Nitrosamines, as ubiquitous environmental carcinogens with adverse impact on human health, were crucial inducers of esophageal cancer (EC). Esophageal inflammation (EI) was an important biological process and considered to be associated with the progression of EC. However, the underlying regulatory mechanism of EI process caused by nitrosamines exposure remained largely unclear. In this study, a metabolomics approach based on mass spectrometry was utilized to explore the effect of nitrosamines exposure to ICR mice. Also, the changes of pivotal metabolic enzyme levels, urinary nitrosamines and histopathological analysis were evaluated. The results showed that nitrosamines exposure was intimately interrelated with EI process in mice. Metabolomics profiling analysis indicated that nitrosamines caused significant alterations of metabolic pathway predominantly enriched in fatty acid metabolism. Targeted metabolomics analysis revealed that nitrosamines promoted decomposition of fatty acids and facilitated fatty acid β-oxidation (FAO) of mice. The significant increase of carnitine palmitoyltransferase 1 (CPT1) and downregulation of acetyl-CoA acyltransferase 2 (ACAA2) would promote FAO in EI process induced by nitrosamines. Additionally, the exposure levels of more than half of nitrosamines in urine were correlated with inflammatory fatty acid biomarkers. Overall, this study found that EI triggered by nitrosamines may be associated with the promotion of FAO, and provided novel insights for evaluating the underlying mechanism of environmental pollutant-caused toxicity based on metabolomics.

Most amyotrophic lateral sclerosis (ALS) cases are sporadic (∼90%) and environmental exposures are implicated in their etiology. Large industrial facilities are permitted the airborne release of certain chemicals with hazardous properties and report the amounts to the US Environmental Protection Agency (EPA) as part of its Toxics Release Inventory (TRI) monitoring program. The objective of this project was to identify industrial chemicals released into the air that may be associated with ALS etiology. We geospatially estimated residential exposure to contaminants using a de-identified medical claims database, the SYMPHONY Integrated Dataverse®, with ∼26,000 nationally distributed ALS patients, and non-ALS controls matched for age and gender. We mapped TRI data on industrial releases of 523 airborne contaminants to estimate local residential exposure and used a dynamic categorization algorithm to solve the problem of zero-inflation in the dataset. In an independent validation study, we used residential histories to estimate exposure in each year prior to diagnosis. Air releases with positive associations in both the SYMPHONY analysis and the spatio-temporal validation study included styrene (false discovery rate (FDR) 5.4e-5), chromium (FDR 2.4e-4), nickel (FDR 1.6e-3), and dichloromethane (FDR 4.8e-4). Using a large de-identified healthcare claims dataset, we identified geospatial environmental contaminants associated with ALS. The analytic pipeline used may be applied to other diseases and identify novel targets for exposure mitigation. Our results support the future evaluation of these environmental chemicals as potential etiologic contributors to sporadic ALS risk.

To date, carbapenem-resistant Enterobacteriaceae have been found predominantly in clinical settings worldwide. Raoultella belongs to the Enterobacteriaceae family which can cause hospital-acquired infections, and carbapenem-resistant Raoultella spp. (CRR) is sporadically reported in the environment. We investigated the distribution and underlying resistance mechanisms of CRR in a wastewater treatment plant (WWTP) from eastern China between January 2018 and February 2019. A total of 17 CRR were isolated from 324 environmental samples, including Raoultella ornithinolytica (n = 15) and Raoultella planticola (n = 2). The detection of CRR was more frequent in the water inlet compared to anaerobic tank, aerobic tank, sludge thickener, activated sludge, mud cake storage area, and water outlet, and CRR was detected in mud cake stacking area. All CRR were resistant to imipenem, meropenem, ampicillin, piperacillin-tazobactam, cefotaxime, ceftazidime, trimethoprim-sulfamethoxazole and fosfomycin. Four different carbapenemase genes were identified, including blaKPC₋₂ (n = 13), blaNDM₋₁ (n = 8), blaNDM₋₅ (n = 1), blaIMP₋₄ (n = 1). Interestingly, isolated R. ornithinolytica from the WWTP were closely related to those reported from human samples in China. Plasmid analysis indicated that IncFII(Yp), IncP6, and IncU mediated blaKPC₋₂ spread, IncX3 and IncN2 mediated blaNDM spread in the environment. The core structure of the Tn3-ISKpn27-blaKPC₋₂-ISKpn6, ISAba125-blaNDM-bleMBL-trpF-dsbD were identified. The study provides evidence that Raoultella spp. may spread alarming carbapenem resistance in the environment and, therefore, the continuous surveillance for carbapenem resistance in the WWTP should be conducted, especially sludge.

Several studies have reported an association between residential surrounding particulate matter with an aerodynamic diameter ≤2.5 μm (PM₂.₅) and coronary heart disease (CHD). However, the underlying biological mechanism remains unclear. To fill this research gap, this study enrolled a residentially stable sample of 942 patients with CHD and 1723 controls. PM₂.₅ concentration was obtained from satellite-based annual global PM₂.₅ estimates for the period 1998–2019. MicroRNA microarray and pathway analysis of target genes was performed to elucidate the potential biological mechanism by which PM₂.₅ increases CHD risk. The results showed that individuals exposed to high PM₂.₅ concentrations had higher risks of CHD than those exposed to low PM₂.₅ concentrations (odds ratio = 1.22, 95% confidence interval: 1.00, 1.47 per 10 μg/m³ increase in PM₂.₅). Systolic blood pressure mediated 6.6% of the association between PM₂.₅ and CHD. PM₂.₅ and miR-4726-5p had an interaction effect on CHD development. Bioinformatic analysis demonstrated that miR-4726-5p may affect the occurrence of CHD by regulating the function of RhoA. Therefore, individuals in areas with high PM₂.₅ exposure and relative miR-4726-5p expression have a higher risk of CHD than their counterparts because of the interaction effect of PM₂.₅ and miR-4726-5p on blood pressure.

Microplastic (MP) contamination is ubiquitous in agricultural soils. As a cost-effective soil amendment, biochar (BC) often coincides with MP exposure. However, little research has been conducted regarding the independent and combined effects of MPs and BC on the soil microbiome and N₂O/CH₄ emissions. Therefore, in this study, polyethylene terephthalate (PET) and wheat straw-derived BC were used, respectively, as representative MP and BC during an entire rice growth period. The high-throughput sequencing results showed that PET alone lowered bacterial diversity by 26.7%, while PET and BC co-existence did not induce apparent change. The relative abundances of some microbes (e.g., Cyanobacteria, Verrucomicrobia, and Bacteroidetes) that are associated with C and N cycling were changed at the phylum and class levels by all the treatments. In comparison with the control, the treatment of BC, PET, and their co-existence reduced the cumulative CH₄ emissions by 50%, 53%, and 61%, respectively. The higher mitigation by BC + PET may be the result of higher soil Eh and a consequently lower methanogenesis functional gene mcrA abundance in the treated soils. In addition, BC and PET alone, as well as their combined treatment, increased the abundance of nitrification genes, enhancing the soil nitrification process. However, the relative contribution of the nitrification process to N₂O emission was possibly lower than that of denitrification, in which the N₂O reductase gene nosZ was found to be the primary gene regulating N₂O emissions. BC alone increased nosZ abundance by 42.3%, thereby showing the potential in suppressing N₂O emission. In contrast, when BC was co-added with PET, the nosZ abundance lowered possibly because of increased soil aeration, and thus its cumulative N₂O emission was 38% higher than the BC treatment. Overall, these results demonstrated that BC and PET function differently in soil ecosystems when they coexisted.

Facing the challenge of global microplastics (MPs) pollution, full characterization of MPs biohazards is urgent. Recent intensive studies revealed that the toxicity depends on the material, size, and exposure concentration of MP. To better elucidate MPs biohazards, we investigated the impact of polystyrene-MPs of size 0.1 μm at a low dose of 50 μg/L on the neuromuscular, retinal, and reproductive phenotypes of fruit fly model, by voltage-clamped electrophysiology, electroretinogram, and reproductive assay, respectively. We found that MPs decreased the frequency of spontaneous junction currents of synapse and altered the receptor potential amplitude of the retina. Furthermore, MPs lowered the rate of embryo-laying of fruit flies. The differential gene expression of ligand-receptor interaction, endocytosis, phototransduction, and Toll/Imd signaling pathways might underlie these MPs-induced phenotypes. These findings call for further investigation on the potential biohazards of low-dose MPs.

The composition of root exudates is modulated by several environmental factors, and it remains unclear how that affects beneficial rhizosphere or inoculated microorganisms under heavy metal (HM) contamination. Therefore, we evaluated the transcriptional response of Pseudomonas putida E36 (a Miscanthus x giganteus isolate with plant growth promotion-related properties) to Cd, Pb and Zn in an in vitro study implementing root exudates from M. x giganteus. To collect root exudates and analyse their composition plants were grown in a pot experiment under HM and control conditions. Our results indicated higher exudation rate for plants challenged with HM. Further, out of 29 organic acids identified and quantified in the root exudates, 8 of them were significantly influenced by HM (e.g., salicylic and terephthalic acid). The transcriptional response of P. putida E36 was significantly affected by the HM addition to the growth medium, increasing the expression of several efflux pumps and stress response-related functional units. The additional supplementation of the growth medium with root exudates from HM-challenged plants resulted in a downregulation of 29% of the functional units upregulated in P. putida E36 as a result of HM addition to the growth medium. Surprisingly, root exudates + HM downregulated the expression of P. putida E36 functional units related to plant colonization (e.g., chemotaxis, motility, biofilm formation) but upregulated its antibiotic and biocide resistance compared to the control treatment without HM. Our findings suggest that HM-induced changes in root exudation pattern may attract beneficial bacteria that are in turn awarded with organic nutrients, helping them cope with HM stress. However, it might affect the ability of these bacteria to colonize plants growing in HM polluted areas. Those findings may offer an insight for future in vivo studies contributing to improvements in phytoremediation measures.

Poor air quality is becoming a critical environmental concern in different countries over the last several years. Most of the air pollutants have serious consequences on human health and wellbeing. In this context, efficient forecasting of air pollutants is currently crucial to predict future events with a view to taking corrective actions and framing effective environmental policies. Although deep learning (DL) as well as statistical forecasting models are investigated in the literature, they have rarely used in air pollutant-specific optimal model building for long-term forecasting. In this paper, our aim is to develop the pollutant-specific optimal forecasting models for the phases spanning from preprocessing to model building by investigating a set of predictive techniques. In this regard, this paper presents a methodology for long-term forecasting of some important air pollutants. More specifically, a total of eight best performing models such as stacked LSTM, LSTM auto-encoder, Bi-LSTM, convLSTM, Holt-Winters, auto-regressive (AR), SARIMA, and Prophet are investigated for developing pollutant-specific optimal forecasting models. The study is carried out based on the real-world data obtained from government-run air quality monitoring units in Kolkata over a period of 4 years. The models such as Holt-Winters, Bi-LSTM, and ConvLSTM achieve high forecasting accuracy with respect to MAE and RMSE values for majority of the pollutants.

Plant-based products such as essential oils and other extracts have been used for centuries due to their beneficial properties. Currently, their use is widely disseminated through a variety of industries and new applications are continuously emerging. For these reasons, they are produced industrially in large quantities and consequently they have the potential to reach the environment. However, the potential effects that these products have on the ecosystems’ health are mostly unknown. In recent years, the scientific community started to focus on the possible toxic effects of essential oils and plant extracts towards non-target organisms. As a result, an increasing body of knowledge has emerged. This review describes the current state of the art on the toxic effects that essential oils and plant extracts have towards organisms from different trophic levels, including producers, primary consumers, and secondary consumers. The majority of the studies (76.5%) focuses on the aquatic environment, particularly in aquatic invertebrates (45.1%) with only 23.5% of the studies focusing on the potential toxicity of plant-derived products on terrestrial ecosystems.While some essential oils and extracts have been described to have no toxic effects to the selected organisms or the toxic effects were only observable at high concentrations, others were reported to be toxic at concentrations below the limit set by international regulations, some of them at very low concentrations. In fact, L(E)C₅₀ values as low as 0.0336 mg.L⁻¹, 0.0005 mg.L⁻¹ and 0.0053 mg.L⁻¹ were described for microalgae, crustaceans and fish, respectively. Generally, essential oils exhibit higher toxicity than extracts. However, when the extracts are obtained from plants that are known to produce toxic metabolites, the extracts can be more toxic than essential oils.Overall, and despite being generally considered “eco-friendly” products and safer than they synthetic counterparts, some essential oils and plant extracts are toxic towards non-target organisms. Given the increasing interest from industry on these plant-based products further research using international standardized protocols is mandatory.