Arsenic methylation and microbial communities in paddy soils under alternating anoxic and oxic conditions.

Arsenic (As) methylation in soils affects the environmental behavior of As, excessive accumulation of dimethylarsenate (DMA) in rice plants leads to straighthead disease and a serious drop in crop yield. Understanding the mobility and transformation of methylated arsenic in redox-changing paddy fields is crucial for food security. Here, soils including un-arsenic contaminated (N-As), low-arsenic (L-As), medium-arsenic (M-As), and high-arsenic (H-As) soils were incubated under continuous anoxic, continuous oxic, and consecutive anoxic/oxic treatments respectively, to profile arsenic methylating process and microbial species involved in the As cycle. Under anoxic-oxic (A-O) treatment, methylated arsenic was significantly increased once oxygen was introduced into the incubation system. The methylated arsenic concentrations were up to 2-24 times higher than those in anoxic (A), oxic (O), and oxic-anoxic (O-A) treatments, under which arsenic was methylated slightly and then decreased in all four As concentration soils. In fact, the most plentiful arsenite S-adenosylmethionine methyltransferase genes (arsM) contributed to the increase in As methylation. Proteobacteria (40.8%-62.4%), Firmicutes (3.5%-15.7%), and Desulfobacterota (5.3%-13.3%) were the major microorganisms related to this process. These microbial increased markedly and played more important roles after oxygen was introduced, indicating that they were potential keystone microbial groups for As methylation in the alternating anoxic (flooding) and oxic (drainage) environment. The novel findings provided new insights into the reoxidation-driven arsenic methylation processes and the model could be used for further risk estimation in periodically flooded paddy fields.

Morphologically controlled synthesis of MgFe-LDH using MgO and succinic acid for enhanced arsenic adsorption: Kinetics, equilibrium, and mechanism studies.

In this study, we investigated improving the performance of a layered double hydroxide (LDH) for the adsorption of As(III) and As(V) by controlling the morphology of LDH crystals. The LDH was synthesized via a simple coprecipitation method using barely soluble MgO as a precursor and succinic acid (SA) as a morphological control agent. Doping the LDH crystals with carboxylate ions (RCOO-) derived from SA caused the crystals to develop in a radial direction. This changed the pore characteristics and increased the density of active surface sites. Subsequently, SA/MgFe-LDH showed excellent affinity for As(III) and As(V) with maximum sorption densities of 2.42 and 1.60 mmol/g, respectively. By comparison, the pristine MgFe-LDH had sorption capacities of 1.56 and 1.31 mmol/g for As(III) and As(V), respectively. The LDH was effective over a wide pH range for As(III) adsorption (pH 3-8.5) and As(V) adsorption (pH 3-6.5). Using a combination of spectroscopy and sorption modeling calculations, the main sorption mechanism of As(III) and As(V) on SA/MgFe-LDH was identified as inner-sphere complexation via ligand exchange with hydroxyl group (-OH) and RCOO-. Specifically, bidentate As-Fe complexes were proposed for both As(III) and As(V) uptake, with the magnitude of formation varying with the initial As concentration. Importantly, the As-laden adsorbent had satisfactory stability in simulated real landfill leachate. These findings demonstrate that SA/MgFe-LDH exhibits considerable potential for remediation of As-contaminated water.

Release characteristics of arsenic from sediments and its source or sink competition with phosphorus: A case of a great lake with grass-algae alternation.

The arsenic (As) release from sediments in great lakes is affected by various factors. In this study, the characteristics of As release from sediments was investigated, and the As sources and sinks with the strengths in sediments from different areas (grass-type, algae-type, and grass-algae alternation areas) in great shallow lakes (Taihu Lake, China) were analyzed, and the influence of P competition in the process of As release was also studied. The results showed that changing trend of the values of equilibrium As concentration in sediments were consistent with the regional changes (0 to 28.12 µg/L), and the sediments from algae-type areas had the higher values. The sediments from western lake and northwest lake bay were a strong As and a weak P source, and the north lake bay had the opposite trend of these two regions. Intense P source competition with As from the sediments occurred in algae-type areas. The grass-type areas had strong As and P retention capacities, indicating a sink role of sediment with high As and P sorption capacities. The degree of As and P saturation had similar trend in sediments, and the grass-type areas had the higher values, 18.3%-21.4% and 15.31%-20.34%, respectively. Contribution analysis results showed that most of As release contribution was from the bottom (30-50 cm) sediments, and the surface (0-10 cm) sediments from algae-type areas contributed more to the overlying water than other region.

Predicting the efficiency of arsenic immobilization in soils by biochar using machine learning.

Arsenic (As) pollution in soils is a pervasive environmental issue. Biochar immobilization offers a promising solution for addressing soil As contamination. The efficiency of biochar in immobilizing As in soils primarily hinges on the characteristics of both the soil and the biochar. However, the influence of a specific property on As immobilization varies among different studies, and the development and application of arsenic passivation materials based on biochar often rely on empirical knowledge. To enhance immobilization efficiency and reduce labor and time costs, a machine learning (ML) model was employed to predict As immobilization efficiency before biochar application. In this study, we collected a dataset comprising 182 data points on As immobilization efficiency from 17 publications to construct three ML models. The results demonstrated that the random forest (RF) model outperformed gradient boost regression tree and support vector regression models in predictive performance. Relative importance analysis and partial dependence plots based on the RF model were conducted to identify the most crucial factors influencing As immobilization. These findings highlighted the significant roles of biochar application time and biochar pH in As immobilization efficiency in soils. Furthermore, the study revealed that Fe-modified biochar exhibited a substantial improvement in As immobilization. These insights can facilitate targeted biochar property design and optimization of biochar application conditions to enhance As immobilization efficiency.

Development of a coupled model to simulate and assess arsenic contamination and impact factors in the Jinsha River Basin, China.

With the increasing severity of arsenic (As) pollution, quantifying the environmental behavior of pollutant based on numerical model has become an important approach to determine the potential impacts and finalize the precise control strategies. Taking the industrial-intensive Jinsha River Basin as typical area, a two-dimensional hydrodynamic water quality model coupled with Soil and Water Assessment Tool (SWAT) model was developed to accurately simulate the watershed-scale distribution and transport of As in the terrestrial and aquatic environment at high spatial and temporal resolution. The effects of hydro-climate change, hydropower station construction and non-point source emissions on As were quantified based on the coupled model. The result indicated that higher As concentration areas mainly centralized in urban districts and concentration slowly decreased from upstream to downstream. Due to the enhanced rainfall, the As concentration was significantly higher during the rainy season than the dry season. Hydro-climate change and the construction of hydropower station not only affected the dissolved As concentration, but also affected the adsorption and desorption of As in sediment. Furthermore, As concentration increased with the input of non-point source pollution, with the maximum increase about 30%, resulting that non-point sources contributed important pollutant impacts to waterways. The coupled model used in pollutant behavior analysis is general with high potential application to predict and mitigate water pollution.

Assessment of internal exposure risk from metals pollution of occupational and non-occupational populations around a non-ferrous metal smelting plant.

Non-ferrous metal smelting poses significant risks to public health. Specifically, the copper smelting process releases arsenic, a semi-volatile metalloid, which poses an emerging exposure risk to both workers and nearby residents. To comprehensively understand the internal exposure risks of metal(loid)s from copper smelting, we explored eighteen metal(loid)s and arsenic metabolites in the urine of both occupational and non-occupational populations using inductively coupled plasma mass spectrometry with high-performance liquid chromatography and compared their health risks. Results showed that zinc and copper (485.38 and 14.00 µg/L), and arsenic, lead, cadmium, vanadium, tin and antimony (46.80, 6.82, 2.17, 0.40, 0.44 and 0.23 µg/L, respectively) in workers (n=179) were significantly higher compared to controls (n=168), while Zinc, tin and antimony (412.10, 0.51 and 0.15 µg/L, respectively) of residents were significantly higher than controls. Additionally, workers had a higher monomethyl arsenic percentage (MMA%), showing lower arsenic methylation capacity. Source appointment analysis identified arsenic, lead, cadmium, antimony, tin and thallium as co-exposure metal(loid)s from copper smelting, positively relating to the age of workers. The hazard index (HI) of workers exceeded 1.0, while residents and control were approximately at 1.0. Besides, all three populations had accumulated cancer risks exceeding 1.0 × 10-4, and arsenite (AsIII) was the main contributor to the variation of workers and residents. Furthermore, residents living closer to the smelting plant had higher health risks. This study reveals arsenic exposure metabolites and multiple metals as emerging contaminants for copper smelting exposure populations, providing valuable insights for pollution control in non-ferrous metal smelting.

Pristine/magnesium-loaded biochar and ZVI affect rice grain arsenic speciation and cadmium accumulation through different pathways in an alkaline paddy soil.

Cadmium (Cd) and arsenic (As) co-contamination has threatened rice production and food safety. It is challenging to mitigate Cd and As contamination in rice simultaneously due to their opposite geochemical behaviors. Mg-loaded biochar with outstanding adsorption capacity for As and Cd was used for the first time to remediate Cd/As contaminated paddy soils. In addition, the effect of zero-valent iron (ZVI) on grain As speciation accumulation in alkaline paddy soils was first investigated. The effect of rice straw biochar (SC), magnesium-loaded rice straw biochar (Mg/SC), and ZVI on concentrations of Cd and As speciation in soil porewater and their accumulation in rice tissues was investigated in a pot experiment. Addition of SC, Mg/SC and ZVI to soil reduced Cd concentrations in rice grain by 46.1%, 90.3% and 100%, and inorganic As (iAs) by 35.4%, 33.1% and 29.1%, respectively, and reduced Cd concentrations in porewater by 74.3%, 96.5% and 96.2%, respectively. Reductions of 51.6% and 87.7% in porewater iAs concentrations were observed with Mg/SC and ZVI amendments, but not with SC. Dimethylarsinic acid (DMA) concentrations in porewater and grain increased by a factor of 4.9 and 3.3, respectively, with ZVI amendment. The three amendments affected grain concentrations of iAs, DMA and Cd mainly by modulating their translocation within plant and the levels of As(III), silicon, dissolved organic carbon, iron or Cd in porewater. All three amendments (SC, Mg/SC and ZVI) have the potential to simultaneously mitigate Cd and iAs accumulation in rice grain, although the pathways are different.

Roles of serum uric acid on the association between arsenic exposure and incident metabolic syndrome in an older Chinese population.

Growing evidences showed that heavy metals exposure may be associated with metabolic diseases. Nevertheless, the mechanism underlying arsenic (As) exposure and metabolic syndrome (MetS) risk has not been fully elucidated. So we aimed to prospectively investigate the role of serum uric acid (SUA) on the association between blood As exposure and incident MetS. A sample of 1045 older participants in a community in China was analyzed. We determined As at baseline and SUA concentration at follow-up in the Yiwu Elderly Cohort. MetS events were defined according to the criteria of the International Diabetes Federation (IDF). Generalized linear model with log-binominal regression model was applied to estimate the association of As with incident MetS. To investigate the role of SUA in the association between As and MetS, a mediation analysis was conducted. In the fully adjusted log-binominal model, per interquartile range increment of As, the risk of MetS increased 1.25-fold. Compared with the lowest quartile of As, the adjusted relative risk (RR) of MetS in the highest quartile was 1.42 (95% confidence interval, CI: 1.03, 2.00). Additionally, blood As was positively associated with SUA, while SUA had significant association with MetS risk. Further mediation analysis demonstrated that the association of As and MetS risk was mediated by SUA, with the proportion of 15.7%. Our study found higher As was remarkably associated with the elevated risk of MetS in the Chinese older adults population. Mediation analysis indicated that SUA might be a mediator in the association between As exposure and MetS.

Arsenic exposure and oxidative damage to lipid, DNA, and protein among general Chinese adults: A repeated-measures cross-sectional and longitudinal study.

Arsenic-related oxidative stress and resultant diseases have attracted global concern, while longitudinal studies are scarce. To assess the relationship between arsenic exposure and systemic oxidative damage, we performed two repeated measures among 5236 observations (4067 participants) in the Wuhan-Zhuhai cohort at the baseline and follow-up after 3 years. Urinary total arsenic, biomarkers of DNA oxidative damage (8-hydroxy-2'-deoxyguanosine (8-OHdG)), lipid peroxidation (8-isoprostaglandin F2alpha (8-isoPGF2α)), and protein oxidative damage (protein carbonyls (PCO)) were detected for all observations. Here we used linear mixed models to estimate the cross-sectional and longitudinal associations between arsenic exposure and oxidative damage. Exposure-response curves were constructed by utilizing the generalized additive mixed models with thin plate regressions. After adjusting for potential confounders, arsenic level was significantly and positively related to the levels of global oxidative damage and their annual increased rates in dose-response manners. In cross-sectional analyses, each 1% increase in arsenic level was associated with a 0.406% (95% confidence interval (CI): 0.379% to 0.433%), 0.360% (0.301% to 0.420%), and 0.079% (0.055% to 0.103%) increase in 8-isoPGF2α, 8-OHdG, and PCO, respectively. More importantly, arsenic was further found to be associated with increased annual change rates of 8-isoPGF2α (ß: 0.147; 95% CI: 0.130 to 0.164), 8-OHdG (0.155; 0.118 to 0.192), and PCO (0.050; 0.035 to 0.064) in the longitudinal analyses. Our study suggested that arsenic exposure was not only positively related with global oxidative damage to lipid, DNA, and protein in cross-sectional analyses, but also associated with annual increased rates of these biomarkers in dose-dependent manners.

Occupational exposure to arsenic and leukopenia risk: Toxicological alert.

Arsenic and its inorganic compounds affect numerous organs and systemic functions, such as the nervous and hematopoietic systems, liver, kidneys, and skin. Despite a large number of studies on arsenic toxicity, rare reports have investigated the leukopenia incidence in workers exposed to arsenic. In workplaces, the main source of workers' exposure is the contaminated air by the inorganic arsenic in mines, arsenic or copper smelter industries, and chemical factories. Erythropoiesis inhibition is one of the arsenic effects and it is related to regulatory factor GATA-1. This factor is necessary for the normal differentiation of early erythroid progenitors. JAK-STAT is an important intracellular signal transduction pathway responsible for the mediating normal functions of several cytokines related to cell proliferation and hematopoietic systems development and regulation. Arsenic inactivates JAK-STAT by inhibiting JAK tyrosine kinase and using the IFNγ pathway. The intravascular hemolysis starts after the absorption phase when arsenic binds to the globin of hemoglobin in erythrocytes and is transported into the body, which increases the oxidation of sulfhydryl groups in hemoglobin. So, this article intends to highlight the potential leukopenia risk via inhalation for workers exposed to arsenic and suggests a possible mechanism for this leukopenia through the JAK-signal transducer and activator of transcription (STAT) pathway inhibition.

Predicting the risk of arsenic accumulation in soil-rice system in Asian monsoon region.

Rice is a staple food for a significant portion of the global population. Arsenic (As) accumulated in rice grains influences rice quality which threatens human health. In this study, we used three machine learning models to predict arsenic accumulation in rice based on over 300 surveys. The prediction results of soil arsenic indicate that high-arsenic soil areas are mainly distributed in South and Southeast Asia such as India, China, and Thailand. In addition, higher bioaccumulation factors (BAF), associated with higher temperature, are predominantly observed in eastern India and southern Myanmar. However, arsenic content in soil is relatively lower in these areas. About 5.5 billion population may be threatened by the consumption of high-arsenic rice. It can be concluded that temperatures may influence the BAF except for soil arsenic, and soil physicochemical properties. Further research on the relationship between climate parameters and BAF should be conducted to address and adapt to future climate change. Additionally, understanding the mechanism of arsenic accumulation under different climatic conditions is crucial for developing agricultural technologies to reduce arsenic accumulation in rice.

Dominant role of soil iron and organic matters in arsenic transfer from soil to plant in a mine area in Hunan Province, Central China.

The transfer of arsenic (As) from soil to plant could be significantly influenced by soil parameters through regulating soil As bioavailability. To distinguish the bioavailable As provided by soil and the As uptaken by plants, herein two different soil bioavailable were defined, namely potential soil bioavailable As (evaluated through the bioavailable fraction of As) and actual soil bioavailable As (assessed through plant bioaccumulation factor, BF, and BFavailable). To identify the dominant soil parameters for the two soil bioavailable As forms, soil and plant samples were collected from a former As mine site. The results showed that the potential bioavailable As only accounted for 1.77 to 11.43% in the sampled soils, while the BF and BFavailable in the sampled vegetables ranged from 0.00 to 1.01 and 0.01 to 17.87, respectively. Despite a similar proportion of As in the residual fraction, soil with higher pH and organic matter (OM) content and lower iron (Fe) content showed a higher potential soil bioavailable As. Correlation analysis indicated a relationship between the soil pH and potential soil bioavailable As (r = 0.543, p < 0.01) and between the soil Fe and actual soil bioavailable As (r = - 0.644, p < 0.05, r = - 0.594, p < 0.05). Stepwise multiple linear regression (SMLR) analysis was employed to identify the dominant soil parameters and showed that soil pH and phosphorus (P) content could be used to predict the potential soil bioavailable As (R2 = 0.69, p < 0.001). On the other hand, soil Fe and OM could be used to predict the actual soil bioavailable As (R2 = 0.18-0.86, p < 0.001-0.015, in different vegetables). These results suggest that different soil parameters affect potential and actual soil bioavailable As. Hence, soil Fe and OM are the most important parameters controlling As transfer from soil to plant in the investigated area.

Seasonal and spatial variations of arsenic and its species in particulate matter in an urban environment of Brno, Czech Republic.

The present paper deals with an analysis of total arsenic concentration using ICP-MS/MS and an analysis of concentration of several arsenic species, arsenite (AsIII), arsenate (AsV), monomethylarsonate (MMA), dimethylarsenite (DMA), and trimethylarsine oxide (TMAO), using HPLC-ICP-MS/MS in the PM10 fraction of airborne urban aerosol. The samples were collected during two campaigns, in the autumn of 2022 and in the winter of 2023, at three locations within the central European city of Brno, with the aim to evaluate the seasonal and spatial variations in the PM10 composition. The results confirmed only the seasonal variability in the content of the methylated arsenic species in PM10 influenced by biomethylation processes. To gain better understanding of the possible arsenic origin, a supplementary analysis of the total arsenic concentrations was performed in samples of different size fractions of particulate matter collected using ELPI + . Local emissions, including industrial activities and heating during the winter season, were suggested as the most likely predominant source contributing to the total As content in PM10.

Simultaneously reducing methane emissions and arsenic mobility by birnessite in flooded paddy soil: Overlooked key role of organic polymerisation.

Flooding of paddy fields enhances methane (CH4) emissions and arsenic (As) mobilisation, which are crucial issues for agricultural greenhouse gas emissions and food safety. Birnessite (δ-MnO2) is a common natural oxidant and scavenger for heavy metals. In this study, birnessite was applied to As-contaminated paddy soil. The capacity for simultaneously alleviating CH4 emissions and As mobility was explored. Soil microcosm incubation results indicated that birnessite addition simultaneously reduced CH4 emissions by 47 %-54 % and As release by 38 %-85 %. The addition of birnessite decreased the dissolved organic carbon (DOC) contents and altered its chemical properties. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) results showed that birnessite reduced the labile fractions of proteins, carbohydrates, lignins, tannins, and unsaturated hydrocarbons, however, increased the abundance of condensed aromatic structures, suggesting the polymerisation of dissolved organic matter (DOM) by birnessite. The degradation of labile fractions and the polymerisation of DOM resulted in an inventory of recalcitrant DOM, which is difficult for microbes to metabolise, thus inhibiting methanogenesis. In contrast, birnessite addition increased CH4 oxidation, as the particulate methane monooxygenase (pmoA) gene abundance increased by 30 %. The enhanced polymerisation of DOM by birnessite also increased As complexation with organics, leading to the transfer of As to the organic bound phase. In addition, the decrease in the ferrous ion [Fe(II)] concentration with birnessite indicated that the reductive dissolution of Fe oxides was suppressed, which limited the release of arsenite [As(III)] under reducing conditions. Furthermore, birnessite decreased As methylation and shaped the soil microbial community structure by enriching the metal-reducing bacterium Bacillus. Overall, our results provide a promising method to suppress greenhouse gas emissions and the risk of As contamination in paddy soils, although further studies are needed to verify its efficacy and effectiveness under field conditions.

Visual Hallucinations With Arsenic Trioxide Therapy in Acute Promyelocytic Leukemia.

A 68-year-old male with a history of diabetes and hypertension was diagnosed with acute promyelocytic leukemia (APML). He underwent induction therapy with all-trans retinoic acid (ATRA) and arsenic trioxide. He had a complete hematologic response and was initiated on consolidation therapy with arsenic trioxide (0.15 mg/kg/day intravenous (IV)) and ATRA (45 mg/per meter square of body surface area/day IV). He developed blurred vision and floaters after a few days. Soon after, he felt that his diabetic neuropathy had suddenly worsened. The floaters and flashing lights worsened and morphed into visual hallucinations. He reported seeing figures watching him from the corner of the room. He was admitted and head imaging was unremarkable. Routine labs did not show anything unusual. Arsenic trioxide therapy was held. The hallucinations gradually started decreasing and eventually subsided after around eight weeks. ATRA was continued but arsenic was permanently discontinued. Arsenic is known to cause poisoning if exposed in significant amounts. The arsenic dose used for APML is substantially low (0.15 mg/kg/day IV). We delineate this unanticipated case of arsenic toxicity leading to severe neurological symptoms like visual hallucinations which has not been previously reported in the literature. It is imperative to closely monitor patients who are on arsenic therapy and inform them about possible rare toxicities.

Assessment of rice genotypes through the lens of morpho-physiological and biochemical traits in response to arsenic stress.

Rice is a globally important food crop which is sensitive to the presence of a metalloid, arsenic (As). There is limited research pertaining to identifying relevant As-tolerant rice germplasm in adaptive breeding research initiatives, despite the fact that As contamination in rice has long been known. This study served to identify the growth performance of different rice genotypes under high levels of As. Rice seed germination analysis (germination percentage, GP) was performed to categorize the eight different rice genotypes and growing under varying As levels including As25, 25 µM and As50, 50 µM. The Zhenong 41 was identified as the highly tolerant genotypes with lowest decrease in GP by 87 %, plant height (PH) by 26 %, and dry weight (DW) by 16 %; while 9311 was observed to be the most sensitive genotype with highest reduction in GP by 44 %, PH by 48 % and DW by 54 % under As25 stress conditions, compared to control treatment. The higher As50 stress treatment delivered more adverse growth inhibitory effects than the rice plants cultivated under As25. Specifically, the As-sensitive rice genotype 9311 showed significantly higher decrease in foliar chlorophyll contents relative to the other genotypes, especially Zhenong 41 (As-tolerant). During exposure to high As levels, the rice genotype 9311 significantly modulated and augmented the production of MDA and H2O2 by stimulating the activities of POD, SOD, and CAT. This study revealed interesting insights into the responses of rice genotypes to variable As stresses throughout the various growth stages. Overall, the findings of this study could be harnessed to support any ongoing As-tolerant rice breeding agendas for cultivation in As-polluted environments.

Biochar and biosorbents derived from biomass for arsenic remediation.

Global groundwater contamination by Arsenic (As) presents a grave danger to the health of living beings and wildlife, demanding comprehensive remediation strategies. This review delves into the complex landscape of arsenic remediation, encompassing its chemical forms, occurrences, sources, and associated health risks. Advanced techniques, notably biomass-derived adsorbents, emerge as promising and cost-effective solutions. The exploration spans preparing and modifying biomass-derived adsorbents, unraveling their adsorption capacity, influencing factors, isotherms, kinetics, and thermodynamics. Noteworthy attention is given to plant-agricultural waste, algal-fungal-bacterial, and iron-modified biomass-derived adsorbents. The comprehensive discussion of the adsorption mechanism highlights the efficacy of low-cost biomass, particularly from plant, animal, and agricultural residues, offering a sustainable remedy for arsenic removal. This insightful review contributes to the understanding of evolving technologies essential for addressing arsenic contamination in wastewater, emphasizing the potential of renewable biomaterials in advancing efficient remediation practices.

Prevalence of perturbed gut microbiota in pathophysiology of arsenic-induced anxiety- and depression-like behaviour in mice.

Severe toxic effects of arsenic on human physiology have been of immense concern worldwide. Arsenic causes irrevocable structural and functional disruption of tissues, leading to major diseases in chronically exposed individuals. However, it is yet to be resolved whether the effects result from direct deposition and persistence of arsenic in tissues, or via activation of indirect signaling components. Emerging evidences suggest that gut inhabitants play an active role in orchestrating various aspects of brain physiology, as the gut-brain axis maintains cognitive health, emotions, learning and memory skills. Arsenic-induced dysbiosis may consequentially evoke neurotoxicity, eventually leading to anxiety and depression. To delineate the mechanism of action, mice were exposed to different concentrations of arsenic. Enrichment of Gram-negative bacteria and compromised barrier integrity of the gut enhanced lipopolysaccharide (LPS) level in the bloodstream, which in turn elicited systemic inflammation. Subsequent alterations in neurotransmitter levels, microglial activation and histoarchitectural disruption in brain triggered onset of anxiety- and depression-like behaviour in a dose-dependent manner. Finally, to confirm whether the neurotoxic effects are specifically a consequence of modulation of gut microbiota (GM) by arsenic and not arsenic accumulation in the brain, fecal microbiota transplantations (FMT) were performed from arsenic-exposed mice to healthy recipients. 16S rRNA gene sequencing indicated major alterations in GM population in FMT mice, leading to severe structural, functional and behavioural alterations. Moreover, suppression of Toll-like receptor 4 (TLR4) using vivo-morpholino oligomers (VMO) indicated restoration of the altered parameters towards normalcy in FMT mice, confirming direct involvement of the GM in inducing neurotoxicity through the arsenic-gut-brain axis. This study accentuates the potential role of the gut microbiota in promoting neurotoxicity in arsenic-exposed mice, and has immense relevance in predicting neurotoxicity under altered conditions of the gut for designing therapeutic interventions that will target gut dysbiosis to attenuate arsenic-mediated neurotoxicity.

Application of green solvents for arsenic removal from petroleum produced water: Statistical, DFT and McCabe-Thiele determination.

This work presents the novel application of green oils to extract arsenic ions from petroleum produced water via liquid-liquid extraction (LLE). In the experiment, the removal of arsenic ions from synthetic petroleum produced water is investigated, using five green oils: canola oil, corn oil, linseed oil, rice bran oil, and sunflower oil, in place of petroleum-based solvents: toluene and kerosene. Both extraction and stripping optimizations are examined. For extractants, Aliquat 336 and Cyanex 921 are implemented. The initial arsenic concentration (3.984 mg L-1) of petroleum produced water is examined. Results demonstrate that Aliquat 336 in corn oil proved to be most effective for arsenic removal. At optimal conditions via response surface methodology (RSM), the highest extraction and stripping percentages reached 99.95 % and 100.00 %, respectively. In accordance with the World Health Organization (WHO) levels of ≤0.01 mg L-1, arsenic concentration remaining in the extracted water (0.002 mg L-1), is seen to fulfill the requirement needed. The extraction and stripping kinetics are of first and second-order. Mechanisms of arsenic removal are evaluated via density functional theory (DFT). Further, selectivity, recycling of the organic phase, and the number of stages via McCabe-Thiele theory are determined under optimal conditions.

Multiple roles of arsenic compounds in phase separation and membraneless organelles formation determine their therapeutic efficacy in tumors.

Arsenic compounds are widely used for the therapeutic intervention of multiple diseases. Ancient pharmacologists discovered the medicinal utility of these highly toxic substances, and modern pharmacologists have further recognized the specific active ingredients in human diseases. In particular, Arsenic trioxide (ATO), as a main component, has therapeutic effects on various tumors (including leukemia, hepatocellular carcinoma, lung cancer, etc.). However, its toxicity limits its efficacy, and controlling the toxicity has been an important issue. Interestingly, recent evidence has pointed out the pivotal roles of arsenic compounds in phase separation and membraneless organelles formation, which may determine their toxicity and therapeutic efficacy. Here, we summarize the arsenic compounds-regulating phase separation and membraneless organelles formation. We further hypothesize their potential involvement in the therapy and toxicity of arsenic compounds, highlighting potential mechanisms underlying the clinical application of arsenic compounds.