Chemical pollution: A growing peril and potential catastrophic risk to humanity

Enhanced photocatalytic degradation of methylene blue dye using eco-friendly synthesized rGO@ZnO nanocomposites

Industrial chemical pollutants such as methylene blue (MB) dye are released into the water body and potentially cause harm to the human and aquatic biosphere. Therefore, this study aims to synthesize eco-friendly nanocatalysts, i.e., reduced graphene oxide (rGO), zinc oxide (ZnO), and reduced graphene oxide-zinc oxide (rGO@ZnO) nanocomposites, for efficient photocatalytic degradation of MB dye. A graphite rod was obtained from waste dry cell batteries for the electrochemical exfoliation synthesis of graphene oxide (GO) and rGO. For the eco-friendly synthesis of ZnO and rGO@ZnO nanocatalysts, Croton macrostachyus leaf extract was used as a reducing and capping agent. The synthesized nanocatalysts were characterized using a UV-Vis spectrophotometer, Fourier transform infrared spectroscopy, X-ray diffraction, and scanning electron microscopy with energy-dispersive X-ray. The eco-friendly synthesized rGO, ZnO, and rGO@ZnO nanocatalysts were applied for the photocatalytic degradation of MB dye using direct sunlight irradiation. At optimum parameters, photocatalytic degradation of MB dye efficiency reached up to 66%, 96.5%, and 99.0%, respectively. Furthermore, kinetics of the photodegradation reaction based on rGO, ZnO, and rGO@ZnO nanocatalysts follow pseudo-first-order with a rate constant of 2.16 × 10-3 min-1, 4.97 × 10-3 min-1, and 5.03 × 10-3 min-1, respectively. Lastly, this study promotes a low catalyst load (20 mg) for the efficient photodegradation of MB dye.

Conflicts of Interest in the Assessment of Chemicals, Waste, and Pollution

Pollution by chemicals and waste impacts human and ecosystem health on regional, national, and global scales, resulting, together with climate change and biodiversity loss, in a triple planetary crisis. Consequently, in 2022, countries agreed to establish an intergovernmental science-policy panel (SPP) on chemicals, waste, and pollution prevention, complementary to the existing intergovernmental science-policy bodies on climate change and biodiversity. To ensure the SPP's success, it is imperative to protect it from conflicts of interest (COI). Here, we (i) define and review the implications of COI, and its relevance for the management of chemicals, waste, and pollution; (ii) summarize established tactics to manufacture doubt in favor of vested interests, i.e., to counter scientific evidence and/or to promote misleading narratives favorable to financial interests; and (iii) illustrate these with selected examples. This analysis leads to a review of arguments for and against chemical industry representation in the SPP's work. We further (iv) rebut an assertion voiced by some that the chemical industry should be directly involved in the panel's work because it possesses data on chemicals essential for the panel's activities. Finally, (v) we present steps that should be taken to prevent the detrimental impacts of COI in the work of the SPP. In particular, we propose to include an independent auditor's role in the SPP to ensure that participation and processes follow clear COI rules. Among others, the auditor should evaluate the content of the assessments produced to ensure unbiased representation of information that underpins the SPP's activities.

Recent Advances on Electrochemical Sensors for Detection of Contaminants of Emerging Concern (CECs)

Contaminants of Emerging Concern (CECs), a new category of contaminants currently in the limelight, are a major issue of global concern. The pervasive nature of CECs and their harmful effects, such as cancer, reproductive disorders, neurotoxicity, etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentrations of CECs can cause great impacts on living beings. They also have a nature of bioaccumulation. Thus, there is a great need to have efficient sensors for the detection of CECs to ensure a safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of the analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in the literature under each category for the detection of major CECs.

Global classification models for predicting acute toxicity of chemicals towards Daphnia magna

Molecular descriptors reflecting structural information on hydrophobicity, reactivity, polarizability, hydrogen bond and charged groups, were used to predict the toxicity (pLC50) of chemicals towards Daphnia magna with global quantitative structure-activity/toxicity relationship (QSAR/QSTR) models. A sufficiently large dataset including 1517 chemical toxicity to Daphnia magna was divided into a training set (758 pLC50) and a test set (759 pLC50). By applying random forest algorithm, two classification models, Class Model A and Class Model B were developed, having prediction accuracy, sensitivity and specificity above 85% for Class 1 (with pLC50 ≤ 4.48) and Class 2 (with pLC50 > 4.48). The Class Model A was based on nine molecular descriptors and RF parameters of nodesize = 1, ntree = 80 and mtry = 2, and yielded accuracy of 92.3% (training set), 85.6% (test set) and 88.9% (total data set). Class Model B was based on ten descriptors and parameters, nodesize = 1, ntree = 90 and mtry = 2, produced accuracy of 88.3% (training set), 86.8% (test set) and 87.5% (total data set). The two classification models were satisfactory compared with other classification model reported in the literature, although classification models in this work dealt with more samples. Thus, the two classification models with a larger applicability domain provided efficient tools for assessing chemical aquatic toxicity towards Daphnia magna.

Persistent organic pollutants and trace elements detected in New Zealand fur seals (long-nosed fur seal; Arctocephalus forsteri) from New South Wales, Australia, between 1998 and 2019

Environmental pollution is a growing threat to wildlife health and biodiversity. The relationship between marine mammals and pollutants is, however, complex and as new chemicals are introduced to ecosystems alongside concomitant, interacting threats such as climate change and habitat degradation, the cumulative impact of these stressors to wildlife continues to expand. Understanding the health of wildlife populations requires a holistic approach to identify potential threatening processes. In the context of environmental pollution in little studied wildlife species, it is important to catalogue the current exposome to develop effective biomonitoring programs that can support diagnosis of health impacts and management and mitigation of pollution. In New South Wales, Australia, the New Zealand fur seal (Arctocephalus forsteri) is a resident species experiencing population growth following devastating historic hunting practices. This study presents a retrospective investigation into the exposure of New Zealand fur seals to a range of synthetic organic compounds and essential and non-essential trace elements. Liver tissue from 28 seals were broadly analyzed to assess concentrations of organochlorine and organophosphate pesticides, polychlorinated biphenyls, per- and polyfluoroalkyl substances, and essential and non-essential trace elements. In addition to contributing extensive pollution baseline data for the species, the work explores the influence of sex, age, and body condition on accumulation patterns. Further, based on these findings, it is recommended that a minimum of 11 juvenile male New Zealand fur seals are sampled and analyzed annually in order to maintain a holistic biomonitoring approach for this population.

Sex differences in frailty among older adults

By definition, aging is a natural, gradual and continuous process. On the other hand, frailty reflects the increase in vulnerability to stressors and shortens the time without disease (health span) while longevity refers to the length of life (lifespan). The average life expectancy has significantly increased during the last few decades. A longer lifespan has been accompanied by an increase in frailty and decreased independence in older adults, with major differences existing between men and women. For example, women tend to live longer than men but also experience higher rates of frailty and disability. Sex differences prevent optimization of lifestyle interventions and therapies to effectively prevent frailty. Sex differences in frailty and aging are rooted in a complex interplay between uncontrollable (genetic, epigenetic, physiological), and controllable factors (psychosocial and lifestyle factors). Thus, understanding the underlying causes of sex differences in frailty and aging is essential for developing personalized interventions to promote healthy aging and improve quality of life in older men and women. In this review, we have discussed the key contributors and knowledge gaps related to sex differences in aging and frailty.

Assessing human internal exposure to chemicals at different physical activity levels: A physiologically based kinetic (PBK) model incorporating metabolic equivalent of task (MET)

Physical activity levels have the potential to impact human internal exposure to environmental chemicals. However, the current lack of simple modeling approaches hinders the high-throughput screening of chemical exposure at different physical activity levels. To address this gap, this study proposes a straightforward model for assessing human internal exposure to chemicals. Our approach is based on the physiologically based kinetic (PBK) model and utilizes the metabolic equivalent of task (MET) to characterize internal exposure to chemicals at varying activity levels. To facilitate the application of this model, we have developed an Excel-based operation tool, allowing users to easily modify the MET value and generate simulation results for different physical activity levels. The simulation results demonstrate that as physical activity levels increase, the biotransfer factors (BTFs) of chemicals decrease, suggesting that higher physical activity levels reduce the bioaccumulation potential of chemicals. The intensified physical activity enhances the overall elimination kinetics of chemicals from the human body. However, the simulated concentrations of chemicals in the human body increase with higher physical activity levels, due to the significantly increased external exposure to chemicals, such as through inhalation. Our proposed modeling approach, along with the operational tool, enables high-throughput simulation of human chronic internal exposure to chemicals at different physical activity levels, where the findings can assist in screening chemicals for further health risk assessment. To accomplish this, the model incorporates certain assumptions and utilizes generic model input values. However, due to the intricate nature of the interaction between external and internal exposures at different physical activity levels, validating the simulation through experimental studies becomes challenging and is not performed in this study. For future studies, we recommend incorporating more MET-related physiological input variables, improving energy balance estimates, comprehending external exposure estimates, and conducting cohort studies to enhance and validate the proposed modeling approach.

Research progress and prospect of glomalin-related soil protein in the remediation of slightly contaminated soil

Soil pollution caused by organic pollutants and potentially toxic elements poses a serious threat to sustainable agricultural development, global food security and human health. Therefore, strategies for reducing soil pollution are urgently required. Arbuscular mycorrhizal fungi (AMF)-assisted phytoremediation is widely recognized for its ability to remediate slightly-contaminated soil. Glomalin-related soil protein (GRSP) production by AMF is considered a vital mechanism of AMF-assisted phytoremediation. GRSP is widespread in soils and may contribute to the remediation of slightly contaminated soils. GRSP facilitates stabilization of pollutants in soils by interacting with pollutants owing to its abundant functional groups, recalcitrance, and long turnover time. It also enhances soil bioremediation and phytoremediation by stimulating soil microbial activity, improving soil structure, and providing nutrients for plants. However, research on GRSP is still in its early stages, and studies on contaminated soil remediation are limited. The effectiveness of GRSP in situ remediation remains to be proved. This review summarizes current knowledge regarding the GRSP distribution and its contribution to the remediation of slightly contaminated soils. Additionally, we present strategies to increase the GRSP content in contaminated soils, as well as prospects for future studies on the use of GRSP in contaminated soil remediation. This study focuses on recent developments that aim to improve awareness of the role of GRSP in soil remediation and relevant future directions.

Discussion. Has the human population become a sentinel for the adverse effects of PFAS contamination on wildlife health and endangered species?

Global contamination with per- and polyfluoroalkyl substances (PFAS) poses a threat to both human health and the environment, with significant implications for ecological conservation policies. A growing list of peer-reviewed publications indicates that PFAS can harm wildlife health and that the adverse effects associated with PFAS exposure in wildlife are in concordance with human epidemiological studies. The correlation of cross-species data supports a unique perspective that humans can be regarded as a sentinel for PFAS effects in other species. The health harms due to PFAS are potentially most concerning for populations of endangered and threatened species that are simultaneously exposed to PFAS and other toxic pollutants, and also face threats to their survival due to habitat loss, degradation of ecosystems, and over-harvesting. Human epidemiological studies on the PFAS doses associated with health harm present a rich source of information about potential impacts on wildlife health due to PFAS. Our analysis suggests that national and international efforts to restrict the discharges of PFAS into the environment and to clean up PFAS-contaminated sites present an opportunity to protect wildlife from chemical pollution and to advance species conservation worldwide.

Application of CRISPR/Cas9-based genome editing in ecotoxicology

Chemicals are widely used and released into the environment, and their degradation, accumulation, migration, and transformation processes in the environment can pose a threat to the ecosystem. The advancement in analytical methods with high-throughput screening of biomolecules has revolutionized the way toxicologists used to explore the effects of chemicals on organisms. CRISPR/Cas is a newly developed tool, widely used in the exploration of basic science and biologically engineered products given its high efficiency and low cost. For example, it can edit target genes efficiently, and save loss of the crop yield caused by environmental pollution as well as gain a better understanding of the toxicity mechanisms from various chemicals. This review briefly introduces the development history of CRISPR/Cas and summarizes the current application of CRISPR/Cas in ecotoxicology, including its application on improving crop yield and drug resistance towards agricultural pollution, antibiotic pollution and other threats. The benefits by applying the CRISPR/Cas9 system in conventional toxicity mechanism studies are fully demonstrated here together with its foreseeable expansions in other area of ecotoxicology. Finally, the prospects and disadvantages of CRISPR/Cas system in the field of ecotoxicology are also discussed.

Removal and detoxification of pentahalogenated phenols using a photocatalytically induced enzymatic process

Poly-halogenated phenols generated from a range of industrial processes can find their way into rivers and ground water. Here we report on a potential treatment for reducing the toxicity of these aqueous pollutants using two highly toxic penta-halogenated phenols (pentachlorophenol (PCP) and pentabromophenol (PBP)) as surrogates. Solutions were passed through a glass column packed with a silica support fused with titanium dioxide (TiO2) and horseradish peroxidase (HRP) immobilized on its TiO2/glass surface (HRP-Tglass). TiO2 photocatalysis was activated through irradiation with UVB (320 nm) which in turn activated the HRP. Two operational flow rates (0.5 and 1.25 mL min-1; hydraulic retention times (HRTs) of 20 and 8 min, respectively), tested the effect of retention time on the extent of degradation and reduction in toxicity of the treated effluent. Microtox® was used to measure the toxicity of the substrate and its by-products at both flow rates. At the highest flow rate, dehalogenation was limited (removal of 37 % chlorine and 22 % bromine) and the toxicity of the reaction products increased. At the lowest flow rate, the longer exposure time resulted in approximately 97 % and 96 % transformation of PCP and PBP, respectively, a greater degree of dehalogenation (removal of 65 % chlorine and 70 % bromine) and a substantial decrease in toxicity of the treated solutions. The higher toxicity of effluent from the higher flow rate was attributed to the initial degradation products being more toxic than the substrates. With a longer HRT, these were then further broken down to less toxic products. Additional toxicity tests (Hydra hexactinella (Hydra) and Chinese Hamster Ovary (CHO) cell toxicity were conducted on the effluent from the lowest flow rate. Both were less sensitive than the Microtox test, with Hydra proving more sensitive than CHO. The novelty of this work is the toxicity risk assessment of the products resulting from the use of a spatially separated immobilized enzyme and photooxidation system. The system was robust and showed no decrease in treatment efficacy over 10 h.

Analysis and derivation of the marine water quality criteria of phenol for Korean seas

Marine water quality criteria (WQC) have to be determined prior to the derivation of water quality based effluent limitations (WQBELs) for hazardous and noxious substances (HNS) discharged from marine industrial facilities. In this study, we carried out toxicity tests using ten native marine organisms and analyzed international toxicity data and data tested in this study to derive the WQC of phenol for Korean seas. By converting acute values to chronic ones with ACRs (acute-chronic ratios) of each trophic level according to well-verified method, we derived provisional WQC (0.96 mg/L) of phenol for Korean seas for the first time. The procedure to derive marine WQC and results of this study could provide the essential information for the establishment of national marine WQC and WQBELs for HNS discharged from marine industrial facilities.

In silico interactions and deep neural network modeling for toxicity profile of methyl methanesulfonate

In this study, the toxicity induced by the alkylating agent methyl methanesulfonate (MMS) in Allium cepa L. was investigated. For this aim, bulbs were divided into 4 groups as control and application (100, 500 and 4000 µM MMS) and germinated for 72 h at 22-24 °C. At the end of the germination period root tips were collected and made ready for analysis by applying traditional preparation methods. Germination, root elongation, weight, mitotic index (MI) values, micronucleus (MN) and chromosomal abnormality (CAs) numbers, malondialdehyde (MDA) levels, superoxide dismutase (SOD) and catalase (CAT) activities and anatomical structures of bulbs were used as indicators to determine toxicity. Moreover the extent of DNA fragmentation induced by MMS was determined by comet assay. To confirm the DNA fragmentation induced by MMS, the DNA-MMS interaction was examined with molecular docking. Correlation and principal component analyses (PCA) were performed to examine the relationship between all parameters and understand the underlying structure and relationships among these parameters. In the present study, a deep neural network (DNN) with two hidden layers implemented in Matlab has been developed for the comparison of the estimated data with the real data. The effect of MDA levels, SOD and CAT activities at 4 different endpoints resulting from administration of various concentrations of MMS, including MN, MI, CAs and DNA damage, was attempted to be estimated by DNN model. It is assumed that the predicted results are in close agreement with the actual data. The effectiveness of the model was evaluated using 4 different metrics, MAE, MAPE, RMSE and R2, which together show that the model performs commendably. As a result, the highest germination, root elongation, weight gain and MI were measured in the control group. MMS application caused a decrease in all physiological parameters and an increase in cytogenetic (except MI) and biochemical parameters. MMS application caused an increase in antioxidant enzyme levels (SOD and CAT) up to a concentration of 500 µM and a decrease at 4000 µM. MMS application induced different types of CAs and anatomical damages in root meristem cells. The results of the comet assay showed that the severity of DNA fragmentation increased with increasing MMS concentration. Molecular docking analysis showed a strong DNA-MMS interaction. The results of correlation and PCA revealed significant positive and negative interactions between the studied parameters and confirmed the interactions of these parameters with MMS. It has been shown that the DNN model developed in this study is a valuable resource for predicting genotoxicity due to oxidative stress and lipid peroxidation. In addition, this model has the potential to help evaluate the genotoxicity status of various chemical compounds. At the end of the study, it was concluded that MMS strongly supports a versatile toxicity in plant cells and the selected parameters are suitable indicators for determining this toxicity.

Harnessing dual applications of a novel ascomycetes yeast, Starmerella cerana sp. nov., as a biocatalyst for stereoselective ketone reduction and biosurfactant production

Introduction: New bioresources for catalytic application and fine chemical synthesis are the need of the hour. In an effort to find out new biocatalyst for oxidation-reduction reaction, leading to the synthesis of chiral intermediates, novel yeast were isolated from unique niche and employed for the synthesis of value added compounds. Methods: To determine the genetic relatedness of the isolated strain, HSB-15T, sequence analysis of the internal transcribed spacer (ITS) and D1/D2 domains of the 26S rRNA gene sequence was carried out. The distinctive features of the strain HSB-15T were also identified by phenotypic characterization. The isolated strain HSB-15T was employed for the reduction of selected naphthyl ketones to their corresponding alcohols and a biosurfactant was isolated from its culture broth. Results: The analysis of the ITS and D1/D2 domains of the 26S rRNA gene revealed that strain HSB-15T is closely related to the type strain of Starmerella vitae (CBS 15147T) with 96.3% and 97.7% sequence similarity, respectively. However, concatenated sequences of the ITS gene and D1/D2 domain showed 94.6% sequence similarity. Phenotypic characterization indicated significant differences between strain HSB-15T and its closely related species and consequently, it was identified as a novel species, leading to the proposal of the name Starmerella cerana sp. nov. The strain was able to reduce selected naphthyl ketones to their corresponding alcohols with remarkable efficiency, within a 12-hours. The strain HSB-15T also produced a surfactant in its culture broth, identified as sophorolipid upon analysis. Discussion: The study explored the potential of the novel strain, HSB-15T, as a whole-cell biocatalyst for the reduction of naphthyl ketones to their corresponding alcohols and also reports its capability to produce sophorolipid, a biosurfactant, in its culture broth. This dual functionality of HSB-15T both as biocatalyst and biosurfactant producer enhances its applicability in biotechnology and environmental science.

Machine learning strategy on activation energy of environmental heterogeneous reactions and its application to atmospheric formation of typical montmorillonite-bound phenoxy radicals

Heterogeneous transformation of organic pollutants into more toxic chemicals poses substantial health risks to humans. Activation energy is an important indicator that help us to understand transformation efficacy of environmental interfacial reactions. However, the determination of activation energies for large numbers of pollutants using either the experimental or high-accuracy theoretical methods is expensive and time-consuming. Alternatively, the machine learning (ML) method shows the strength in predictive performance. In this study, using the formation of a typical montmorillonite-bound phenoxy radical as an example, a generalized ML framework RAPID was proposed for activation energy prediction of environmental interfacial reactions. Accordingly, an explainable ML model was developed to predict the activation energy via easily accessible properties of the cations and organics. The model developed by decision tree (DT) performed best with the lowest root-mean-squared error (RMSE = 0.22) and the highest coefficient of determination values (R2 score = 0.93), the underlying logic of which was well understood by combining model visualization and SHapley Additive exPlanations (SHAP) analysis. The performance and interpretability of the established model suggest that activation energies can be predicted by the well-designed ML strategy, and this would allow us to predict more heterogeneous transformation reactions in the environmental field.

A One-Health environmental risk assessment of contaminants of emerging concern in London's waterways throughout the SARS-CoV-2 pandemic

The SARS-CoV-2 pandemic had huge impacts on global urban populations, activity and health, yet little is known about attendant consequences for urban river ecosystems. We detected significant changes in occurrence and risks from contaminants of emerging concern (CECs) in waterways across Greater London (UK) during the pandemic. We were able to rapidly identify and monitor large numbers of CECs in n = 390 samples across 2019-2021 using novel direct-injection liquid chromatography-mass spectrometry methods for scalable targeted analysis, suspect screening and prioritisation of CEC risks. A total of 10,029 measured environmental concentrations (MECs) were obtained for 66 unique CECs. Pharmaceutical MECs decreased during lockdown in 2020 in the R. Thames (p ≤ 0.001), but then increased significantly in 2021 (p ≤ 0.01). For the tributary rivers, the R. Lee, Beverley Brook, R. Wandle and R. Hogsmill were the most impacted, primarily via wastewater treatment plant effluent and combined sewer overflows. In the R. Hogsmill in particular, pharmaceutical MEC trends were generally correlated with NHS prescription statistics, likely reflecting limited wastewater dilution. Suspect screening of ∼ 1,200 compounds tentatively identified 25 additional CECs at the five most impacted sites, including metabolites such as O-desmethylvenlafaxine, an EU Watch List compound. Lastly, risk quotients (RQs) ≥ 0.1 were calculated for 21 compounds across the whole Greater London freshwater catchment, of which seven were of medium risk (RQ ≥ 1.0) and three were in the high-risk category (RQ ≥ 10), including imidacloprid (RQ = 19.6), azithromycin (15.7) and diclofenac (10.5). This is the largest spatiotemporal dataset of its kind for any major capital city globally and the first for Greater London, representing ∼ 16 % of the population of England, and delivering a foundational One-Health case study in the third largest city in Europe across a global pandemic.

The Foreseeable Future of Spent Lithium-Ion Batteries: Advanced Upcycling for Toxic Electrolyte, Cathode, and Anode from Environmental and Technological Perspectives

With the rise of the new energy vehicle industry represented by Tesla and BYD, the need for lithium-ion batteries (LIBs) grows rapidly. However, owing to the limited service life of LIBs, the large-scale retirement tide of LIBs has come. The recycling of spent LIBs has become an inevitable trend of resource recovery, environmental protection, and social demand. The low added value recovery of previous LIBs mostly used traditional metal extraction, which caused environmental damage and had high cost. Beyond metal extraction, the upcycling of spent LIBs came into being. In this work, we have outlined and particularly focus on sustainable upcycling technologies of toxic electrolyte, cathode, and anode from spent LIBs. For electrolyte, whether electrolyte extraction or decomposition, restoring the original electrolyte components or decomposing them into low-carbon energy conversion is the goal of electrolyte upcycling. Direct regeneration and preparation of advanced materials are the best strategies for cathodic upcycling with the advantages of cost and energy consumption, but challenges remain in industrial practice. The regeneration of advanced graphite-based materials and battery-grade graphite shows us the prospect of regeneration of anode. Furthermore, the challenges and future development of spent LIBs upcycling are summarized and discussed from technological and environmental perspectives.

Zinc nanoparticles encapsulated in porous biopolymer beads for reduction of water pollutants and antimicrobial activity

This work focuses on the preparation of composite beads from alginate crosslinked with copper at several loading percent and also loaded with ZnNPs. Th obtained samples were applied as catalysts for the reduction of the organic polluants 4-NP, MB, OG, MO, and CR in simple and binary systems. XRD results and TEM images confirmed the presence of ZnNPs in the polymer matrix. XRF and TGA analysis showed that the percentage of the cross-linking agent significantly influences the content of ZnNPs as well as the thermal stability of the resulting material. The catalytic activity of the composite beads showed that the Cu(4 %)-ALG(ZnNPs) sample was the best catalyst for all pollutants. In the simple system, the recorded rate constants for MB, MO, 4-NP, OG, and CR were 0.0133 s-1, 0.0076 s-1, 0.005 s-1, 0.0042 s-1, 0.0036 s-1, respectively. The catalyst was more selective towards the cationic MB dye for binary systems. For antibacterial and antifungal applications, the different materials containing ZnNPs and their counterparts containing Zn2+ were found to be active across all bacterial strains (Gram positive and Gram negative) as well as fungi, and the Zn2+-containing composites in particular performed better across all bacteria and fungi.

Chemical Mixtures and Multiple Stressors: Same but Different?

Ecosystems are strongly influenced by multiple anthropogenic stressors, including a wide range of chemicals and their mixtures. Studies on the effects of multiple stressors have largely focussed on nonchemical stressors, whereas studies on chemical mixtures have largely ignored other stressors. However, both research areas face similar challenges and require similar tools and methods to predict the joint effects of chemicals or nonchemical stressors, and frameworks to integrate multiple chemical and nonchemical stressors are missing. We provide an overview of the research paradigms, tools, and methods commonly used in multiple stressor and chemical mixture research and discuss potential domains of cross-fertilization and joint challenges. First, we compare the general paradigms of ecotoxicology and (applied) ecology to explain the historical divide. Subsequently, we compare methods and approaches for the identification of interactions, stressor characterization, and designing experiments. We suggest that both multiple stressor and chemical mixture research are too focused on interactions and would benefit from integration regarding null model selection. Stressor characterization is typically more costly for chemical mixtures. While for chemical mixtures comprehensive classification systems at suborganismal level have been developed, recent classification systems for multiple stressors account for environmental context. Both research areas suffer from rather simplified experimental designs that focus on only a limited number of stressors, chemicals, and treatments. We discuss concepts that can guide more realistic designs capturing spatiotemporal stressor dynamics. We suggest that process-based and data-driven models are particularly promising to tackle the challenge of prediction of effects of chemical mixtures and nonchemical stressors on (meta-)communities and (meta-)food webs. We propose a framework to integrate the assessment of effects for multiple stressors and chemical mixtures. Environ Toxicol Chem 2023;42:1915-1936. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency

Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.

Synthesis of TiO2-SiO2-Ag/Fiberglass with Antibacterial Properties and Its Application for Air Cleaning

The TiO₂-SiO₂-Ag/fiberglass with antibacterial properties under UV light irradiation was synthesized. The effects of compositions of TiO₂-SiO₂-Ag/fiberglass, optical, and textural characteristics on the antibacterial activity were studied. The TiO₂-SiO₂-Ag film was coated on the surface of fiberglass carrier filaments. The temperature effect on the formation of the TiO₂-SiO₂-Ag film was established by thermal analysis, and the temperature treatment mode was selected as 300 °C for 30 min, 400 °C for 30 min, 500 °C for 30 min, and 600 °C for 30 min. The influence of silicon oxide and silver additives on the antibacterial properties of TiO₂-SiO₂-Ag films was established. Increasing the treatment temperature of the materials up to 600 °C increased the thermal stability of the titanium dioxide anatase phase, while the values of optical characteristics decreased: the film thickness decreased to 23.92 ± 1.24 nm, the refractive index decreased to 2.154 ± 0.002, the energy of the band gap width decreased to 2.8 ± 0.5, and the light absorption shifted to the visible-light regime, which is important for photocatalytic reactions. The results showed that the use of TiO₂-SiO₂-Ag/fiberglass allows significant decrease in the value of CFU microbial cells to 125 CFU m^-3.

Data driven toxicity assessment of organic chemicals against Gammarus species using QSAR approach

Nowadays, organic chemicals play an essential role in almost all walks of life and have become indispensable to modern society. However, the continually synthesized chemicals and the numerous potential adverse endpoints against living organisms increasingly promote the regulators regarding the computational approach as a crucial supplement and an alternative to the traditional animal tests in chemical risk assessment. In this present research, we evaluated the ecotoxicity of chemicals against four typical Gammarus species, which constituted a critical element in detritus cycle and also the recommended species for water monitoring. We first screened the molecular descriptors based on the Genetic Algorithm and then developed the Quantitative Structure-Activity Relationship models using the Multiple Linear Regression method. The statistical results from various validation metrics suggested that the obtained models were internally robust and externally predictive. The application domain analysis based on the leverage approach and standardized residual method demonstrated the broad application range of each model. The interpretation of molecular descriptors in each model suggested that the chemicals with higher polarity and hydrophilicity tend to be less toxic, whereas the lipophilic moieties would enhance the chemical toxicity. Meanwhile, the other selected descriptors, such as Chi-cluster, heterocyclic, and distance matrix descriptors, manifested that the chemical toxicity was also affected by molecular branching, connectivity, electrotopological state, and other various properties. In summary, the present work proposed well-performed QSAR models and clarified the possible toxic mechanism of chemicals against Gammarus species. The obtained models could help predict the toxicity data and conduct a preliminary risk assessment, thus guiding the subsequent animal tests and reducing the assessment cost.

Linking Transthyretin-Binding Chemicals and Free Thyroid Hormones: In Vitro to In Vivo Extrapolation Based on a Competitive Binding Model

Large numbers of pollutants competitively inhibit the binding between thyroid hormones and transthyretin (TTR) in vitro. However, the impact of this unintended binding on free thyroid hormones in vivo has not yet been characterized. Herein, we established a quantitative in vitro to in vivo extrapolation (QIVIVE) method based on a competitive binding model to quantify the effect of TTR-binding chemicals on free thyroid hormones in human blood. Twenty-five TTR-binding chemicals including 6 hydroxyl polybromodiphenyl ethers (OH-PDBEs), 6 hydroxyl polychlorobiphenyls (OH-PCBs), 4 halogenphenols, 5 per- and polyfluorinated substances (PFASs), and 4 phenols were selected for investigation. Incorporating the in vitro binding parameters and human exposure data, the QIVIVE model could well predict the in vivo effect on free thyroid hormones. Co-exposure to twenty-five typical TTR-binding chemicals resulted in median increases of 0.080 and 0.060% in circulating levels of free thyroxine (FT4) and free triiodothyronine (FT3) in the general population. Individuals with occupational exposure to TTR-binding chemicals suffered 1.88-32.2% increases in free thyroid hormone levels. This study provides a quantitative tool to evaluate the thyroid-disrupting risks of TTR-binding chemicals and proposes a new framework for assessing the in vivo effects of chemical exposures on endogenous molecules.

FAIR environmental and health registry (FAIREHR)- supporting the science to policy interface and life science research, development and innovation

The environmental impact on health is an inevitable by-product of human activity. Environmental health sciences is a multidisciplinary field addressing complex issues on how people are exposed to hazardous chemicals that can potentially affect adversely the health of present and future generations. Exposure sciences and environmental epidemiology are becoming increasingly data-driven and their efficiency and effectiveness can significantly improve by implementing the FAIR (findable, accessible, interoperable, reusable) principles for scientific data management and stewardship. This will enable data integration, interoperability and (re)use while also facilitating the use of new and powerful analytical tools such as artificial intelligence and machine learning in the benefit of public health policy, and research, development and innovation (RDI). Early research planning is critical to ensuring data is FAIR at the outset. This entails a well-informed and planned strategy concerning the identification of appropriate data and metadata to be gathered, along with established procedures for their collection, documentation, and management. Furthermore, suitable approaches must be implemented to evaluate and ensure the quality of the data. Therefore, the 'Europe Regional Chapter of the International Society of Exposure Science' (ISES Europe) human biomonitoring working group (ISES Europe HBM WG) proposes the development of a FAIR Environment and health registry (FAIREHR) (hereafter FAIREHR). FAIR Environment and health registry offers preregistration of studies on exposure sciences and environmental epidemiology using HBM (as a starting point) across all areas of environmental and occupational health globally. The registry is proposed to receive a dedicated web-based interface, to be electronically searchable and to be available to all relevant data providers, users and stakeholders. Planned Human biomonitoring studies would ideally be registered before formal recruitment of study participants. The resulting FAIREHR would contain public records of metadata such as study design, data management, an audit trail of major changes to planned methods, details of when the study will be completed, and links to resulting publications and data repositories when provided by the authors. The FAIREHR would function as an integrated platform designed to cater to the needs of scientists, companies, publishers, and policymakers by providing user-friendly features. The implementation of FAIREHR is expected to yield significant benefits in terms of enabling more effective utilization of human biomonitoring (HBM) data.

Safe and just Earth system boundaries

The stability and resilience of the Earth system and human well-being are inseparably linked^1-3, yet their interdependencies are generally under-recognized; consequently, they are often treated independently^4,5. Here, we use modelling and literature assessment to quantify safe and just Earth system boundaries (ESBs) for climate, the biosphere, water and nutrient cycles, and aerosols at global and subglobal scales. We propose ESBs for maintaining the resilience and stability of the Earth system (safe ESBs) and minimizing exposure to significant harm to humans from Earth system change (a necessary but not sufficient condition for justice)⁴. The stricter of the safe or just boundaries sets the integrated safe and just ESB. Our findings show that justice considerations constrain the integrated ESBs more than safety considerations for climate and atmospheric aerosol loading. Seven of eight globally quantified safe and just ESBs and at least two regional safe and just ESBs in over half of global land area are already exceeded. We propose that our assessment provides a quantitative foundation for safeguarding the global commons for all people now and into the future.

The preparation of difluoromethylated indoles via electrochemical oxidation under catalyst- and oxidant-free conditions

A green and efficient electrochemical method for the preparation of difluoromethylated indoles has been developed. In this work, sodium difluoromethanesulfinate (HCF₂SO₂Na) was used as the fluorinating reagent, and various indole derivatives with difluoromethylation at the C-2 position were obtained in moderate to good yields under catalyst- and oxidant-free conditions. Moreover, this C-2 difluoromethylation protocol is operationally simple, proceeds at room temperature, and can be easily scaled up. Cyclic voltammetry (CV) and control experiments indicated that this transformation may proceed via a radical pathway.

Environmental Exposure Science and Human Health

Human health and environmental exposure form an inseparable binomial [...].

Effects of endocrine disrupting compounds on female fertility

Endocrine Disrupting Compounds or Chemicals (EDCs) constitute an extensive and varied group of mostly non-natural chemicals that have the ability to imitate any aspect of hormone action, perturbing many physiological functions in humans and animals. As for female fertility, several EDCs are associated with adverse effects in the regulation of steroidogenesis, higher miscarriage rates as well as lower fertilization and embryo implantation rates and some of them are considered to decrease the number of high-quality embryos in assisted reproductive technology (ART) pregnancy. The most common EDCs are pesticides, hexachlorobenzene (HCB), hexachlorocyclohexane (HCH) and especially phthalates and bisphenols which are used in thousands of products as plasticizers. Among all, Bisphenol A (BPA) is one of the most permeating and well-studied EDCs. BPA's action resembles that of estradiol affecting negatively the female reproductive system in various ways. This review summarizes the most recent literature on the impact of EDCs in female fertility.

Fragrance materials affect life history parameters and gene expression in Daphnia magna: An emerging issue for freshwater ecosystems

A chronic toxicity test (21 d exposure) with the model organism Daphnia magna was performed to study the single-compound and combined effects of four fragrance materials (FMs), including musk xylene (MX), Celestolide™ (ADBI), Galaxolide™ (HHCB), and ethylene brassylate (MT). Furthermore, the transcriptional responses of ten target genes related to detoxification, molting and reproduction (DHR96, P-gp, CYP360A8, GST, CYP314, EcRb, Vtg, CAT, GPX, and GCLC) were determined by performing a quantitative real-time polymerase chain reaction (qRT‒PCR) after juvenile D. magna was exposed for 48 h. The results showed that MX, ADBI and HHCB affected development and reproduction after chronic exposure at a concentration of 10 μg L^-1. Conversely, MT did not affect reproduction, growth or molting during the 21 d exposure. In juvenile D. magna, gene expression was significantly altered by ADBI (DHR96, CYP260A8, and GCLC) and MX (DHR96, CYP360A8, EcRb, Vtg, CYP314, and GCLC) but not by HHCB. These results suggest that compared to biochemical measures, conventional biological endpoints provide more informative data regarding the effects of this FM. Compared to single substances in the chronic test, the mixture of the four FMs showed effects at lower concentrations and increased gene expression for EcRb and CYP314 during juvenile exposure, indicating a possible additive or synergistic effect of the four FMs compared to single compound exposure.

The Impacts and Analysis of Individual and Social Risks of the Stochastic Emission of Benzene from Floating-Roof Tanks Using Response Surface Analysis and MPACT Model

In the present study, the researchers used an integrated approach composed of response surface analysis (RSM) and MPACT model to predict fatality rates caused by benzene emitted from floating-roof tanks. RSM scenarios were configured in Expert Design (version 7.0) software using the central composite design (CCD) method and five variables of wind speed, relative humidity, atmospheric temperature, failure diameter, and emission height were considered. Continuous Pasquill-Gifford Gaussian model was used to estimate the results of the RSM scenarios. The response values were considered for exposure concentrations above 50 ppm (slight damages), 150 ppm (moderate damage), and 1000 ppm (high damage). The analysis of individual and social risks for each scenario was done using the MPACT model in SAFETI program (version 8.22) by providing two variables of population characteristics and the frequency of tank wall failure. The results showed that atmospheric temperature, wind speed, failure diameter, and emission height have positive effects on the dispersion of the cloud of toxic benzene vapor with a concentration of 1000 ppm. Intolerable individual risk distances were estimated to be lower for indoor environments than for outdoor. Maximum distances of intolerable individual risks for the worst-case scenarios were estimated up to 2500 m from the emission point, which resulted from exposure to a concentration of 1000-ppm benzene. Results regarding the estimation of social risks showed that over 1600 fatalities should be expected under the worst-case scenarios. The three factors of high temperature, low wind speed, and low emission height play a major role in the occurrence of scenarios with the highest fatalities. High wind speed and high emission height were the most important factors in most scenarios with zero fatalities rate. Generally, the findings of this study show the necessity to provide an emergency response plan in the studied industry in both autumn and winter due to low wind speed. However, the coupling of the developed statistical models based on regional meteorological conditions with the MPACT model can help researchers to design an emergency response plan to deal with leakage incidents in petrochemical industries.

Contaminants of Emerging Concern (CECs) and Male Reproductive Health: Challenging the Future with a Double-Edged Sword

Approximately 9% of couples are infertile, with half of these cases relating to male factors. While many cases of male infertility are associated with genetic and lifestyle factors, approximately 30% of cases are still idiopathic. Contaminants of emerging concern (CECs) denote substances identified in the environment for the first time or detected at low concentrations during water quality analysis. Since CEC production and use have increased in recent decades, CECs are now ubiquitous in surface and groundwater. CECs are increasingly observed in human tissues, and parallel reports indicate that semen quality is continuously declining, supporting the notion that CECs may play a role in infertility. This narrative review focuses on several CECs (including pesticides and pharmaceuticals) detected in the nearshore marine environment of False Bay, Cape Town, South Africa, and deliberates their potential effects on male fertility and the offspring of exposed parents, as well as the use of spermatozoa in toxicological studies. Collective findings report that chronic in vivo exposure to pesticides, including atrazine, simazine, and chlorpyrifos, is likely to be detrimental to the reproduction of many organisms, as well as to sperm performance in vitro. Similarly, exposure to pharmaceuticals such as diclofenac and naproxen impairs sperm motility both in vivo and in vitro. These contaminants are also likely to play a key role in health and disease in offspring sired by parents exposed to CECs. On the other side of the double-edged sword, we propose that due to its sensitivity to environmental conditions, spermatozoa could be used as a bioindicator in eco- and repro-toxicology studies.

Levels and sources of hydrocarbons in the Patos Lagoon estuary and Cassino Beach mud bank (South Atlantic, Brazil): evidence of transference between environments

This study assessed the concentrations and sources of natural and anthropogenic aliphatic (AHs) and polycyclic aromatic hydrocarbons (PAHs) in superficial sediments collected along the Patos Lagoon estuary and in sediment cores obtained from the Cassino Beach mud bank. Levels and distribution of n-alkanes indicate terrestrial sources, overlapping with a low amount of petrogenic hydrocarbons (heavy oils). Unresolved complex mixture (UCM) was observed in all samples. On the other hand, the distribution of PAHs in the sediments showed a predominance of pyrolytic over petrogenic sources. In general, hydrocarbons (HCs) contamination in the Patos Lagoon estuary and its adjacent coastal area can be considered low, except for sites near urban or industrial effluents, where moderate to high levels of contamination were found. Concentrations of hydrocarbons were homogeneous throughout the sediment cores, suggesting that mixing processes may have occurred along the layers or that HCs inputs to the mud banks were uniform during the studied deposition period. In addition, the levels and profile of HCs in the coastal sediments were similar to those observed in the estuary. Moreover, the frequent remobilization of sediments from the mud bank towards Cassino beach does not seem to pose any threats to the local biota or beach users since the levels of contamination were relatively low and below the threshold limits of sediment quality guidelines.

In vitro and in silico assessment of endocrine disrupting effects of food contaminants through pregnane X receptor

As a promiscuous xenobiotic receptor, pregnane X receptor (PXR) has been confirmed to participate in numerous physiological process. In addition to the conventional estrogen/androgen receptor, PXR also serves as an alternative target for environmental chemical contaminants. In this work, the PXR-mediated endocrine disrupting effects of typical food contaminants were explored. Firstly, the time-resolved fluorescence resonance energy transfer assays confirmed the PXR binding affinities of 2,2',4,4',5,5'-hexachlorobiphenyl, bis(2-ethylhexyl) phthalate, dibutyl phthalate, chlorpyrifos, bisphenol A, and zearalenone, with IC50 values ranging from 1.88 to 4284.00 nM. Then their PXR agonist activities were assessed by PXR-mediated CYP3A4 reporter gene assays. Subsequently, the regulation of gene expressions of PXR and its targets CYP3A4, UGT1A1, and MDR1 by these compounds was further investigated. Intriguingly, all the tested compounds interfered with these gene expressions, confirming their endocrine disrupting effects via PXR-mediated signaling. The compound-PXR-LBD binding interactions were explored by molecular docking and molecular dynamics simulations to unravel the structural basis of their PXR binding capacities. The weak intermolecular interactions are key players in stabilizing these compound-PXR-LBD complexes. During the simulation process, 2,2',4,4',5,5'-hexachlorobiphenyl remained stable while the other 5 compounds underwent relatively severe disturbances. In conclusion, these food contaminants might exhibit endocrine disrupting effects via PXR.

Impacts of Environmental Pollution on Brain Tumorigenesis

Pollutants consist of several components, known as direct or indirect mutagens, that can be associated with the risk of tumorigenesis. The increased incidence of brain tumors, observed more frequently in industrialized countries, has generated a deeper interest in examining different pollutants that could be found in food, air, or water supply. These compounds, due to their chemical nature, alter the activity of biological molecules naturally found in the body. The bioaccumulation leads to harmful effects for humans, increasing the risk of the onset of several pathologies, including cancer. Environmental components often combine with other risk factors, such as the individual genetic component, which increases the chance of developing cancer. The objective of this review is to discuss the impact of environmental carcinogens on modulating the risk of brain tumorigenesis, focusing our attention on certain categories of pollutants and their sources.

Coupled System Approach to Healthy Earth Environments and Individual Human Resilience

The SARS-CoV-2 pandemic has stressed our social organizations, health care systems and economies at a level not experienced since WWII or the last “Spanish flu” pandemic of 1918. This shock provides a real-life test of the resilience of human societies and of individuals, challenging our understanding and level of preparation. While hurried coercive non-pharmaceutical measures and vaccinations were the main responses, for the future, we propose a coupled double-system approach linking efforts to improve both human well-being and Earth environmental health. Concretely, this means linking (i) the build-up of individual health resilience using holistic medical system perspectives applied to each person with (ii) efforts to depollute and achieve more healthy Earth environments that are intrinsic pillars of humans’ health and wealth. The push to fight Earth ecological damages towards environmental sustainability should be rethought as being motivated by recovering an ecosystem in which each own personal biological ecosystem (i.e., each person's homeostatic balance) can strive again. We propose to prioritize Human-Environment-Health initiatives for depolluting the environment and of our immune systems, as well as improving individual responsibility and resilience.

Hybrid Composite of Sn(IV)-Porphyrin and Mesoporous Structure for Enhanced Visible Light Photocatalytic Degradation of Organic Dyes

Two hybrid composites (SnP@MCM-41 and SnP@SiO₂) were fabricated by chemical adsorption of (trans-dihydroxo)(5,10,15,20-tetraphenylporphyrinato)tin(IV) (SnP) on mesoporous structured Mobil Composition of Matter No. 41 (MCM-41) and SiO₂ nanoparticles. These materials were characterized by Fourier-transform infrared spectroscopy, ultraviolet-visible spectroscopy, fluorescence spectroscopy, transmission electron microscopy, and field-emission scanning electron microscopy techniques. The incorporation of SnP into MCM-41 and SiO₂ supports efficient photocatalytic degradation of the anionic erioglaucine, cationic rhodamine B, and neutral m-cresol purple dyes under visible light irradiation in an aqueous solution. The performances of degradation of these dyes by these photocatalysts under visible light irradiation varied from 87 to 95%. The pseudo-first-order degradation rate constant of organic dyes for SnP@MCM-41 was higher than those of SnP@SiO₂ and SnP. These visible light photocatalysts showed remarkable stability and reliable reusability.

Transcription factor-based biosensors for screening and dynamic regulation

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

Plant Growth Promotion and Biocontrol of Leaf Blight Caused by Nigrospora sphaerica on Passion Fruit by Endophytic Bacillus subtilis Strain GUCC4

Passion fruit (Passiflora edulis Sims) is widely cultivated in tropic and sub-tropic regions for the production of fruit, flowers, cosmetics, and for pharmacological applications. Its high economic, nutritional, and medical values elicit the market demand, and the growing areas are rapidly increasing. Leaf blight caused by Nigrospora sphaerica is a new and emerging disease of passion fruit in Guizhou, in southwest China, where the unique karst mountainous landscape and climate conditions are considered potential areas of expansion for passion fruit production. Bacillus species are the most common biocontrol and plant-growth-promotion bacteria (PGPB) resources in agricultural systems. However, little is known about the endophytic existence of Bacillus spp. in the passion fruit phyllosphere as well as their potential as biocontrol agents and PGPB. In this study, 44 endophytic strains were isolated from 15 healthy passion fruit leaves, obtained from Guangxi province, China. Through purification and molecular identification, 42 of the isolates were ascribed to Bacillus species. Their inhibitory activity against N. sphaerica was tested in vitro. Eleven endophytic Bacillus spp. strains inhibited the pathogen by >65%. All of them produced biocontrol- and plant-growth-promotion-related metabolites, including indole-3-acetic acid (IAA), protease, cellulase, phosphatase, and solubilized phosphate. Furthermore, the plant growth promotion traits of the above 11 endophytic Bacillus strains were tested on passion fruit seedlings. One isolate, coded B. subtilis GUCC4, significantly increased passion fruit stem diameter, plant height, leaf length, leaf surface, fresh weight, and dry weight. In addition, B. subtilis GUCC4 reduced the proline content, which indicated its potential to positively regulate passion fruit biochemical properties and resulted in plant growth promotion effects. Finally, the biocontrol efficiencies of B. subtilis GUCC4 against N. sphaerica were determined in vivo under greenhouse conditions. Similarly to the fungicide mancozeb and to a commercial B. subtilis-based biofungicide, B. subtilis GUCC4 significantly reduced disease severity. These results suggest that B. subtilis GUCC4 has great potential as a biological control agent and as PGPB on passion fruit.

A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

Detection and Degradation Studies of Nile Blue Sulphate Using Electrochemical and UV-Vis Spectroscopic Techniques

An efficient and reliable electrochemical sensing platform based on COOH-fMWCNTs modified GCE (COOH-fMWCNTs/GCE) was designed for the detection of nanomolar concentration of Nile Blue Sulphate (NBS). In comparison to the bare GCE, the electrochemical sensing scaffold considerably enhanced the peak current response of NBS dye as confirmed from the results of voltammetric investigations. The electrochemical approach of detecting NBS in the droplet of its solution dried over the surface of modified electrode validated, the role of modifier in enhancing the sensing response. Under optimized conditions, the designed electrochemical platform demonstrated a wide linearity range (0.03–10 μM) for NBS, with LOD of 1.21 nM. Moreover, COOH-fMWCNTs/GCE was found reproducible and stable as confirmed by repeatability and inter-day durability tests. The selectivity of the designed sensing matrix was ensured by anti-interference tests. The photocatalytic degradation of NBS dye was carried out by using TiO2 nanoparticles as photocatalyst in the presence of H2O2. UV-visible spectroscopic studies revealed 95% photocatalytic degradation of NBS following a pseudo-first-order kinetics with a rate constant of 0.028 min−1. These findings were supported electrochemically by monitoring the photocatalytically degraded dye at the designed sensing platform. The color variation and final decolorization of the selected dye in water served as a visual indicator of the degradation process. To conclude, the designed sensing platform immobilized with COOH-fMWCNTs imparted improved selectivity and sensitivity to detect and to, monitor the photocatalytic degradation of NBS.

Digital tools for brownfield redevelopment: Stakeholder perspectives and opportunities

Brownfield redevelopment is a complex process often involving a wide range of stakeholders holding differing priorities and opinions. The use of digital systems and products for decision making, modelling, and supporting discussion has been recognised throughout literature and industry. The inclusion of stakeholder preferences is an important consideration in the design and development of impactful digital tools and decision support systems. In this study, we present findings from stakeholder consultation with professionals from the UK brownfield sector with the aim of informing the design of future digital tools and systems. Our research investigates two broad themes; digitalisation and the use of digital tools across the sector; and perceptions of key brownfield challenge areas where digital tools could help better inform decision-makers. The methodology employed for this study comprises the collection of data and information using a combination of interviews and an online questionnaire. The results from these methods were evaluated both qualitatively and quantitatively. Findings reveal a disparity in levels of digital capability between stakeholder groups including between technical stakeholder types, and that cross-discipline communication of important issues may be aided by the development of carefully designed digital tools. To this end, we present seven core principles to guide the design and implementation of future digital tools for the brownfield sector. These principles are that future digital tools should be: (1) Stakeholder driven, (2) Problem centred, (3) Visual, (4) Intuitive, (5) Interactive, (6) Interoperable, and (7) Geospatial data driven.

Prioritization of mixtures of neurotoxic chemicals for biomonitoring using high-throughput toxicokinetics and mixture toxicity modeling

Modern society continues to pollute the environment with larger quantities of chemicals that have also become more structurally and functionally diverse. Risk assessment of chemicals can hardly keep up with the sheer numbers that lead to complex mixtures of increasing chemical diversity including new chemicals, substitution products on top of still abundant legacy compounds. Fortunately, over the last years computational tools have helped us to identify and prioritize chemicals of concern. These include toxicokinetic models to predict exposure to chemicals as well as new approach methodologies such as in-vitro bioassays to address toxicodynamic effects. Combined, they allow for a prediction of mixtures and their respective effects and help overcome the lack of data we face for many chemicals. In this study we propose a high-throughput approach using experimental and predicted exposure, toxicokinetic and toxicodynamic data to simulate mixtures, to which a virtual population is exposed to and predict their mixture effects. The general workflow is adaptable for any type of toxicity, but we demonstrated its applicability with a case study on neurotoxicity. If no experimental data for neurotoxicity were available, we used baseline toxicity predictions as a surrogate. Baseline toxicity is the minimal toxicity any chemical has and might underestimate the true contribution to the mixture effect but many neurotoxicants are not by orders of magnitude more potent than baseline toxicity. Therefore, including baseline-toxic effects in mixture simulations yields a more realistic picture than excluding them in mixture simulations. This workflow did not only correctly identify and prioritize known chemicals of concern like benzothiazoles, organochlorine pesticides and plasticizers but we were also able to identify new potential neurotoxicants that we recommend to include in future biomonitoring studies and if found in humans, to also include in neurotoxicity screening.

Health risks of solid waste management practices in rural Ghana: A semi-quantitative approach toward a solid waste safety plan

Inadequate solid waste management (SWM) can lead to environmental contamination and human health risks. The health risks from poor SWM can vary based on specific practices and exposure pathways. Thus, it is necessary to adequately understand the local context. This information, however, is rarely available in low-resource settings, particularly in rural areas. A solid waste safety plan could be helpful in these settings for gathering necessary data to assess and minimize health risks. As a step in developing such a tool, a semi-quantitative health risk analysis of SWM practices in nine Ghanaian rural villages was undertaken. Data on SWM in each village were collected through qualitative field observations and semi-structured interviews with local stakeholders. SWM-related health risks were assessed using the collected data, similar case studies in the scientific literature and dialogue among an assembled team of experts. The analysis identified context-specific practices and exposure pathways that may present the most substantial health risks as well as targeted solutions for mitigation risks. A risk assessment matrix was developed to quantify SWM risks as low, medium, high, or very high based on the likelihood and severity of identified hazards. The highest SWM risks were identified from dumpsites and uncontrolled burying of solid waste. More specifically, a very high or high risk of infectious and vector-borne diseases from SWM in the villages was identified, both in the disposal of solid waste in dumpsites and uncontrolled burying of solid waste. Additionally, a very high or high risk of inhalation, ingestion or dermal contact with contaminants was found in the disposal of solid waste in dumpsites, open burning of waste and reuse of waste from dumpsites as compost. The results demonstrate the potential value of a solid waste safety plan and a parsimonious approach to collect key local data to inform its contents.

A multiplex inhalation platform to model in situ like aerosol delivery in a breathing lung-on-chip

Prolonged exposure to environmental respirable toxicants can lead to the development and worsening of severe respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD) and fibrosis. The limited number of FDA-approved inhaled drugs for these serious lung conditions has led to a shift from in vivo towards the use of alternative in vitro human-relevant models to better predict the toxicity of inhaled particles in preclinical research. While there are several inhalation exposure models for the upper airways, the fragile and dynamic nature of the alveolar microenvironment has limited the development of reproducible exposure models for the distal lung. Here, we present a mechanistic approach using a new generation of exposure systems, the Cloud α AX12. This novel in vitro inhalation tool consists of a cloud-based exposure chamber (VITROCELL) that integrates the breathing ^AXLung-on-chip system (AlveoliX). The ultrathin and porous membrane of the AX12 plate was used to create a complex multicellular model that enables key physiological culture conditions: the air-liquid interface (ALI) and the three-dimensional cyclic stretch (CS). Human-relevant cellular models were established for a) the distal alveolar-capillary interface using primary cell-derived immortalized alveolar epithelial cells (^AXiAECs), macrophages (THP-1) and endothelial (HLMVEC) cells, and b) the upper-airways using Calu3 cells. Primary human alveolar epithelial cells (^AXhAEpCs) were used to validate the toxicity results obtained from the immortalized cell lines. To mimic in vivo relevant aerosol exposures with the Cloud α AX12, three different models were established using: a) titanium dioxide (TiO2) and zinc oxide nanoparticles b) polyhexamethylene guanidine a toxic chemical and c) an anti-inflammatory inhaled corticosteroid, fluticasone propionate (FL). Our results suggest an important synergistic effect on the air-blood barrier sensitivity, cytotoxicity and inflammation, when air-liquid interface and cyclic stretch culture conditions are combined. To the best of our knowledge, this is the first time that an in vitro inhalation exposure system for the distal lung has been described with a breathing lung-on-chip technology. The Cloud α AX12 model thus represents a state-of-the-art pre-clinical tool to study inhalation toxicity risks, drug safety and efficacy.

Dynamics of microbial communities during biotransformation of nitrofurantoin

The purpose of this research was to investigate the biodegradation of nitrofurantoin (NFT), a typical nitrofuran antibiotic of potential carcinogenic properties, by two microbial communities derived from distinct environmental niches - mountain stream (NW) and seaport water (SS). The collected environmental samples represent the reserve of the protected area with no human intervention and the contaminated area that concentrates intense human activities. The structure, composition, and diversity of the communities were analyzed at three timepoints during NFT biodegradation. Comamonadaceae (43.2%) and Pseudomonadaceae (19.6%) were the most abundant families in the initial NW sample. The top families in the initial SS sample included Aeromonadaceae (31.4%) and Vibrionaceae (25.3%). The proportion of the most abundant families in both consortia was remarkably reduced in all samples treated with NFT. The biodiversity significantly increased in both consortia treated with NFT suggesting that NFT significantly alters community structure in the aquatic systems. In this study, NFT removal efficiency and transformation products were also studied. The biodegradation rate decreased with the increasing initial NFT concentration. Biodegradation followed similar pathways for both consortia and led to the formation of transformation products: 1-aminohydantoin, semicarbazide (SEM), and hydrazine (HYD). SEM and HYD were detected for the first time as NFT biotransformation products. This study demonstrates that the structure of the microbial community may be directly correlated with the presence of NFT. Enchanced biodiversity of the microbial community does not have to be correlated with increase in functional capacity, such as the ability to biodegradation because higher biodiversity corresponded to lower biodegradation. Our findings provide new insights into the effect of NFT contamination on aquatic microbiomes. The study also increases our understanding of the environmental impact of nitrofuran residues and their biodegradation.