Ecotoxicity of ammonium chlorophenoxyacetate derivatives towards aquatic organisms: Unexpected enhanced toxicity upon oxygen by sulfur replacement

Detection and adsorption of 2-methyl-4-chlorophenoxyacetic acid in vegetables via dual-functional molecularly imprinted polymer doping with carbon dot

2-Methyl-4-chlorophenoxyacetic acid (MCPA) is one of the most widely used herbicides, so adsorption and detection of MCPA in the environment is critical. Blue fluorescent carbon dot (CD) was synthesized from citric acid and urea, which could be quenched by MCPA. Herein, bifunctional molecularly imprinted polymer (CD@MIP) was prepared on monodisperse poly (glycidyl methacrylate-co-ethylene glycol dimethacrylate) microspheres, with 4-vinylpyridine as the functional monomer, ethylene glycol dimethacrylate as the cross-linking agent, and doped with CD. The enrichment ability of CD@MIP for MCPA and fluorescence detection performance were determined. The maximum adsorption amount of MCPA was 93.9 mg g-1 as determined by isothermal adsorption experiments and was in accordance with the Langmuir adsorption model. The results of the kinetic experiments showed that the adsorption equilibrium reached within 30 min, which possessed a relatively fast adsorption rate and was in accordance with the pseudo-second-order adsorption model. Both MIP without CD and non-imprinted polymers were also fabricated and tested as references. Fluorescence experiments showed good linearity of CD@MIP in the range of 0-80 μmol. The cabbage samples were analyzed by high performance liquid chromatography with a linear range of 0.02-15 μg mL-1, recoveries of 90.5%-98% and low relative standard deviations (RSD, n = 3) of 1.5%-5.9%. CD@MIP with excellent performance provides a feasible practical application in the detection and enrichment of MCPA.

Application of interpretable machine learning models to improve the prediction performance of ionic liquids toxicity

With the wide application prospect of ionic liquids (ILs) as solvent in the future industry, in order to promote green and sustainable chemical engineering, the toxicity problem of common concern has been systematically modeled. Machine learning has promoted the development of chemical property prediction model with its powerful data processing ability. Two typical ensemble learning models, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), were used to model the toxicity of ILs to Vibrio fischeri in this work. The model's hyperparameters were fine-tuned using Bayesian optimization, and its robustness was enhanced through the 5-fold cross validation. The results of the model comparison showed that the XGBoost model exhibited good generalization ability. In addition, the SHapley Additive exPlanations (SHAP) method was used to explain the model in more detail and the XGBoost model was used to supplement the toxicity value matrix of 1590 ILs.

Calculation of Lipophilicity of Organophosphate Pesticides Using Density Functional Theory

Higher lipophilicity facilitates the passage of a substance across lipid cell membranes, the blood–brain barrier and protein binding, and may also indicate its toxicity. We proposed eight methods for predicting the lipophilicity of the 22 most commonly used organophosphate pesticides. In this work, to determine the lipophilicity and thermodynamic parameters of the solvation of pesticides, we used methods of density functional theory with various basis sets, as well as modern Grimm methods. The prediction models were evaluated and compared against eight performance statistics, as well as time and RAM used in the calculation. The results show that the PBE-SVP method provided the best of the proposed predictive capabilities. In addition, this method consumes relatively less CPU and RAM resources. These methods make it possible to reliably predict the ability of pesticide molecules to penetrate cell membranes and have a negative effect on cells and the organism as a whole.

Chronic ecotoxicology and statistical investigation of ciprofloxacin and ofloxacin to Daphnia magna under extendedly long-term exposure

Ciprofloxacin (CFX) and ofloxacin (OFX) are two of the most often used fluoroquinolone antibiotics, and their residues are found in large amounts in various aquatic settings. However, the toxicity tests of CFX using eukaryotic organisms such as Daphnia magna are inadequate, and the test result of OFX is currently unknown. Therefore, the chronic toxicity test for D. magna was performed during 42 days under exposure to CFX and OFX concentrations of 50, 500, and 5000 μg L^-1. All exposure conditions did not cause mortality for D. magna. CFX exposure at 500 μg L^-1 resulted in an earlier oogenesis date and increased brood size in the second birth. The Poisson-based generalized linear mixed-effects model revealed that the reduction of fertility was statistically significant for the CFX and OFX exposures at 5000 μg L^-1. On the other hand, the production of dead eggs as offspring degradation was also found significantly as maternal D. magna exposed to antibiotics at 5000 μg L^-1. In addition, following long-term exposure to antibiotics, maternal adaptation to antibiotics was established for offspring deterioration and fertility. However, the OFX exposure showed that the fertility-suppressed effects continued for a longer period than the CFX exposure. Although no rational explanation has yet been given for the more substantial effect of OFX on reducing fertility than CFX, molecular cell biology and symbiotic microbial flora derived from previous studies could explain our ecotoxicological results. This study is the first report for the OFX chronic toxicities on D. magna by comparing it to the toxicity of CFX. Our study contributes to guiding the future impact assessment of fluoroquinolone antibiotic pollution on ecosystems, including the need for new statistical methods in ecotoxicological studies.

Review of the toxic effects of ionic liquids

Interest in ionic liquids (ILs), called green or designer solvents, has been increasing because of their excellent properties such as thermal stability and low vapor pressure; thus, they can replace harmful organic chemicals and help several industrial fields e.g., energy-storage materials production and biomaterial pretreatment. However, the claim that ILs are green solvents should be carefully considered from an environmental perspective. ILs, given their minimal vapor pressure, may not directly cause atmospheric pollution. However, they have the potential to cause adverse effects if leaked into the environment, for instance if they are spilled due to human mistakes or technical errors. To estimate the risks of ILs, numerous ILs have had their toxicity assessed toward several micro- and macro-organisms over the past few decades. Since the toxic effects of ILs depend on the method of estimating toxicity, it is necessary to briefly summarize and comprehensively discuss the biological effects of ILs according to their structure and toxicity testing levels. This can help simplify our understanding of the toxicity of ILs. Therefore, in this review, we discuss the key findings of toxicological information of ILs, collect some toxicity data of ILs to different species, and explain the influence of IL structure on their toxic properties. In the discussion, we estimated two different sensitivity values of toxicity testing levels depending on the experiment condition, which are theoretical magnitudes of the inherent sensitivity of toxicity testing levels in various conditions and their changes in biological response according to the change in IL structure. Finally, some perspectives, future research directions, and limitations to toxicological research of ILs, presented so far, are discussed.

Removal of 4-chloro-2-methylphenoxyacetic acid from water by MIL-101(Cr) metal-organic framework: kinetics, isotherms and statistical models

Effective removal of 4-chloro-2-methylphenoxyacetic acid (MCPA), an emerging agrochemical contaminant in water with carcinogenic and mutagenic health effects has been reported using hydrothermally synthesized MIL-101(Cr) metal-organic framework (MOF). The properties of the MOF were ascertained using powdered X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermal gravimetric analysis (TGA), field emission scanning electron microscopy (FESEM) and surface area and porosimetry (SAP). The BET surface area and pore volume of the MOF were 1439 m2 g-1 and 0.77 cm3 g-1, respectively. Artificial neural network (ANN) model was significantly employed for the accurate prediction of the experimental adsorption capacity (qe ) values with minimal error. A rapid removal of the pollutant (99%) was recorded within short time (approx. 25 min), and the reusability of the MOF (20 mg) was achieved up to six cycles with over 90% removal efficiency. The kinetics, isotherm and thermodynamics of the process were described by the pseudo-second-order, Freundlich and endothermic adsorption, respectively. The adsorption process is spontaneous based on the negative Gibbs free energy values. The significant correlation between the experimental findings and simulation results suggests the great potential of MIL-101(Cr) for the remediation of MCPA from water matrices.

Adsorption of dicamba and MCPA onto MIL-53(Al) metal-organic framework: response surface methodology and artificial neural network model studies

An aluminium-based metal–organic framework ((MOF), MIL-53(Al)), was hydrothermally synthesized, characterized and applied for the remediation of the herbicides dicamba (3,6-dichloro-2-methoxy benzoic acid) and 4-chloro-2-methylphenoxyacetic acid (MCPA) in aqueous medium. Response surface methodology (RSM) and artificial neural network (ANN) were used to design, optimize and predict the non-linear relationships between the independent and dependent variables. The shared interaction of the effects of key response parameters on the adsorption capacity were assessed using the central composite design-RSM and ANN optimization models. The optimum adsorption capacities for dicamba and MCPA are 228.5 and 231.9 mg g⁻¹, respectively. The RSM ANOVA results showed significant p-values, with coefficients of determination (R²) = 0.988 and 0.987 and R² adjusted = 0.974 and 0.976 for dicamba and MCPA, respectively. The ANN prediction model gave R² = 0.999 and 0.999, R² adjusted = 0.997 and 0.995 and root mean square errors (RMSEs) of 0.001 and 0.004 for dicamba and MCPA, respectively. In each set of experimental conditions used for the study, the ANN gave better prediction than the RSM, with high accuracy and minimal error. The rapid removal (∼25 min), reusability (5 times) and good agreement between the experimental findings and simulation results suggest the great potential of MIL-53(Al) for the remediation of dicamba and MCPA from water matrices.

Rapid equilibration within a short time, high adsorption capacity, optimization, multivariate interaction of adsorption parameters and artificial neural network prediction model.

Residues and Dietary Risk Assessments of 2,4-D Isooctyl Ester, Metribuzin, Acetochlor, and 2-Ethyl-6-methylaniline in Corn or Soybean Fields

Since 2,4-dichlorophenoxy acetic acid (2,4-D) was discovered in the 1940s, 2,4-D and its derivatives remain among most commonly used herbicides in the world. There have been recent increases in using 2,4-D products in a combination with other herbicides such as metribuzin and acetochlor to control noxious weeds. However, accurate analysis of 2,4-D isooctyl ester remains to be improved due to long analysis time and rapid conversion of the ester to acid (i.e., under-reporting residues). In this work, a simple hydrolysis procedure was introduced to provide a quantitative hydrolytic rate of the ester (>95%) and did not affect the other pH-sensitive compounds. Analysis parameters and sample pretreatments were optimized for improved selectivity and accuracy. The hydrolysis-QuEChERS (quick, easy, cheap, effective, rugged, and safe) technique for multidetermination of 2,4-D isooctyl ester, metribuzin, acetochlor, and 2-ethyl-6-methylaniline in corn and soybeans via high performance liquid chromatography-tandem mass spectrometry was established. The method had average recoveries of 74-109% with relative standard deviations ≤13.5% and limits of quantifications (LOQs) of 0.05 mg/kg. The terminal residues of these compounds found in real edible matrixes were less than the corresponding LOQs at harvest time. The risk quotients were far below 100%, indicating a low health risk to consumers.