 97:5434-5438. [PMID: 40047663 PMCID: PMC11923942 DOI: 10.1021/acs.analchem.4c06234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2025]
Abstract
Suspect screening strives to rapidly monitor a large number of substances in a sample using mass spectral libraries. For hydrophobic organic contaminants (HOCs), these libraries are traditionally based on electron ionization mass spectra. However, with the growing use of state-of-the-art mass spectrometers, which often use alternative ionization approaches and separation techniques, new suspect screening workflows and libraries are urgently needed. This study established a new suspect screening library for 1,590 HOCs, including exact mass and a combination of measured and model-predicted values for retention time (RT) and collision cross section (CCS). The accuracy of in silico predictions was assessed using standards for 102 HOCs. Thereafter, using gas chromatography-atmospheric pressure chemical ionization-ion mobility-mass spectrometry, a suspect screening workflow constrained by the full scan mass spectrum of (quasi-)molecular ions (including isotope patterns), RT, CCS, and fragmentation mass spectra, together with a continuous scoring system, was established to reduce false positives and improve identification confidence. Application of the method to fortified and standard reference sediment samples demonstrated true positive rates of 79% and 64%, respectively, with all false positives attributed to suspect isomers. This study offers a new workflow for improved suspect screening of HOCs using multidimensional information and highlights the need to enrich mass spectral databases and extend the applicable chemical space of current in silico tools to hydrophobic substances.
Collapse
Affiliation(s)
- Xiaodi Shi
- Department of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| | - Anna Sobek
- Department of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| | - Jonathan P Benskin
- Department of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| |
Collapse
|
7
|
Shi X, Langberg HA, Sobek A, Benskin JP. Exploiting Molecular Ions for Screening Hydrophobic Contaminants in Sediments Using Gas Chromatography-Atmospheric Pressure Chemical Ionization-Ion Mobility-Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:4699-4708. [PMID: 39996462 PMCID: PMC11912331 DOI: 10.1021/acs.est.4c13059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2024] [Revised: 02/14/2025] [Accepted: 02/14/2025] [Indexed: 02/26/2025]
Abstract
Hydrophobic organic contaminants (HOCs) are conventionally screened by matching electron ionization (EI) mass spectra acquired using gas chromatography-mass spectrometry (GC-MS) to reference spectra. However, extensive in-source fragmentation hampers de novo structure elucidation of novel substances that are absent from EI databases. To address this problem, a new method based on GC-atmospheric pressure chemical ionization (APCI) coupled to ion mobility-high resolution mass spectrometry (IM-HRMS) was developed for simultaneous target, suspect, and nontarget screening of HOCs. Of 102 target chemicals, 85.3% produced (quasi-)molecular ions as base peaks, while 71.6% displayed method detection limits lower than those of GC-EI-low resolution MS. The optimized method was applied to standard reference sediment and sediments from the Baltic Sea, an Arctic shelf, and a Norwegian lake. In total, we quantified 56 target chemicals with concentrations ranging from 4.86 pg g-1 to 124 ng g-1 dry weight. Further, using a combination of full scan mass spectrum, retention time, collision cross section (CCS), and fragmentation spectrum, a total of 54 suspects were identified at Confidence Level (CL) 2. Among the remaining features, 169 were prioritized using a halogen-selective CCS cutoff (100 Å2 + 20% mass), leading to annotation of 54 substances (CL ≤ 3). Notably, a suite of fluorotelomer thiols, disulfides, and alkyl sulfones were identified in sediment (CL 1-2) for the first time. Overall, this work demonstrates the potential of GC-APCI-IM-HRMS as a next-generation technique for resolving complex HOC mixtures in environmental samples through exploitation of molecular ions.
Collapse
Affiliation(s)
- Xiaodi Shi
- Department
of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| | - Håkon A. Langberg
- Geotechnics
and Environment, Norwegian Geotechnical
Institute, Oslo 0484, Norway
| | - Anna Sobek
- Department
of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| | - Jonathan P. Benskin
- Department
of Environmental Science, Stockholm University, Stockholm 10691, Sweden
| |
Collapse
|
8
|
Zhang Z, Li Z, Nan J, Ouyang J, Chen X, Wang H, Wang A. Evaluating advancements and opportunities in electro-assisted biodehalogenation of emerging halogenated contaminants. BIORESOURCE TECHNOLOGY 2025; 419:132011. [PMID: 39725360 DOI: 10.1016/j.biortech.2024.132011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Revised: 12/06/2024] [Accepted: 12/20/2024] [Indexed: 12/28/2024]
Abstract
Electro-assisted biodehalogenation (EASB) as a biostimulation strategy can accelerate the slow attenuation of emerging halogenated contaminants (EHCs) in anaerobic aqueous environments. A timely review is urgent to evaluate the knowledge gaps and potential opportunities, further facilitating its design and application. Till now, EASB achieves promising progress in accelerating biohalogenation rates, promoting the detoxification of EHCs to cope with unfavourable environments and mitigating greenhouse gas emissions. However, EASB of EHCs still faces several knowledge gaps. Exploring crucial microbes and deciphering insights into dehalogenase characteristics and extracellular electron transfer (EET) pathways remain the prominent task for EASB of EHCs. Moreover, microbial ecological relationships and intricate environmental factors affecting performances and applications are largely underexplored. The emergence of emerging tools holds promises for sorting the intricate changes and addressing these knowledge gaps. Judicious use of emerging tools will rejuvenate EASB strategy, from EET to scale-up, to purposefully and effectively address cascading EHCs.
Collapse
Affiliation(s)
- Zimeng Zhang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Zhiling Li
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China.
| | - Jun Nan
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Jia Ouyang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Xueqi Chen
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Hongcheng Wang
- School of Civil & Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China
| | - Aijie Wang
- State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China; School of Civil & Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen 518055, China.
| |
Collapse
|
9
|
Jyoti S, Murmu A, Matore BW, Singh J, Roy PP. Exploring QSTR and q-RASTR modeling of agrochemical toxicity on cabbage for environmental safety and human health. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2025; 32:5504-5520. [PMID: 39930099 DOI: 10.1007/s11356-025-36033-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Accepted: 01/26/2025] [Indexed: 02/28/2025]
Abstract
Cabbage is a widely consumed vegetable in the human diet because of its low cost, broad availability and high nutritional value. The rising use of pesticides in food production creates a need to assess vegetable toxicity, which primarily results from residues in food products and environmental exposure. The study aims to offer exploration of vegetable toxicity in cabbage with the help of reliable QSTR and q-RASTR models. All the developed models were robust and predictive enough (Q2LOO = 0.7491-0.8164, Q2F1 = 0.5243-0.6253, Q2F2 = 0.513-0.617, MAEext = 0.495-0.690). Furthermore, the reliability and predictability of models were assessed and confirmed by applicability domain and prediction reliability indicator analysis. Additionally, different machine learning models were developed to making effective predictions and multiple linear regression (MLR) comparison. Consensus approach was advocated data gap filling for USEPA ECOTOX database compounds. The most and least toxic compounds from both MLR model predictions were prioritized and analyzed. Mechanistic interpretation highlighted the structural features or fragments responsible for the agrochemical toxicity and a safe approach for designing green chemicals minimizing the toxicity. This first reported study can be useful for toxicity profiling, data gap filling and designing safer and green agrochemical for minimizing vegetable toxicity, healthy human life and environmental safety.
Collapse
Affiliation(s)
- Surbhi Jyoti
- Laboratory of Drug Discovery and Ecotoxicology, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, 495009, India
| | - Anjali Murmu
- Laboratory of Drug Discovery and Ecotoxicology, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, 495009, India
| | - Balaji Wamanrao Matore
- Laboratory of Drug Discovery and Ecotoxicology, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, 495009, India
| | - Jagadish Singh
- Laboratory of Drug Discovery and Ecotoxicology, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, 495009, India
| | - Partha Pratim Roy
- Laboratory of Drug Discovery and Ecotoxicology, Department of Pharmacy, Guru Ghasidas Vishwavidyalaya (A Central University), Bilaspur, 495009, India.
| |
Collapse
|
10
|
Arturi K, Harris EJ, Gasser L, Escher BI, Braun G, Bosshard R, Hollender J. MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data. J Cheminform 2025; 17:14. [PMID: 39891244 PMCID: PMC11786476 DOI: 10.1186/s13321-025-00950-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Accepted: 01/06/2025] [Indexed: 02/03/2025] Open
Abstract
MLinvitroTox is an automated Python pipeline developed for high-throughput hazard-driven prioritization of toxicologically relevant signals detected in complex environmental samples through high-resolution tandem mass spectrometry (HRMS/MS). MLinvitroTox is a machine learning (ML) framework comprising 490 independent XGBoost classifiers trained on molecular fingerprints from chemical structures and target-specific endpoints from the ToxCast/Tox21 invitroDBv4.1 database. For each analyzed HRMS feature, MLinvitroTox generates a 490-bit bioactivity fingerprint used as a basis for prioritization, focusing the time-consuming molecular identification efforts on features most likely to cause adverse effects. The practical advantages of MLinvitroTox are demonstrated for groundwater HRMS data. Among the 874 features for which molecular fingerprints were derived from spectra, including 630 nontargets, 185 spectral matches, and 59 targets, around 4% of the feature/endpoint relationship pairs were predicted to be active. Cross-checking the predictions for targets and spectral matches with invitroDB data confirmed the bioactivity of 120 active and 6791 nonactive pairs while mislabeling 88 active and 56 non-active relationships. By filtering according to bioactivity probability, endpoint scores, and similarity to the training data, the number of potentially toxic features was reduced by at least one order of magnitude. This refinement makes the analytical confirmation of the toxicologically most relevant features feasible, offering significant benefits for cost-efficient chemical risk assessment.Scientific Contribution:In contrast to the classical ML-based approaches for toxicity prediction, MLinvitroTox predicts bioactivity for HRMS features (i.e., distinct m/z signals) based on MS2 fragmentation spectra rather than the chemical structures from the identified features. While the original proof of concept study was accompanied by the release of a MLinvitroTox v1 KNIME workflow, in this study, we release a Python MLinvitroTox v2 package, which, in addition to automation, expands functionality to include predicting toxicity from structures, cleaning up and generating chemical fingerprints, customizing models, and retraining on custom data. Furthermore, as a result of improvements in bioactivity data processing, realized in the concurrently released pytcpl Python package for the custom processing of invitroDBv4.1 input data used for training MLinvitroTox, the current release introduces enhancements in model accuracy, coverage of biological mechanistic targets, and overall interpretability.
Collapse
Affiliation(s)
- Katarzyna Arturi
- Department of Environmental Chemistry, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Überlandstrasse 133, 8600, Dübendorf, Switzerland.
| | - Eliza J Harris
- Swiss Data Science Center (SDSC), Andreasstrasse 5, 8092, Zürich, Switzerland
- Now at: Climate and Environmental Physics Division, University of Bern, Sidlerstrasse 5, 3012, Bern, Switzerland
| | - Lilian Gasser
- Swiss Data Science Center (SDSC), Andreasstrasse 5, 8092, Zürich, Switzerland
| | - Beate I Escher
- Cell Toxicology, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, 04318, Leipzig, Germany
| | - Georg Braun
- Cell Toxicology, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, 04318, Leipzig, Germany
| | - Robin Bosshard
- Department of Computer Science, Eidgenössische Technische Hochschule Zürich (ETH Zürich), Universitätstrasse 6, 8092, Zürich, Switzerland
| | - Juliane Hollender
- Department of Environmental Chemistry, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Überlandstrasse 133, 8600, Dübendorf, Switzerland.
- Institute of Biogeochemistry and Pollution Dynamics, Eidgenössische Technische Hochschule Zürich (ETH Zürich), Rämistrasse 101, 8092, Zürich, Switzerland.
| |
Collapse
|
11
|
Liu Z, Shang L, Huang K, Yue Z, Han AY, Wang D, Zhang H. Combining Group Contribution Method and Semisupervised Learning to Build Machine Learning Models for Predicting Hydroxyl Radical Rate Constants of Water Contaminants. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2025; 59:857-868. [PMID: 39723902 DOI: 10.1021/acs.est.4c11950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2024]
Abstract
Machine learning is an effective tool for predicting reaction rate constants for many organic compounds with the hydroxyl radical (HO•). Previously reported models have achieved relatively good performance, but due to scarce data (<1400 records), the applicability domain (AD) has been significantly limited. To address this limitation, we curated a much larger experimental data set (Primary data set), which contains 2358 kinetic records. We then employed both the group contribution method (GCM) and a semisupervised learning (SSL) strategy to add new data points, aiming to effectively expand the model's AD while improving model performance. The results indicated that GCM improved the model's performance for chemicals outside the AD, while SSL expanded the model's AD. The final model, after incorporating 147,168 new data points, achieved an R2 = 0.77, root-mean-square-error = 0.32, and mean-absolute-error = 0.24 on the test set. Importantly, the AD was expanded by 117% compared to the model developed solely based on the Primary data set, and the final model can be reliably applied to more than 560,000 chemicals from the DSSTox database. Further model interpretation results indicated that the model made predictions based on a correct "understanding" of the impact of key substituents and reactive sites toward HO•. This research provides an effective method for augmenting data sets, which is important in improving ML model performance and expanding AD. The final model has been made widely accessible through a free online predictor.
Collapse
Affiliation(s)
- Zhao Liu
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Lanyu Shang
- School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois 61820, United States
| | - Kuan Huang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Zhenrui Yue
- School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois 61820, United States
| | - Alan Y Han
- Department of Computer Science, Cornell University, Ithaca, New York 14850, United States
| | - Dong Wang
- School of Information Sciences, University of Illinois Urbana-Champaign, Champaign, Illinois 61820, United States
| | - Huichun Zhang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| |
Collapse
|
12
|
Li D, Liu Y, Hui Y, Li B, Hao C. A Glimpse of Research Trends and Frontiers in the Etiology of Premature Ovarian Insufficiency via Bibliometric Analysis. Endocr Metab Immune Disord Drug Targets 2025; 25:310-325. [PMID: 38919087 PMCID: PMC12079320 DOI: 10.2174/0118715303313887240624071238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 05/19/2024] [Accepted: 05/23/2024] [Indexed: 06/27/2024]
Abstract
INTRODUCTION Premature Ovarian Insufficiency (POI) is the most common reproductive aging disorder in women of reproductive age, which is characterized by decreased ovarian function in women before the age of 40. Etiology research of POI has garnered interest and attention from scholars worldwide over the past decades. METHODS However, to the best of our knowledge, no comprehensive survey with bibliometric analysis has been conducted yet on the research trends of POI etiology. This article aimed to analyze current scientific findings on the etiology of POI, offering innovative ideas for further research. Research articles on the etiology of POI from 1994 to 2023 were collected from the Web of Science Core Collection. A total of 456 research articles were included, and the total number of publications increased annually. We used VOSviewer and bibliometric.com to analyze the keywords, terms, institution, publication country/region, author name, publication journal, and the sum of times the articles have been cited. RESULTS This study has shown that a research hotspot is the genetic etiology of POI; however, there is still a lack of research on the impact of epigenetic alterations, iatrogenic injuries, environmental pollution, social stress, and unhealthy lifestyles on the pathogenesis of POI. CONCLUSION The factors illustrated here represent potential future directions for POI etiology research and warrant more attention from researchers.
Collapse
Affiliation(s)
- Duan Li
- Centre for Reproductive Medicine, Women and Children’s Hospital, Qingdao University, Qingdao, China
- Branch of Shandong Provincial Clinical Research Center for Reproductive Health, Qingdao, China
- College of Medicine, Qingdao University, Qingdao, China
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Yingxue Liu
- Centre for Reproductive Medicine, Women and Children’s Hospital, Qingdao University, Qingdao, China
- Branch of Shandong Provincial Clinical Research Center for Reproductive Health, Qingdao, China
- College of Medicine, Qingdao University, Qingdao, China
| | - Yameng Hui
- Qingdao Central Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Bing Li
- Department of Genetics and Cell Biology, Basic Medical College, Qingdao University, Qingdao, China
| | - Cuifang Hao
- Centre for Reproductive Medicine, Women and Children’s Hospital, Qingdao University, Qingdao, China
- Branch of Shandong Provincial Clinical Research Center for Reproductive Health, Qingdao, China
- College of Medicine, Qingdao University, Qingdao, China
| |
Collapse
|
13
|
Đurišić-Mladenović N, Živančev J, Antić I, Rakić D, Buljovčić M, Pajin B, Llorca M, Farre M. Occurrence of contaminants of emerging concern in different water samples from the lower part of the Danube River Middle Basin - A review. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 363:125128. [PMID: 39414068 DOI: 10.1016/j.envpol.2024.125128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 10/12/2024] [Accepted: 10/13/2024] [Indexed: 10/18/2024]
Abstract
This study intends to assess the extent of the occurrence of CECs in different water types based on the literature data reported for the countries from a lower part of the Middle Danube Basin, including those belonging to the Western Balkan (WB) region and two upstream neighboring EU Member States, Croatia and Slovenia. These countries share main freshwater courses important for drinking water supply, agriculture, industry, navigation, tourism, etc, but in some of them there are low rate of wastewater treatment, impacting the chemical status of water resources in the region and probably beyond, if downstream countries are considered. The literature survey revealed 38 investigative studies reporting data on CECs in water matrices sampled in the region in the period 2008-2022. Surface water was the most frequently studied water type in WB countries, while wastewater was the dominant water type studied in Slovenia and Croatia. The most often analyzed compounds in the studies dealing with surface water and wastewater were the anti-epileptic drug carbamazepine, some non-steroidal anti-inflammatory drugs, and antibiotics; pharmaceutically active compounds were also the most analyzed CECs in groundwater and drinking water. Additionally, similarities/dissimilarities among the experimental approaches in these studies were discussed in relation to the state-of-the-art research directions for the CECs surveillance in the European Union, resulting in summarized strengths and gaps in capacities for the wide-range surveillance of CECs in the lower part of the Middle Danube Basin. This is the first integral overview of the studies on CECs in waters from the countries belonging to this part of the Danube Basin, representing a valuable baseline for further enhancement of the relevant monitoring efforts and chemical status of the regional water resources, especially in countries with poor wastewater management.
Collapse
Affiliation(s)
- Nataša Đurišić-Mladenović
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Jelena Živančev
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia.
| | - Igor Antić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Dušan Rakić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Maja Buljovčić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Biljana Pajin
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Marta Llorca
- Institute of Environmental Assessment and Water Research (IDAEA), CSIC, C. Jordi Girona, 18-26, Barcelona, 08034, Spain
| | - Marinella Farre
- Institute of Environmental Assessment and Water Research (IDAEA), CSIC, C. Jordi Girona, 18-26, Barcelona, 08034, Spain
| |
Collapse
|
14
|
Stephens VR, Horner KB, Avila WM, Spicer SK, Chinni R, Bernabe EB, Hinton AO, Damo SM, Eastman AJ, McCallister MM, Osteen KG, Gaddy JA. The impact of persistent organic pollutants on fertility: exposure to the environmental toxicant 2,3,7,8-tetrachlorodibenzo-p-dioxin alters reproductive tract immune responses. Front Immunol 2024; 15:1497405. [PMID: 39720712 PMCID: PMC11666484 DOI: 10.3389/fimmu.2024.1497405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Accepted: 11/18/2024] [Indexed: 12/26/2024] Open
Abstract
Exposure to environmental contaminants can result in profound effects on the host immune system. One class of environmental toxicants, known as dioxins, are persistent environmental contaminants termed "forever chemicals". The archetype toxicant from this group of chemicals is 2, 3, 7, 8-tetrachlorodibenzo-p-dioxin (TCDD), an immunotoxicant that activates the aryl-hydrocarbon receptor pathway leading to a variety of changes in immune cell responses. Immune cell functions are crucial to the development and maintenance of healthy reproduction. Immune cells facilitate tolerance between at the maternal-fetal interface between the parent and the semi-allogenic fetus and help defend the gravid reproductive tract from infectious assault. Epidemiological studies reveal that exposure to environmental contaminants (such as TCDD) are linked to adverse reproductive health outcomes including endometriosis, placental inflammation, and preterm birth. However, little is known about the molecular mechanisms that underpin how environmental toxicant exposures impact immune functions at the maternal-fetal interface or within the reproductive tract in general. This review presents the most recent published work that studies interactions between dioxin or TCDD exposure, the host immune system, and reproduction.
Collapse
Affiliation(s)
- Victoria R. Stephens
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Kensley B. Horner
- Department of Life and Physical Sciences, Fisk University, Nashville, TN, United States
| | - Walter M. Avila
- Department of Life and Physical Sciences, Fisk University, Nashville, TN, United States
| | - Sabrina K. Spicer
- Department of Chemistry, Vanderbilt University, Nashville, TN, United States
| | - Riya Chinni
- Department of Medicine, Health, and Society, Vanderbilt University, Nashville, TN, United States
| | - Emily B. Bernabe
- Tennessee Valley Health Systems, Department of Veterans Affairs, Nashville, TN, United States
| | - Antentor O. Hinton
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, United States
| | - Steven M. Damo
- Department of Life and Physical Sciences, Fisk University, Nashville, TN, United States
- Department of Biochemistry, Vanderbilt University, Nashville, TN, United States
- Center for Structural Biology, Vanderbilt University, Nashville, TN, United States
| | - Alison J. Eastman
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Monique M. McCallister
- Department of Biological Sciences, Tennessee State University, Nashville, TN, United States
| | - Kevin G. Osteen
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
- Tennessee Valley Health Systems, Department of Veterans Affairs, Nashville, TN, United States
- Department of Obstetrics and Gynecology, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Obstetrics and Gynecology, Meharry Medical College, Nashville, TN, United States
| | - Jennifer A. Gaddy
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Medicine, Health, and Society, Vanderbilt University, Nashville, TN, United States
- Tennessee Valley Health Systems, Department of Veterans Affairs, Nashville, TN, United States
- Department of Medicine, Division of Infectious Diseases, Vanderbilt University Medical Center, Nashville, TN, United States
| |
Collapse
|
15
|
Ji X, Lakuleswaran M, Cowell W, Kahn LG, Sirota M, Abrahamsson D. Insights into the Chemical Exposome during Pregnancy: A Non-Targeted Analysis of Preterm and Term Births. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:20883-20893. [PMID: 39526929 PMCID: PMC11603774 DOI: 10.1021/acs.est.4c08534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Revised: 10/30/2024] [Accepted: 11/01/2024] [Indexed: 11/16/2024]
Abstract
Human-made chemicals are ubiquitous, leading to chronic exposure to complex mixtures of potentially harmful substances. We investigated chemical exposures in pregnant women in New York City by applying a non-targeted analysis (NTA) workflow to 95 paired prenatal urine and serum samples (35 pairs of preterm birth) collected as part of the New York University Children's Health and Environment Study. We analyzed all samples using liquid chromatography coupled with Orbitrap high-resolution mass spectrometry in both positive and negative electrospray ionization modes, employing full scan and data-dependent MS/MS fragmentation scans. We detected a total of 1524 chemical features for annotation, with 12 chemicals confirmed by authentic standards. Two confirmed chemicals dodecyltrimethylammonium and N,N-dimethyldecylamine N-oxide appear to not have been previously reported in human blood samples. We observed a statistically significant differential enrichment between urine and serum samples, as well as between preterm and term birth (p < 0.0001) in serum samples. When comparing between preterm and term births, an exogenous contaminant, 1,4-cyclohexanedicarboxylic acid (tentative), showed a statistical significance difference (p = 0.003) with more abundance in preterm birth in serum. An example of chemical associations (12 associations in total) observed was between surfactants (tertiary amines) and endogenous metabolites (fatty acid amides).
Collapse
Affiliation(s)
- Xiaowen Ji
- Division
of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University, New York, New York 10016, United States
| | - Mathusa Lakuleswaran
- Division
of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University, New York, New York 10016, United States
| | - Whitney Cowell
- Division
of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University, New York, New York 10016, United States
| | - Linda G. Kahn
- Division
of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University, New York, New York 10016, United States
| | - Marina Sirota
- Bakar
Computational Health Sciences Institute, UCSF, San Francisco, California 94158, United States
- Department
of Pediatrics, University of California,
San Francisco, San Francisco, California 94158, United States
| | - Dimitri Abrahamsson
- Division
of Environmental Pediatrics, Department of Pediatrics, Grossman School of Medicine, New York University, New York, New York 10016, United States
- Department
of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, California 94158, United States
| |
Collapse
|
16
|
Liang W, Su W, Zhong L, Yang Z, Li T, Liang Y, Ruan T, Jiang G. Comprehensive Characterization of Oxidative Stress-Modulating Chemicals Using GPT-Based Text Mining. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:20540-20552. [PMID: 39513989 DOI: 10.1021/acs.est.4c07390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2024]
Abstract
The screening of hazardous environmental pollutants is hindered by the limited availability of toxicological databases. Large language model (LLM)-based text mining holds the potential to automatically extract complex toxicological information from the literature. Due to its relevance to diseases and the challenge of comprehensive characterization, oxidative stress serves as a suitable case for research by texting mining. In this study, a robust workflow utilizing a LLM (i.e., GPT-4) was developed to extract information on oxidative stress tests, including data collection, text preprocessing, prompt engineering, and performance evaluation procedures. A total of 17,780 relevant records were extracted from 7166 articles, covering 2558 unique compounds. A rising interest in oxidative stress was observed over the past two decades. A list of known prooxidants (n = 1416) and antioxidants (n = 1102) was established, with the leading chemical categories being pharmaceuticals, pesticides, and metals for prooxidants and pharmaceuticals and flavonoids for antioxidants. Structural alert analysis identified potential prooxidant (e.g., chlorobenzene, nitrobenzene, and tertiary amines) and antioxidant (e.g., flavonoid and thiol) substructures. These findings illustrate the feasibility of building toxicological databases through LLM-based text mining in a cost-efficient manner, and the information obtained from the technique holds significant promise for future applications in environmental and health research.
Collapse
Affiliation(s)
- Wenqing Liang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenyuan Su
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Laijin Zhong
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhendong Yang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tingyu Li
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yong Liang
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Ting Ruan
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
- Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
17
|
Kong AX, Johnson M, Eno AF, Pham K, Zhang P, Geng Y. Proteome-wide reverse molecular docking reveals folic acid receptor as a mediator of PFAS-induced neurodevelopmental toxicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.11.623082. [PMID: 39605555 PMCID: PMC11601370 DOI: 10.1101/2024.11.11.623082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
Per- and polyfluoroalkyl substances (PFAS) are a class of long-lasting chemicals with widespread use and environmental persistence that have been increasingly studied for their detrimental impacts to human and animal health. Several major PFAS species are linked to neurodevelopmental toxicity. For example, epidemiological studies have associated prenatal exposure to perfluorooctanoate (PFOA) and perfluorononanoate (PFNA) with autism risk. However, the neurodevelopmental toxicities of major PFAS species have not been systematically evaluated in an animal model, and the molecular mechanisms underlying these toxicities have remained elusive. Using a high-throughput zebrafish social behavioral model, we screened six major PFAS species currently under regulation by the Environmental Protection Agency (EPA), including PFOA, PFNA, perfluorooctane sulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorobutane sulfonate (PFBS), and hexafluoropropylene oxide dimer acid ammonium salt (GenX). We found that embryonic exposure to PFNA, PFOA, and PFOS induced social deficits in zebrafish, recapitulating one of the hallmark behavioral deficits in autistic individuals. To uncover protein targets of the six EPA-regulated PFAS, we screened a virtual library containing predicted binding pockets of over 80% of the 3D human proteome through reverse molecular docking. We found that folate receptor beta (FR-β, encoded by the gene FOLR2) interacts strongly with PFNA, PFOA, and PFOS but to a lesser degree with PFHxS, PFBS, and GenX, correlating positively with their in vivo toxicity. Embryonic co-exposure to folic acid rescued social deficits induced by PFAS. The folic acid pathway has been implicated in autism, indicating a novel molecular mechanism for PFAS in autism etiology.
Collapse
Affiliation(s)
- Ally Xinyi Kong
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| | - Maja Johnson
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| | - Aiden F Eno
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| | - Khoa Pham
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| | - Ping Zhang
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| | - Yijie Geng
- Department of Environmental and Occupational Health Sciences, Seattle, WA 98105, USA
| |
Collapse
|
18
|
Ciccarelli D, Lancaster BMJ, Braddock DC, Calvaresi M, Mišík M, Knasmüller S, Mattioli EJ, Zerbetto F, White AJP, Marczylo T, Gant TW, Barron LP. Structure confirmation, reactivity, bacterial mutagenicity and quantification of 2,2,4-tribromo-5-hydroxycyclopent-4-ene-1,3-dione in drinking water. Commun Chem 2024; 7:266. [PMID: 39543162 PMCID: PMC11564736 DOI: 10.1038/s42004-024-01356-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Accepted: 11/04/2024] [Indexed: 11/17/2024] Open
Abstract
The presence of two new disinfectant by-product (DBP) groups in the UK was recently shown using non-target analysis, halogenated-hydroxycyclopentenediones and halogenated-methanesulfonic acids. In this work, we confirmed the structure of 2,2,4-tribromo-5-hydroxycyclopent-4-ene-1,3-dione (TBHCD), and quantified it together with dibromomethanesulfonic acid at 122 ± 34 and 326 ± 157 ng L-1 on average in London's drinking water, respectively (n = 21). We found TBHCD to be photolabile and unstable in tap water and at alkaline pH. Furthermore, spectral and computational data for TBHCD and three other halogenated-hydroxycyclopentenediones indicated they could act as a source of radicals in water and in the body. Importantly, TBHCD was calculated to have a 14.5 kcal mol-1 lower C-Br bond dissociation enthalpy than the N-Br bond of N-bromosuccinimide, a common radical substitution reagent used in organic synthesis. TBHCD was mutagenic in Salmonella/microsome assays using strains TA98, TA100 and TA102. This work reveals the unique features, activity and toxicity of trihalogenated hydroxycyclopent-4-ene-1,3-diones, prompting a need to more comprehensively assess their risks.
Collapse
Affiliation(s)
- Davide Ciccarelli
- Environmental Research Group, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK
- NIHR-HPRU Chemical and Radiation Threats and Hazards, NIHR-HPRU Environmental Exposures and Health, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK
| | - Ben M J Lancaster
- Department of Chemistry, Imperial College London, 82 Wood Lane, London, W12 0BZ, UK
| | | | - Matteo Calvaresi
- Dipartimento di Chimica "Giacomo Ciamician", Alma Mater Studiorum - Università di Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Miroslav Mišík
- Medical University of Vienna, Center for Cancer Research, Borschkegasse 8a, 1090, Vienna, Austria
| | - Siegfried Knasmüller
- Medical University of Vienna, Center for Cancer Research, Borschkegasse 8a, 1090, Vienna, Austria
| | - Edoardo Jun Mattioli
- Dipartimento di Chimica "Giacomo Ciamician", Alma Mater Studiorum - Università di Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Francesco Zerbetto
- Dipartimento di Chimica "Giacomo Ciamician", Alma Mater Studiorum - Università di Bologna, Via Francesco Selmi 2, 40126, Bologna, Italy
| | - Andrew J P White
- Department of Chemistry, Imperial College London, 82 Wood Lane, London, W12 0BZ, UK
| | - Tim Marczylo
- NIHR-HPRU Chemical and Radiation Threats and Hazards, NIHR-HPRU Environmental Exposures and Health, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK
- UK Health Security Agency, Harwell Science Campus, Oxon, OX11 0RQ, UK
| | - Timothy W Gant
- NIHR-HPRU Chemical and Radiation Threats and Hazards, NIHR-HPRU Environmental Exposures and Health, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK
- UK Health Security Agency, Harwell Science Campus, Oxon, OX11 0RQ, UK
| | - Leon P Barron
- Environmental Research Group, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK.
- NIHR-HPRU Chemical and Radiation Threats and Hazards, NIHR-HPRU Environmental Exposures and Health, MRC Centre for Environment and Health, School of Public Health, Imperial College London, 86 Wood Lane, London, W12 0BZ, UK.
- UK Health Security Agency, Harwell Science Campus, Oxon, OX11 0RQ, UK.
| |
Collapse
|
19
|
Tanui IC, Kandie F, Krauss M, Piotrowska A, Kiprop A, Shahid N, Liess M, Brack W. Seasonal hot spots of pollution and risks in Western Kenya: A spatial-temporal analysis of almost 800 organic micropollutants. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:175036. [PMID: 39069188 DOI: 10.1016/j.scitotenv.2024.175036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 07/23/2024] [Accepted: 07/23/2024] [Indexed: 07/30/2024]
Abstract
The release of chemicals into the environment presents a significant threat to aquatic ecosystems dependent on the proximity to emission sources and seasonal dynamics of emission and mobilization. While spatial-temporal information on water pollution in Europe is increasing, there are substantial knowledge gaps on seasonal pollution dynamics in tropical countries. Thus, we took Lake Victoria South Basin in western Kenya as a case study to identify spatial and seasonal hot spots of contamination, quantified toxic risks to different groups of organisms, and identified seasonal risk drivers. For this purpose, we analyzed grab water samples from five rivers with agricultural and wastewater treatment plants in their catchment in four different seasons. We used liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) with a target list of 785 organic micropollutants. A total of 307 compounds were detected with concentrations ranging from 0.3 ng/L to 6.6 μg/L. Using a Toxic Unit (TU) approach based on mixture toxicity to standard test organisms, crustaceans were identified as the most affected group followed by algae and fish. For crustaceans, chronic risk thresholds were exceeded in 96 % of all the samples, while 56 % of all samples are expected to be acutely toxic, with the highest risk in February during the dry season. High toxic unit values for algae and fish were recorded in July dry season and May wet season. Diazinon, imidacloprid, clothianidin and pirimiphos-methyl were the major drivers for crustacean toxicity while triclosan and different herbicide mixtures drive risks to algae in dry and wet seasons, respectively. A total of 18 chemicals were found to exceed acute and chronic environmental risk thresholds. With this study, strong spatial-temporal patterns of pollution, risks and risk drivers could be confirmed informing prioritization of monitoring and abatement to enhance water quality and reduce toxic risks.
Collapse
Affiliation(s)
- Isaac Cheruiyot Tanui
- Department of Exposure Science, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany; Institute of Ecology, Evolution and Diversity, Goethe University, Max-von-Laue-Straße 13, Frankfurt am Main, Germany; Department of Chemistry and Biochemistry, Moi University, 3900-30100 Eldoret, Kenya.
| | - Faith Kandie
- Department of Biological Sciences, Moi University, 3900-30100 Eldoret, Kenya.
| | - Martin Krauss
- Department of Exposure Science, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany.
| | - Aleksandra Piotrowska
- Department of Exposure Science, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany.
| | - Ambrose Kiprop
- Department of Chemistry and Biochemistry, Moi University, 3900-30100 Eldoret, Kenya.
| | - Naeem Shahid
- Institute of Ecology, Evolution and Diversity, Goethe University, Max-von-Laue-Straße 13, Frankfurt am Main, Germany; System Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany.
| | - Matthias Liess
- System Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany.
| | - Werner Brack
- Department of Exposure Science, Helmholtz Centre for Environmental Research (UFZ), Permoserstraße 15, 04318 Leipzig, Germany; Institute of Ecology, Evolution and Diversity, Goethe University, Max-von-Laue-Straße 13, Frankfurt am Main, Germany.
| |
Collapse
|
20
|
Xie H, Sdougkou K, Bonnefille B, Papazian S, Bergdahl IA, Rantakokko P, Martin JW. Chemical Exposomics in Human Plasma by Lipid Removal and Large-Volume Injection Gas Chromatography-High-Resolution Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:17592-17605. [PMID: 39376097 PMCID: PMC11465644 DOI: 10.1021/acs.est.4c05942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 09/11/2024] [Accepted: 09/12/2024] [Indexed: 10/09/2024]
Abstract
For comprehensive chemical exposomics in blood, analytical workflows are evolving through advances in sample preparation and instrumental methods. We hypothesized that gas chromatography-high-resolution mass spectrometry (GC-HRMS) workflows could be enhanced by minimizing lipid coextractives, thereby enabling larger injection volumes and lower matrix interference for improved target sensitivity and nontarget molecular discovery. A simple protocol was developed for small plasma volumes (100-200 μL) by using isohexane (H) to extract supernatants of acetonitrile-plasma (A-P). The HA-P method was quantitative for a wide range of hydrophobic multiclass target analytes (i.e., log Kow > 3.0), and the extracts were free of major lipids, thereby enabling robust large-volume injections (LVIs; 25 μL) in long sequences (60-70 h, 70-80 injections) to a GC-Orbitrap HRMS. Without lipid removal, LVI was counterproductive because method sensitivity suffered from the abundant matrix signal, resulting in low ion injection times to the Orbitrap. The median method quantification limit was 0.09 ng/mL (range 0.005-4.83 ng/mL), and good accuracy was shown for a certified reference serum. Applying the method to plasma from a Swedish cohort (n = 32; 100 μL), 51 of 103 target analytes were detected. Simultaneous nontarget analysis resulted in 112 structural annotations (12.8% annotation rate), and Level 1 identification was achieved for 7 of 8 substances in follow-up confirmations. The HA-P method is potentially scalable for application in cohort studies and is also compatible with many liquid-chromatography-based exposomics workflows.
Collapse
Affiliation(s)
- Hongyu Xie
- Department
of Environmental Science, Stockholm University, 106 91 Stockholm, Sweden
| | - Kalliroi Sdougkou
- Department
of Environmental Science, Stockholm University, 106 91 Stockholm, Sweden
| | - Bénilde Bonnefille
- Department
of Environmental Science, Stockholm University, 106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, 171 65 Solna, Sweden
| | - Stefano Papazian
- Department
of Environmental Science, Stockholm University, 106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, 171 65 Solna, Sweden
| | - Ingvar A. Bergdahl
- Department
of Public Health and Clinical Medicine, Section for Sustainable Health, Umeå University, 901 87 Umeå, Sweden
| | - Panu Rantakokko
- Department
of Public Health, Lifestyles and Living Environments Unit, National Institute for Health and Welfare, Neulaniementie 4, 702 10 Kuopio, Finland
| | - Jonathan W. Martin
- Department
of Environmental Science, Stockholm University, 106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, 171 65 Solna, Sweden
| |
Collapse
|
21
|
Peets P, Rian MB, Martin JW, Kruve A. Evaluation of Nontargeted Mass Spectral Data Acquisition Strategies for Water Analysis and Toxicity-Based Feature Prioritization by MS2Tox. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:17406-17418. [PMID: 39297340 PMCID: PMC11447898 DOI: 10.1021/acs.est.4c02833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 09/06/2024] [Accepted: 09/09/2024] [Indexed: 10/02/2024]
Abstract
The machine-learning tool MS2Tox can prioritize hazardous nontargeted molecular features in environmental waters, by predicting acute fish lethality of unknown molecules based on their MS2 spectra, prior to structural annotation. It has yet to be investigated how the extent of molecular coverage, MS2 spectra quality, and toxicity prediction confidence depend on sample complexity and MS2 data acquisition strategies. We compared two common nontargeted MS2 acquisition strategies with liquid chromatography high-resolution mass spectrometry for structural annotation accuracy by SIRIUS+CSI:FingerID and MS2Tox toxicity prediction of 191 reference chemicals spiked to LC-MS water, groundwater, surface water, and wastewater. Data-dependent acquisition (DDA) resulted in higher rates (19-62%) of correct structural annotations among reference chemicals in all matrices except wastewaters, compared to data-independent acquisition (DIA, 19-50%). However, DIA resulted in higher MS2 detection rates (59-84% DIA, 37-82% DDA), leading to higher true positive rates for spectral library matching, 40-73% compared to 34-72%. DDA resulted in higher MS2Tox toxicity prediction accuracy than DIA, with root-mean-square errors of 0.62 and 0.71 log-mM, respectively. Given the importance of MS2 spectral quality, we introduce a "CombinedConfidence" score to convey relative confidence in MS2Tox predictions and apply this approach to prioritize potentially ecotoxic nontargeted features in environmental waters.
Collapse
Affiliation(s)
- Pilleriin Peets
- Department
of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius Väg 16, SE-106
91, Stockholm, Sweden
- Institute
of Biodiversity, Faculty of Biological Science, Cluster of Excellence
Balance of the Microverse, Friedrich-Schiller-University
Jena, 07743, Jena, Germany
| | - May Britt Rian
- Department
of Environmental Science, Stockholm University, Svante Arrhenius Väg 16, SE-106 91 Stockholm, Sweden
| | - Jonathan W. Martin
- Department
of Environmental Science, Stockholm University, Svante Arrhenius Väg 16, SE-106 91 Stockholm, Sweden
- National
Facility for Exposomics, Metabolomics Platform, Science for Life Laboratory, Stockholm University, Solna 171 65, Sweden
| | - Anneli Kruve
- Department
of Materials and Environmental Chemistry, Stockholm University, Svante Arrhenius Väg 16, SE-106
91, Stockholm, Sweden
- Department
of Environmental Science, Stockholm University, Svante Arrhenius Väg 16, SE-106 91 Stockholm, Sweden
| |
Collapse
|
22
|
Cheng Y, Zhang K, Huang K, Zhang H. Meta-Analysis and Machine Learning Models for Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:12976-12988. [PMID: 38988037 DOI: 10.1021/acs.est.4c01033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/12/2024]
Abstract
Anaerobic biodegradation rates (half-lives) of organic chemicals are pivotal for environmental risk assessment and remediation. Traditional experimental evaluation, constrained by prolonged, oxygen-free conditions, struggles to keep pace with emerging contaminants. Data-driven machine learning (ML) models serve as promising complements. However, reported quantitative structure-biodegradation relationships or ML models on anaerobic biodegradation are mostly based on small data sets (<100 records) and neglect experimental conditions, usually achieving compromised predictions. This work aimed to develop ML models for predicting the biodegradation half-lives of organic pollutants in anaerobic environments (i.e., sediment/soil and sludge). Focusing on important features of both chemicals and experimental conditions, we first curated two data sets, one for sediment/soil (SED) and the other for sludge (SLD), covering 978 records for 206 chemicals from the literature, and then conducted a meta-analysis. Next, we built a binary classification (half-life of 30 days as the cutoff) model with an accuracy of 81% and a regression model with R2 of 0.56 for SED based on LightGBM (80% and 0.31 for SLD based on Extra tree, respectively). The model interpretations underscored the significance of experimental conditions (e.g., temperature and inoculum dosage), as evidenced by their high feature importance, and the models were found to correctly capture the effects of chemical substructures, for example, branched structures and aromatic rings prolonged half-lives while methyl group and ortho-substitution on rings shortened half-lives. The applicability domains of the models were also defined, resulting in reasonable prediction for the half-lives of 41% (SED) or 67% (SLD) of over 4000 persistent, bioaccumulative, and toxic chemicals. Overall, this study pioneers ML models for predicting the anaerobic degradation half-lives, offering valuable support for future evaluation and implementation of chemical anaerobic biodegradation.
Collapse
Affiliation(s)
- Yushu Cheng
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Kai Zhang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Kuan Huang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| | - Huichun Zhang
- Department of Civil and Environmental Engineering, Case Western Reserve University, Cleveland, Ohio 44106, United States
| |
Collapse
|
23
|
Samanipour S, Barron LP, van Herwerden D, Praetorius A, Thomas KV, O’Brien JW. Exploring the Chemical Space of the Exposome: How Far Have We Gone? JACS AU 2024; 4:2412-2425. [PMID: 39055136 PMCID: PMC11267556 DOI: 10.1021/jacsau.4c00220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Revised: 05/29/2024] [Accepted: 05/31/2024] [Indexed: 07/27/2024]
Abstract
Around two-thirds of chronic human disease can not be explained by genetics alone. The Lancet Commission on Pollution and Health estimates that 16% of global premature deaths are linked to pollution. Additionally, it is now thought that humankind has surpassed the safe planetary operating space for introducing human-made chemicals into the Earth System. Direct and indirect exposure to a myriad of chemicals, known and unknown, poses a significant threat to biodiversity and human health, from vaccine efficacy to the rise of antimicrobial resistance as well as autoimmune diseases and mental health disorders. The exposome chemical space remains largely uncharted due to the sheer number of possible chemical structures, estimated at over 1060 unique forms. Conventional methods have cataloged only a fraction of the exposome, overlooking transformation products and often yielding uncertain results. In this Perspective, we have reviewed the latest efforts in mapping the exposome chemical space and its subspaces. We also provide our view on how the integration of data-driven approaches might be able to bridge the identified gaps.
Collapse
Affiliation(s)
- Saer Samanipour
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- UvA
Data Science Center, University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Leon Patrick Barron
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- MRC
Centre for Environment and Health, Environmental Research Group, School
of Public Health, Faculty of Medicine, Imperial
College London, London W12 0BZ, United Kingdom
| | - Denice van Herwerden
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
| | - Antonia Praetorius
- Institute
for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
| | - Kevin V. Thomas
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
| | - Jake William O’Brien
- Van’t
Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam 1090 GD, The Netherlands
- Queensland
Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, Cornwall Street, Woolloongabba, Queensland 4102, Australia
| |
Collapse
|
24
|
Sadia M, Boudguiyer Y, Helmus R, Seijo M, Praetorius A, Samanipour S. A stochastic approach for parameter optimization of feature detection algorithms for non-target screening in mass spectrometry. Anal Bioanal Chem 2024:10.1007/s00216-024-05425-3. [PMID: 38995405 DOI: 10.1007/s00216-024-05425-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/05/2024] [Accepted: 06/18/2024] [Indexed: 07/13/2024]
Abstract
Feature detection plays a crucial role in non-target screening (NTS), requiring careful selection of algorithm parameters to minimize false positive (FP) features. In this study, a stochastic approach was employed to optimize the parameter settings of feature detection algorithms used in processing high-resolution mass spectrometry data. This approach was demonstrated using four open-source algorithms (OpenMS, SAFD, XCMS, and KPIC2) within the patRoon software platform for processing extracts from drinking water samples spiked with 46 per- and polyfluoroalkyl substances (PFAS). The designed method is based on a stochastic strategy involving random sampling from variable space and the use of Pearson correlation to assess the impact of each parameter on the number of detected suspect analytes. Using our approach, the optimized parameters led to improvement in the algorithm performance by increasing suspect hits in case of SAFD and XCMS, and reducing the total number of detected features (i.e., minimizing FP) for OpenMS. These improvements were further validated on three different drinking water samples as test dataset. The optimized parameters resulted in a lower false discovery rate (FDR%) compared to the default parameters, effectively increasing the detection of true positive features. This work also highlights the necessity of algorithm parameter optimization prior to starting the NTS to reduce the complexity of such datasets.
Collapse
Affiliation(s)
- Mohammad Sadia
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands.
| | - Youssef Boudguiyer
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Rick Helmus
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Marianne Seijo
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Antonia Praetorius
- Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands
| | - Saer Samanipour
- Van'T Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
25
|
Wang F, Xiang L, Sze-Yin Leung K, Elsner M, Zhang Y, Guo Y, Pan B, Sun H, An T, Ying G, Brooks BW, Hou D, Helbling DE, Sun J, Qiu H, Vogel TM, Zhang W, Gao Y, Simpson MJ, Luo Y, Chang SX, Su G, Wong BM, Fu TM, Zhu D, Jobst KJ, Ge C, Coulon F, Harindintwali JD, Zeng X, Wang H, Fu Y, Wei Z, Lohmann R, Chen C, Song Y, Sanchez-Cid C, Wang Y, El-Naggar A, Yao Y, Huang Y, Cheuk-Fung Law J, Gu C, Shen H, Gao Y, Qin C, Li H, Zhang T, Corcoll N, Liu M, Alessi DS, Li H, Brandt KK, Pico Y, Gu C, Guo J, Su J, Corvini P, Ye M, Rocha-Santos T, He H, Yang Y, Tong M, Zhang W, Suanon F, Brahushi F, Wang Z, Hashsham SA, Virta M, Yuan Q, Jiang G, Tremblay LA, Bu Q, Wu J, Peijnenburg W, Topp E, Cao X, Jiang X, Zheng M, Zhang T, Luo Y, Zhu L, Li X, Barceló D, Chen J, Xing B, Amelung W, Cai Z, Naidu R, Shen Q, Pawliszyn J, Zhu YG, Schaeffer A, Rillig MC, Wu F, Yu G, Tiedje JM. Emerging contaminants: A One Health perspective. Innovation (N Y) 2024; 5:100612. [PMID: 38756954 PMCID: PMC11096751 DOI: 10.1016/j.xinn.2024.100612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 03/10/2024] [Indexed: 05/18/2024] Open
Abstract
Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.
Collapse
Affiliation(s)
- Fang Wang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leilei Xiang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kelvin Sze-Yin Leung
- Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
- HKBU Institute of Research and Continuing Education, Shenzhen Virtual University Park, Shenzhen, China
| | - Martin Elsner
- Technical University of Munich, TUM School of Natural Sciences, Institute of Hydrochemistry, 85748 Garching, Germany
| | - Ying Zhang
- School of Resources & Environment, Northeast Agricultural University, Harbin 150030, China
| | - Yuming Guo
- Climate, Air Quality Research Unit, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Bo Pan
- Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China
| | - Hongwen Sun
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Taicheng An
- Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Guangguo Ying
- Ministry of Education Key Laboratory of Environmental Theoretical Chemistry, South China Normal University, Guangzhou, Guangdong 510006, China
| | - Bryan W. Brooks
- Department of Environmental Science, Baylor University, Waco, TX, USA
- Center for Reservoir and Aquatic Systems Research (CRASR), Baylor University, Waco, TX, USA
| | - Deyi Hou
- School of Environment, Tsinghua University, Beijing 100084, China
| | - Damian E. Helbling
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Jianqiang Sun
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, Zhejiang University of Technology, Hangzhou 310014, China
| | - Hao Qiu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Timothy M. Vogel
- Laboratoire d’Ecologie Microbienne, Universite Claude Bernard Lyon 1, UMR CNRS 5557, UMR INRAE 1418, VetAgro Sup, 69622 Villeurbanne, France
| | - Wei Zhang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Yanzheng Gao
- Institute of Organic Contaminant Control and Soil Remediation, College of Resources and Environmental Sciences, Nanjing Agricultural University, Weigang Road 1, Nanjing 210095, China
| | - Myrna J. Simpson
- Environmental NMR Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4, Canada
| | - Yi Luo
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China
| | - Scott X. Chang
- Department of Renewable Resources, University of Alberta, 442 Earth Sciences Building, Edmonton, AB T6G 2E3, Canada
| | - Guanyong Su
- Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
| | - Bryan M. Wong
- Materials Science & Engineering Program, Department of Chemistry, and Department of Physics & Astronomy, University of California-Riverside, Riverside, CA, USA
| | - Tzung-May Fu
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Dong Zhu
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Karl J. Jobst
- Department of Chemistry, Memorial University of Newfoundland, 45 Arctic Avenue, St. John’s, NL A1C 5S7, Canada
| | - Chengjun Ge
- Key Laboratory of Agro-Forestry Environmental Processes and Ecological Regulation of Hainan Province, School of Ecological and Environmental Sciences, Hainan University, Haikou 570228, China
| | - Frederic Coulon
- School of Water, Energy and Environment, Cranfield University, Cranfield MK43 0AL, UK
| | - Jean Damascene Harindintwali
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiankui Zeng
- Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
| | - Haijun Wang
- Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming 650504, China
| | - Yuhao Fu
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhong Wei
- Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing 210095, China
| | - Rainer Lohmann
- Graduate School of Oceanography, University of Rhode Island, Narragansett, RI, USA
| | - Changer Chen
- Ministry of Education Key Laboratory of Environmental Theoretical Chemistry, South China Normal University, Guangzhou, Guangdong 510006, China
| | - Yang Song
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Concepcion Sanchez-Cid
- Environmental Microbial Genomics, UMR 5005 Laboratoire Ampère, CNRS, École Centrale de Lyon, Université de Lyon, Écully, France
| | - Yu Wang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ali El-Naggar
- Department of Renewable Resources, University of Alberta, 442 Earth Sciences Building, Edmonton, AB T6G 2E3, Canada
- Department of Soil Sciences, Faculty of Agriculture, Ain Shams University, Cairo 11241, Egypt
| | - Yiming Yao
- Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yanran Huang
- Applied Biology and Chemical Technology, Hong Kong Polytechnic University, Hong Kong, China
| | | | - Chenggang Gu
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huizhong Shen
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Yanpeng Gao
- Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Chao Qin
- Institute of Organic Contaminant Control and Soil Remediation, College of Resources and Environmental Sciences, Nanjing Agricultural University, Weigang Road 1, Nanjing 210095, China
| | - Hao Li
- Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming 650500, China
| | - Tong Zhang
- Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
| | - Natàlia Corcoll
- Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Daniel S. Alessi
- Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada
| | - Hui Li
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Kristian K. Brandt
- Section for Microbial Ecology and Biotechnology, Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Denmark
- Sino-Danish Center (SDC), Beijing, China
| | - Yolanda Pico
- Food and Environmental Safety Research Group of the University of Valencia (SAMA-UV), Desertification Research Centre - CIDE (CSIC-UV-GV), Road CV-315 km 10.7, 46113 Moncada, Valencia, Spain
| | - Cheng Gu
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China
| | - Jianhua Guo
- Australian Centre for Water and Environmental Biotechnology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Jianqiang Su
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Philippe Corvini
- School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, 4132 Muttenz, Switzerland
| | - Mao Ye
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Teresa Rocha-Santos
- Centre for Environmental and Marine Studies (CESAM) & Department of Chemistry, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Huan He
- Jiangsu Engineering Laboratory of Water and Soil Eco-remediation, School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Yi Yang
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Meiping Tong
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Weina Zhang
- Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, School of Environmental Science and Engineering, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou 510006, China
| | - Fidèle Suanon
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Laboratory of Physical Chemistry, Materials and Molecular Modeling (LCP3M), University of Abomey-Calavi, Republic of Benin, Cotonou 01 BP 526, Benin
| | - Ferdi Brahushi
- Department of Environment and Natural Resources, Agricultural University of Tirana, 1029 Tirana, Albania
| | - Zhenyu Wang
- Institute of Environmental Processes and Pollution Control, and School of Environment & Ecology, Jiangnan University, Wuxi 214122, China
| | - Syed A. Hashsham
- Center for Microbial Ecology, Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
- Department of Civil and Environmental Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Marko Virta
- Department of Microbiology, University of Helsinki, 00010 Helsinki, Finland
| | - Qingbin Yuan
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China
| | - Gaofei Jiang
- Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing 210095, China
| | - Louis A. Tremblay
- School of Biological Sciences, University of Auckland, Auckland, Aotearoa 1142, New Zealand
| | - Qingwei Bu
- School of Chemical & Environmental Engineering, China University of Mining & Technology - Beijing, Beijing 100083, China
| | - Jichun Wu
- Key Laboratory of Surficial Geochemistry, Ministry of Education, School of Earth Sciences and Engineering, Nanjing University, Nanjing 210023, China
| | - Willie Peijnenburg
- National Institute of Public Health and the Environment, Center for the Safety of Substances and Products, 3720 BA Bilthoven, The Netherlands
- Leiden University, Center for Environmental Studies, Leiden, the Netherlands
| | - Edward Topp
- Agroecology Mixed Research Unit, INRAE, 17 rue Sully, 21065 Dijon Cedex, France
| | - Xinde Cao
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Xin Jiang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Minghui Zheng
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Taolin Zhang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Yongming Luo
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lizhong Zhu
- Department of Environmental Science, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Xiangdong Li
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China
| | - Damià Barceló
- Chemistry and Physics Department, University of Almeria, 04120 Almeria, Spain
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Baoshan Xing
- Stockbridge School of Agriculture, University of Massachusetts, Amherst, MA 01003, USA
| | - Wulf Amelung
- Institute of Crop Science and Resource Conservation (INRES), Soil Science and Soil Ecology, University of Bonn, 53115 Bonn, Germany
- Agrosphere Institute (IBG-3), Forschungszentrum Jülich GmbH, 52428 Jülich, Germany
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
| | - Ravi Naidu
- Global Centre for Environmental Remediation (GCER), The University of Newcastle (UON), Newcastle, NSW 2308, Australia
- Cooperative Research Centre for Contamination Assessment and Remediation of the Environment (CRC CARE), The University of Newcastle (UON), Newcastle, NSW 2308, Australia
| | - Qirong Shen
- Jiangsu Provincial Key Lab for Organic Solid Waste Utilization, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing Agricultural University, Nanjing 210095, China
| | - Janusz Pawliszyn
- Department of Chemistry, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Yong-guan Zhu
- University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Andreas Schaeffer
- Institute for Environmental Research, RWTH Aachen University, 52074 Aachen, Germany
| | - Matthias C. Rillig
- Institute of Biology, Freie Universität Berlin, Berlin, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany
| | - Fengchang Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Gang Yu
- Advanced Interdisciplinary Institute of Environment and Ecology, Beijing Normal University, Zhuhai, China
| | - James M. Tiedje
- Center for Microbial Ecology, Department of Plant, Soil, and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| |
Collapse
|
26
|
Du Z, Ruan Y, Chen J, Fang J, Xiao S, Shi Y, Zheng W. Global Trends and Hotspots in Research on the Health Risks of Organophosphate Flame Retardants: A Bibliometric and Visual Analysis. TOXICS 2024; 12:391. [PMID: 38922072 PMCID: PMC11209454 DOI: 10.3390/toxics12060391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 05/17/2024] [Accepted: 05/25/2024] [Indexed: 06/27/2024]
Abstract
BACKGROUND Organophosphate flame retardants (OPFRs) are compounds with a wide range of industrial and commercial applications and are mainly used as flame retardants and plasticizers. The global consumption of OPFRs has risen rapidly in recent decades, and they have been widely detected in environmental media. Unfortunately, OPFRs have been associated with many adverse health outcomes. The issue of the health risks of OPFRs is attracting increasing attention. Therefore, there is a need to review the current state of research and trends in this field to help researchers and policymakers quickly understand the field, identify new research directions, and allocate appropriate resources for further development of the OPFR health risk research field. METHODS This study statistically analyzed 1162 relevant publications included in the Web of Science Core Collection from 2003-2023. The internal and external features of the literature, such as publication trends, countries, authors, journals, and keywords, were quantitatively analyzed and visually presented to identify the research hotspots, compositions, and paradigms of the field and to horizontally and vertically analyze the development trends and structural evolution of the field. RESULTS The development of the field can be divided into three stages, and the field entered a period of rapid development in 2016. China (649 papers) is the most prolific country, followed by the United States (188 papers). The authors STAPLETON HM and WANG Y have the highest combined impact. International collaboration between countries and researchers still needs to be strengthened. Science of The Total Environment is the most frequently published journal (162 papers), and Environmental Science and Technology is the most frequently cited journal (5285 citations). Endocrine disruption, developmental toxicity, and neurotoxicity are the health effects of greatest interest. CONCLUSIONS Future research is expected to be multidisciplinary, and research hotspots may involve a comprehensive assessment of OPFR exposure in the population, exploration of the mechanisms of endocrine-disrupting effects and in vivo metabolic processes, and examination of the health effects of OPFR metabolites.
Collapse
Affiliation(s)
- Zhiyuan Du
- Key Laboratory of the Public Health Safety, Ministry of Education, Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; (Z.D.); (J.C.); (J.F.)
| | - Yuanyuan Ruan
- NHC Key Laboratory of Glycoconjugates Research, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China;
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Jiabin Chen
- Key Laboratory of the Public Health Safety, Ministry of Education, Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; (Z.D.); (J.C.); (J.F.)
| | - Jian Fang
- Key Laboratory of the Public Health Safety, Ministry of Education, Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; (Z.D.); (J.C.); (J.F.)
| | - Shuo Xiao
- Department of Pharmacology and Toxicology, Ernest Mario School of Pharmacy, Environmental and Occupational Health Sciences Institutes, Rutgers University, Piscataway, NJ 08854, USA;
| | - Yewen Shi
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Weiwei Zheng
- Key Laboratory of the Public Health Safety, Ministry of Education, Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China; (Z.D.); (J.C.); (J.F.)
- Center for Water and Health, School of Public Health, Fudan University, Shanghai 200032, China
| |
Collapse
|
27
|
Richardson SD, Manasfi T. Water Analysis: Emerging Contaminants and Current Issues. Anal Chem 2024; 96:8184-8219. [PMID: 38700487 DOI: 10.1021/acs.analchem.4c01423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Affiliation(s)
- Susan D Richardson
- Department of Chemistry and Biochemistry, University of South Carolina, JM Palms Center for GSR, 631 Sumter Street, Columbia, South Carolina 29208, United States
| | - Tarek Manasfi
- Eawag, Environmental Chemistry, Uberlandstrasse 133, Dubendorf 8600, Switzerland
| |
Collapse
|
28
|
Collins EMS, Hessel EVS, Hughes S. How neurobehavior and brain development in alternative whole-organism models can contribute to prediction of developmental neurotoxicity. Neurotoxicology 2024; 102:48-57. [PMID: 38552718 PMCID: PMC11139590 DOI: 10.1016/j.neuro.2024.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/01/2024] [Accepted: 03/23/2024] [Indexed: 04/12/2024]
Abstract
Developmental neurotoxicity (DNT) is not routinely evaluated in chemical risk assessment because current test paradigms for DNT require the use of mammalian models which are ethically controversial, expensive, and resource demanding. Consequently, efforts have focused on revolutionizing DNT testing through affordable novel alternative methods for risk assessment. The goal is to develop a DNT in vitro test battery amenable to high-throughput screening (HTS). Currently, the DNT in vitro test battery consists primarily of human cell-based assays because of their immediate relevance to human health. However, such cell-based assays alone are unable to capture the complexity of a developing nervous system. Whole organismal systems that qualify as 3 R (Replace, Reduce and Refine) models are urgently needed to complement cell-based DNT testing. These models can provide the necessary organismal context and be used to explore the impact of chemicals on brain function by linking molecular and/or cellular changes to behavioural readouts. The nematode Caenorhabditis elegans, the planarian Dugesia japonica, and embryos of the zebrafish Danio rerio are all suited to low-cost HTS and each has unique strengths for DNT testing. Here, we review the strengths and the complementarity of these organisms in a novel, integrative context and highlight how they can augment current cell-based assays for more comprehensive and robust DNT screening of chemicals. Considering the limitations of all in vitro test systems, we discuss how a smart combinatory use of these systems will contribute to a better human relevant risk assessment of chemicals that considers the complexity of the developing brain.
Collapse
Affiliation(s)
- Eva-Maria S Collins
- Swarthmore College, Biology, 500 College Avenue, Swarthmore, PA 19081, USA; Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Center of Excellence in Environmental Toxicology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Ellen V S Hessel
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, Bilthoven, 3721 MA, the Netherlands
| | - Samantha Hughes
- Department of Environmental Health and Toxicology, A-LIFE, Vrije Universiteit Amsterdam, de Boelelaan 1085, Amsterdam, 1081 HV, the Netherlands.
| |
Collapse
|
29
|
Reincke M, Arlt W, Damdimopoulou P, Köhrle J, Bertherat J. Endocrine disrupting chemicals are a threat to hormone health: a commentary on behalf of the ESE. Nat Rev Endocrinol 2024; 20:187-188. [PMID: 38388677 DOI: 10.1038/s41574-024-00958-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Affiliation(s)
- Martin Reincke
- Medizinische Klinik und Poliklinik IV, LMU Klinikum, LMU München, München, Germany.
| | - Wiebke Arlt
- MRC Laboratory of Medical Sciences, London, UK
- Institute of Clinical Sciences, Imperial College London, London, UK
| | - Pauliina Damdimopoulou
- Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Department of Gynecology and Reproductive Medicine, Karolinska University Hospital, Huddinge, Stockholm, Sweden
| | - Josef Köhrle
- Institut für Experimentelle Endokrinologie, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Jerome Bertherat
- Institut Cochin, Inserm U1016, CNRS UMR8104, Université Paris-Cité, Paris, France
| |
Collapse
|
30
|
Phillips KA, Chao A, Church RL, Favela K, Garantziotis S, Isaacs KK, Meyer B, Rice A, Sayre R, Wetmore BA, Yau A, Wambaugh JF. Suspect Screening Analysis of Pooled Human Serum Samples Using GC × GC/TOF-MS. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1802-1812. [PMID: 38217501 PMCID: PMC11459241 DOI: 10.1021/acs.est.3c05092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/15/2024]
Abstract
Humans interact with thousands of chemicals. This study aims to identify substances of emerging concern and in need of human health risk evaluations. Sixteen pooled human serum samples were constructed from 25 individual samples each from the National Institute of Environmental Health Sciences' Clinical Research Unit. Samples were analyzed using gas chromatography (GC) × GC/time-of-flight (TOF)-mass spectrometry (MS) in a suspect screening analysis, with follow-up confirmation analysis of 19 substances. A standard reference material blood sample was also analyzed through the confirmation process for comparison. The pools were stratified by sex (female and male) and by age (≤45 and >45). Publicly available information on potential exposure sources was aggregated to annotate presence in serum as either endogenous, food/nutrient, drug, commerce, or contaminant. Of the 544 unique substances tentatively identified by spectral matching, 472 were identified in females, while only 271 were identified in males. Surprisingly, 273 of the identified substances were found only in females. It is known that behavior and near-field environments can drive exposures, and this work demonstrates the existence of exposure sources uniquely relevant to females.
Collapse
Affiliation(s)
- Katherine A. Phillips
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Alex Chao
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Rebecca L. Church
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, NC 27709, USA
| | - Kristin Favela
- Southwest Research Institute, San Antonio, TX 78238, USA
| | - Stavros Garantziotis
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, NC 27709, USA
| | - Kristin K. Isaacs
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Brian Meyer
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
- Deceased April 2023
| | - Annette Rice
- U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Environmental Health Sciences, Clinical Research Unit, Durham, NC 27709, USA
| | - Risa Sayre
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Barbara A. Wetmore
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| | - Alice Yau
- Southwest Research Institute, San Antonio, TX 78238, USA
| | - John F. Wambaugh
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Computational Toxicology and Exposure, Research Triangle Park, NC 27711, USA
| |
Collapse
|
31
|
Zhang Z, Sangion A, Wang S, Gouin T, Brown T, Arnot JA, Li L. Chemical Space Covered by Applicability Domains of Quantitative Structure-Property Relationships and Semiempirical Relationships in Chemical Assessments. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 38263624 PMCID: PMC10882972 DOI: 10.1021/acs.est.3c05643] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
A significant number of chemicals registered in national and regional chemical inventories require assessments of their potential "hazard" concerns posed to humans and ecological receptors. This warrants knowledge of their partitioning and reactivity properties, which are often predicted by quantitative structure-property relationships (QSPRs) and other semiempirical relationships. It is imperative to evaluate the applicability domain (AD) of these tools to ensure their suitability for assessment purpose. Here, we investigate the extent to which the ADs of commonly used QSPRs and semiempirical relationships cover seven partitioning and reactivity properties of a chemical "space" comprising 81,000+ organic chemicals registered in regulatory and academic chemical inventories. Our findings show that around or more than half of the chemicals studied are covered by at least one of the commonly used QSPRs. The investigated QSPRs demonstrate adequate AD coverage for organochlorides and organobromines but limited AD coverage for chemicals containing fluorine and phosphorus. These QSPRs exhibit limited AD coverage for atmospheric reactivity, biodegradation, and octanol-air partitioning, particularly for ionizable organic chemicals compared to nonionizable ones, challenging assessments of environmental persistence, bioaccumulation capability, and long-range transport potential. We also find that a predictive tool's AD coverage of chemicals depends on how the AD is defined, for example, by the distance of a predicted chemical from the centroid of the training chemicals or by the presence or absence of structural features.
Collapse
Affiliation(s)
- Zhizhen Zhang
- School of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States
| | | | - Shenghong Wang
- School of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States
| | - Todd Gouin
- TG Environmental Research, Sharnbrook, Bedford MK44 1PL, U.K
| | - Trevor Brown
- ARC Arnot Research & Consulting, Toronto, Ontario M4M 1W4, Canada
| | - Jon A Arnot
- ARC Arnot Research & Consulting, Toronto, Ontario M4M 1W4, Canada
- Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario M1C 1A4, Canada
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Ontario M5S 1A8, Canada
| | - Li Li
- School of Public Health, University of Nevada, Reno, Reno, Nevada 89557, United States
| |
Collapse
|
32
|
Jones RR, White AJ. Invited Perspective: New Motivations and Future Directions for Investigating Environmental Risk Factors for Breast Cancer. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:11301. [PMID: 38197649 PMCID: PMC10777818 DOI: 10.1289/ehp13777] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 09/21/2023] [Accepted: 12/04/2023] [Indexed: 01/11/2024]
Affiliation(s)
- Rena R. Jones
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Rockville, Maryland, USA
| | - Alexandra J. White
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, DHHS, Research Triangle Park, North Carolina, USA
| |
Collapse
|
33
|
Qu Y, Keller V, Bachiller-Jareno N, Eastman M, Edwards F, Jürgens MD, Sumpter JP, Johnson AC. Significant improvement in freshwater invertebrate biodiversity in all types of English rivers over the past 30 years. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 905:167144. [PMID: 37730070 DOI: 10.1016/j.scitotenv.2023.167144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 09/14/2023] [Accepted: 09/14/2023] [Indexed: 09/22/2023]
Abstract
There remains a persistent concern that freshwater biodiversity is in decline and being threatened by pollution. As the UK, and particularly England, is a densely populated nation with rivers of modest dilution capacity, this location is very suitable to examine how freshwater biodiversity has responded to human pressures over the past 30 years. A long-term dataset of 223,325 freshwater macroinvertebrate records from 1989 to 2018 for England was retrieved and examined. A sub-set of approximately 200 sites per English Region (1515 sites in total with 62,514 samples), with the longest and most consistent records were matched with predicted wastewater exposure, upstream land cover and terrain characteristics (latitude, altitude, slope gradient and flow discharge). To understand changes in macroinvertebrate diversity and sensitivity with respect to these parameters, the biotic indices of (i) overall family richness, (ii) Ephemeroptera, Plecoptera, Trichoptera (EPT) family richness, and (iii) the Biological Monitoring Working Party (BMWP) scores of NTAXA (number of scoring taxa) and (iv) ASPT (average score per taxon) were selected. A review of how close the BMWP scores come to those expected at minimally impacted reference sites was included. For all latitudes, altitudes, channel slope, river size, wastewater exposure levels, and differing proportions of upstream woodland, seminatural, arable and urban land cover, all diversity or sensitivity indices examined improved over this period, although this improvement has slowed in some cases post 2003. Mean overall family richness has increased from 15 to 25 family groups, a 66 % improvement. The improvement in mean EPT family richness (3 to 10 families, >300 % improvement), which are considered to be particularly sensitive to pollution, implies macroinvertebrate diversity has benefited from a national improvement in critical components of water quality.
Collapse
Affiliation(s)
- Yueming Qu
- UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK
| | - Virginie Keller
- UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK
| | - Nuria Bachiller-Jareno
- UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK; University of Portsmouth, Portsmouth PO1 2UP, UK
| | - Michael Eastman
- UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK; Met Office, Exeter, EX1 3PB, UK
| | - Francois Edwards
- UK Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK; APEM Ltd, Chester CH4 0GZ, UK
| | | | | | | |
Collapse
|
34
|
Contini T, Béranger R, Multigner L, Klánová J, Price EJ, David A. A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:15301-15313. [PMID: 37796725 DOI: 10.1021/acs.est.3c04845] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/07/2023]
Abstract
Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.
Collapse
Affiliation(s)
- Thomas Contini
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, F-35000 Rennes, France
- RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, 602 00 Brno, Czech Republic
| | - Rémi Béranger
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, F-35000 Rennes, France
| | - Luc Multigner
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, F-35000 Rennes, France
| | - Jana Klánová
- RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, 602 00 Brno, Czech Republic
| | - Elliott J Price
- RECETOX, Faculty of Science, Masaryk University, Kotlářská 2, 602 00 Brno, Czech Republic
| | - Arthur David
- Univ Rennes, CHU Rennes, Inserm, EHESP, Irset (Institut de Recherche en Santé, Environnement et Travail) - UMR_S 1085, F-35000 Rennes, France
| |
Collapse
|