Coefficient Log Research Articles

Pesticides’ Cornea Permeability—How Serious Is This Problem?

Background: A total of 348 pesticides from different chemical families (carbamates, organochlorines organophosphorus compounds, pyrethroids, triazines and miscellaneous) were investigated in the context of their cornea permeability and potential to cause eye corrosion. Methods: Multivariate models of cornea permeability based on compounds whose cornea permeability has been determined experimentally were proposed. The models, applicable to compounds across a relatively broad lipophilicity range (e.g., pesticides with octanol–water partition coefficient log P up to ca. 8), assume a reverse-parabolic relationship between cornea permeability and lipophilicity, expressed as XLOGP3; other main descriptors present in the models are log D at pH 7.4 and polar surface area (PSA). Results: It appears that the trans-corneal transport of all studied pesticides is possible to some degree; however, it is more difficult for the majority of highly lipophilic pesticides from the organochlorine and pyrethroid families. The same set of 348 pesticides was also evaluated for their eye-corrosive potential using novel artificial neural network models involving simple physico-chemical properties of the compounds (lipophilicity, aqueous solubility, polar surface area, H-bond donor and acceptor count and the count of atoms such as N, NH, O, P, S and halogens). Conclusions: It was concluded that eye corrosion is an issue, especially among the pesticides from organochlorine and organophosphorus families.

Predictive modeling of microplastic adsorption in aquatic environments using advanced machine learning models.

This study addresses the critical environmental concerns surrounding microplastics, aiming to elucidate the intricate factors influencing their behavior and interactions with organic pollutants. Utilizing advanced artificial neural network modeling techniques, including GRU, LSTM, RNN, and CNN, a comprehensive analysis of microplastic sorption capacity and underlying mechanisms is conducted. The research relies on a meticulously curated dataset encompassing fundamental parameters such as organic compound composition, n-octanol/water partition coefficient, covalent acidity, covalent basicity, molecular polarizability to volume ratio, and the logarithm of the partition coefficient. Findings underscore the significance of understanding the n-octanol/water distribution coefficient (Log D) in predicting organic pollutant fate in aquatic environments, with compounds displaying higher Log D values exhibiting heightened affinity for microplastics, posing substantial ecological and human health risks. Additionally, the study highlights the importance of selecting appropriate models to accurately capture complex sorption processes, especially in varied aquatic environments. Furthermore, the profound impact of acidity, molecular polarizability to volume ratio, and covalent basicity on microplastic behavior is elucidated. Notably, machine learning models and CNNs demonstrate remarkable speed in prediction generation. A comparative analysis of four robust machine learning models establishes fundamental alignment between model predictions and empirical findings. Particularly noteworthy is the RNN model, emerging as the most accurate with an impressive accuracy of 0.967 and a minimum absolute error of 0.38. These results underscore the efficacy of the RNN model in predicting microplastic dynamics, holding promise for significant contributions to addressing microplastic pollution.

Silicone wristbands for assessing personal chemical exposures: impacts of movement on chemical uptake rates.

Silicone wristbands are utilized as personal passive sampling devices for exposure assessments of semi-volatile organic compounds (SVOCs). While research demonstrates that accumulation of SVOCs on the wristbands correlates with internal dose for many different chemical classes, the mechanisms of accumulation remain poorly understood. Multiple factors such as movement of the individual lead to variable mass transfer conditions at the sampler interface. The objective of this study was to investigate the effect of air flow velocity across the wristband surface on SVOC uptake rates and to evaluate if enhanced rates vary between compounds with a range physicochemical properties. Experiments were conducted in a residential home where wristbands were either held in static conditions or attached to an end-over-end rotator at different speeds for a four week period. We measured the uptake of 17 different SVOCs that are commonly detected in indoor environments and compared their accumulation rates as a function of the rotating velocity. For wristbands moving at tangential speeds of 0.05, 0.5, and 1.1 m s-1 (relevant for a walking pace), the motion enhanced uptake rates by 1.2 ± 0.2, 3.2 ± 0.6, and 4.3 ± 0.8 times the respective rates for the static controls. This enhancement is consistent with gas phase diffusion-controlled mass transfer theory at the wristband interface. Moreover, the enhancement of uptake positively correlated with octanol-air partition coefficients log KOA (R = 0.6; p < 0.02) of the chemicals and negatively correlated with diffusivity (R = 0.5; p < 0.05). In a comparison with worn wristband studies, the ratio of uptakes rates for worn relative to rotating wristbands correlated with SVOC properties (R = 0.85 for log KOA). For SVOCs with log KOA > 9, uptake rates on worn wristbands greatly exceeded (by a factor of 10 to 104) the respective rates in this rotator experiment. These results suggest that a mass transfer mechanism based solely on gas-solid partitioning under variations in air velocity cannot fully explain uptake on worn wristbands. Instead, the results implicate additional processes such as particle phase deposition, direct contact with certain materials, and excretion from skin as pathways of accumulation on the wristband sampler and personal exposure.

A HPLC-assisted mathematical prediction method of ternary solvent systems to develop an intelligent online selection system for countercurrent chromatography solvent system.

Countercurrent chromatography (CCC) is an efficient technique for purifying bioactive natural compounds, but selecting the solvent system can be a time-consuming and crucial process for successful separation. This paper discussed the HPLC-assisted mathematical prediction method for the n-hexane/alcohol solvents/water (HAWat) and ethyl acetate/n-butanol/water (EBuWat) systems and designed an intelligent online selection system to simplify the separation process. First, the applicable rage of HAWat and EBuWat solvent systems were quantified by the methanol concentration at the column inlet when template molecules peak in a HPLC analysis (B%). Then, we analyzed the relationship between the logarithmic partition coefficient (log K) of template molecules and the alcohol solvent ratio by using different brands of chromatography columns. Moreover, the prediction function was developed by correlating the best solvent composition of CCC solvent system with the B% of template molecules. The results indicated that the HAWat system was suitable for separating compounds with B% > 85 %, while the EBuWat system was effective for compounds with 40 % < B% < 55 %. The quadratic function for HAWat systems and one universal EBuWat system (8.2:1.8:10) were determined and verified to develop the HPLC-assisted mathematical prediction function method. The method could select suitable solvent systems for separfigation easily and quickly. And a step of result correction was required for the occasional discrete value. Finally, an intelligent CCC online selection system that integrates established mathematical functions was designed to enable real-time solvent selection, on-demand solvent configuration, and automated sample separation. It eliminates the iterative process of shake-flask experiments and facilitates intelligent upgrading of CCC instrumentation.

Thermo-Responsive Polymer-Modified Carbon Nanofiber Electrodes with Autonomous and Heteronomous Switchable Selectivity for Catechol Derivatives

Sophisticated switchable interfaces enable to develop advanced micromachines and biodevices. In the electrochemistry field, functional electrodes switchable by basically either environmental stimuli, such as changes in temperature and pH, or artificial input signals, such as a specific wavelength and magnetic field, have attracted great attention to develop sensors with tunable sensitivity or selectivity and fuel cells with tunable power output in the past few decades. Recently, we have developed thermo- and photo-responsive cup-stacked carbon nanofiber electrodes modified with thermo-responsive poly(N-isopropylacrylamide) (PNIPA/CSCNF electrodes) [1]. PNIPA is known to be reversibly switched between hydrophilic expanded coil structure and hydrophobic collapsed globule structure by environmental temperature changes. CSCNFs have been used as not only electroactive electrode materials but also photothermal conversion materials of near-infrared (NIR) light. Redox species, such as a hydrophilic [Fe(CN)6]3–/4– ion, easily diffused to the CSCNF electrode surface across the swollen PNIPA layer because of its hydrophobic hydration at 25 ˚C without NIR light irradiation, leading to the larger current responses. However, in an electrolyte solution at 45 ˚C and even 25 ˚C with NIR light (> 940 nm) irradiation, the contracted structure of PNIPA was formed because of its hydrophobic interaction, resulting in suppressing transport of the redox species to the CSCNF electrode surface due to its steric hindrance and hydrophobicity. Therefore, the obtained PNIPA/CSCNF electrode allowed to control the activation and inhibition of the electrochemical process for the diffusional redox probe by both alternating surrounding temperature and irradiating the electrode surface with NIR light (Figure 1). If two chemicals with similar structures but different octanol-water partition coefficient log K ow, such as catechol (Mw = 111, Log K ow = 0.88) and dopamine (Mw = 153, Log K ow = –0.98) known as one of the neurotransmitters, contain in the same solution, the present electrode might enable to detect separately. In the present work, we examined autonomous and heteronomous switchable selectivity for catechol and dopamine at the thermo- and photo-responsive PNIPA/CSCNF electrode. As a result, both catechol and dopamine permeated to the CSCNF electrode surface through the swollen PNIPA layer at 25 ˚C, causing their electrochemical signal readout. In contrast, transport of dopamine was selectively suppressed to the CSCNF electrode surface by exposing PNIPA to temperature at 45 ˚C or NIR light irradiation to the CSCNF electrode surface even at 25 ˚C due to the steric hindrance and hydrophobicity of the collapsed globule structure of the PNIPA layer. The electrochemical signal for catechol was therefore observed preferentially. We thus expected that the present electrode would be applied to electrochemical sensors with autonomous and heteronomous switchable selectivity for catechol-based neurotransmitters. [1] K. Komori, R. Ihara, S. Hirao, M. Liu, Y. Toyota, M. Nakata, Y. Tani, and K. Shiraishi, J. Electroanal. Chem., 992, 116704 (2022). Figure 1

Distribution, sorption patterns, and outflows of riverine microplastics-affiliated linear alkylbenzenes and polycyclic aromatic hydrocarbons in a dynamic coastal zone

Microplastics (MPs) pollution has emerged as a global concern. To mitigate the potential threats by MPs, particularly to coastal regions, it is crucial to comprehend the environmental behavior of MPs and their affiliated chemicals. In the present study, we collected floating MPs using a Manta net (0.33 mm mesh size) in a one-year sampling event in 2022 from the eight major estuaries in the Pearl River Delta, China, and also from five coastal sites in August and December in the same year. Nineteen linear alkylbenzenes (∑19LAB) and 16 polycyclic aromatic hydrocarbons (∑16PAH) affiliated with MPs were measured. The mean concentrations of MPs-affiliated ∑19LAB and ∑16PAH were 6710 (range: 3400–12300) and 5310 (range: 817–19,600) ng g−1, respectively, at the estuarine sites, and were 4920 (range: 2400–7600) and 2610 (range: 911–7890) ng g−1, respectively, at the coastal sites. Significant correlations were found between logarithmic MPs–water partition coefficients (log Kpw) and logarithmic suspended particulate matter–water partition coefficients (log Kd) values for LABs and PAHs, indicating analogous partitioning dynamics for MPs and suspended particulate matter with water. The annual riverine outflows were 1170 and 414 g for ∑19LAB and ∑16PAH, respectively. Although the riverine outflows of LABs and PAHs carried by MPs remain negligible compared to those by suspended particulate matter, an upward trend was identified between 2018 and 2022. Notably, the riverine input of LABs and PAHs carried by suspended particulate matter to the coastal ocean decreased from 2005/2006 to 2022, due to a combination of improved technological processes and energy structures.

Characterization (XRD/TGA-DSC) and assessment of calf thymus DNA interaction with single-crystalline novel complexes from Schiff base ligands

The Schiff base complexes [Zn(H2L)2Cl2] 2/3(CH3OH) 2/3(H2O) (1) and [Cd(H2L)2(NO3)2(CH3OH)2] (2), where H2L is an N-Acylhydrazone ligand, have been investigated mainly using a combinatory approach of single-crystal X-ray diffractometry (XRD), thermogravimetric and differential thermal analysis (TGA-DSC). XRD analysis revealed that both complexes coordinate through the nitrogen atom of the ligand’s pyridine ring. In complex (1), the zinc(II) ion coordinates with two ligands and two chloride ions, forming a distorted tetrahedral geometry. In complex (2), the cadmium(II) ion coordinates with two ligands, two nitrate ions, and two methanol molecules, resulting in an octahedral geometry. The crystalline material’s high purity and precise stoichiometry were crucial for accurate thermoanalytical analysis. Additionally, characterizations were performed using infrared (IR), ultraviolet–visible (UV–vis), molar conductivity, elemental analysis (EA) and nuclear magnetic resonance (NMR) spectroscopy. Biological studies with calf thymus DNA (CT-DNA), using UV–vis spectroscopy, viscosity measurements and ethidium bromide displacement assays indicated intercalative binding of the complexes with DNA. The binding (Kb) and quenching (Ksv) constants (104 L/mol) suggest moderate interaction with CT-DNA. The positive partition coefficients (log P) values in water and 1-octanol suggest a significant preference for the lipid-like organic phase, implying that these complexes can efficiently penetrate biological membranes.

Environmental pH and compound structure affect the activity of short-chain carboxylic acids against planktonic growth, biofilm formation, and eradication of the food pathogen Salmonella enterica.

Short-chain carboxylic acids (SCCAs) that are naturally produced by microbial fermentation play an essential role in delaying microbial spoilage. SCCAs are structurally diverse, but only a few of them are routinely used in food biopreservation. This study investigated the effects of environmental pH and intrinsic properties of 21 structurally different SCCAs on the antimicrobial and antibiofilm activity against Salmonella enterica. Inhibition of SCCA toward planktonic and biofilm growth of S. enterica was higher in an acidic environment (pH 4.5) that is common in fermented products, and for SCCA that possessed both a high acid dissociation strength (pKa) (>4.0) and a positive hydrophobicity [octanol/water partition coefficient (log Kow)]. Crotonic and caproic acids were identified as SCCAs with potential as biopreservatives even at near-neutral pH. SCCA with hydrophilic groups such as lactic acid did not inhibit S. enterica at concentrations up to 50 mM, while SCCA with benzene or methyl groups or a double bond prevented S. enterica growth and biofilm formation. Stimulation of biofilm formation was observed for formic, acetic, and propionic acid close to the minimum inhibitory concentration to reduce 50% of cell density (MIC50) of planktonic cells, and for citric and isocitric acid with an MIC50 of ≥50 mM. The presence of low concentrations of formic and propionic acids during biofilm formation conferred protection during eradication possibly due to a pre-adaptation effect, yet two consecutive acid treatments were successful in eradicating biofilms if the first acid treatment was two- to threefold of the MIC50.IMPORTANCEThis study provides a systematic comparison on the antimicrobial and antibiofilm activity of more than 20 structurally different SCCAs against a common food pathogen. We tested the antimicrobial activity at controlled pH and identified the structure-dependent antimicrobial effects of SCCA without the confounding influence of acidification. The combined effect of pKa and log Kow was identified as an important feature that should be considered when deciding for a specific SCCA in the application as antimicrobial. Our results imply that additional phenomena such as the use of SCCA as substrate and cellular pre-adaption effects have to be taken into consideration. We finally present a two-step treatment as an efficient approach to eradicate biofilms, which can be applied for the disinfection of contact surfaces and manufacturing equipment. Results obtained here can serve as guidelines for application of SCCA to avoid the growth of food pathogens and/or to develop biopreserved food systems.

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study therefore demonstrates a novel multi-criteria decision making (MCDM) framework utilizing machine learning (ML) algorithms coupled with toxicological prioritization index tool (i.e., ml_ToxPi) to rank 251 chemicals of interest in groundwater for subsequent targeted analysis. The MCDM framework integrated chemical analysis data (i.e., peak area and detection frequency), toxicity profiles (i.e., bioactivity ratio, human exposure metadata, and carcinogenicity metadata), as well as the environmental fate and transport information (i.e., octanol-water partition coefficient (log Kow), water solubility, biodegradation half-life, and soil adsorption coefficient (Koc)) for ranking the identified pollutants, and the random forest machine learning model was useful for systematically determining the weighting factors of each variable according to their variable importance scores (R2 = 0.808 and 0.778 for training and testing datasets, respectively, while RMSE = 0.042 in both cases). A total of 47 unique high priority compounds (i.e., ml_ToxPi score ≥ 0.55) were identified across the investigated sampling regions, which constituted diverse groups of compounds classified according to their chemical uses, such as alkylated polycyclic aromatic hydrocarbons (alkyl-PAHs), organophosphate flame retardants (OPFRs), parent PAHs, personal care products (PCPs), pesticides, pharmaceuticals, phenols, plasticizers, transformation product (TPs), and other industrial use chemicals. By incorporating relevant variables into the proposed ML-optimized ToxPi MCDM framework, the prioritization approach described here may be adopted in future SNTS assessment of environmental and biological media.

Exploring the Influence of Ionic Liquid Anion Structure on Gas-Ionic Liquid Partition Coefficients of Organic Solutes Using Machine Learning.

This article presents an in-depth investigation into the influence of anionic structures of ionic liquids (ILs) on gas-ionic liquid partition coefficients (log K) of organic solutes in three ILs. While the primary objective was to examine whether there is a relationship between the molecular structure of the IL anion component and log K, additionally it was looked at whether the molecular descriptors of the anion in the relationships encode possible molecular interactions during the miscibility and partitioning in the IL. The research involves the compilation of data series of experimental log K values, where the cation component is constant. Such representative data series were obtained for three solutes─benzene, cyclohexane, and methanol─in three ILs with a uniform cationic component of methylimidazoliums. Using multiple linear regression models enhanced with machine learning techniques, the relationship between anionic structures and log K values was successfully quantified and modeled. Systematically selected molecular descriptors describing the anion structure show that in the case of methanol log K is strongly dependent on hydrogen bonds and Coulomb-dipolar interactions with the anion component, while in the case of benzene and cyclohexane the dispersion forces of the anion component are dominant. The outlier analysis and data interpretation highlight the need for extensive experimental data. The results confirm the initial hypothesis and provide valuable information on the role of the structure of the anionic component in determining the partitioning behavior of organic solutes. This knowledge is important for the design and optimization of ILs for specific applications, particularly as solvents in various industrial processes. The research also provides useful information about molecular interactions taking place in the interfaces of IL and organic additives in complex liquid media such as multicomponent electrolyte solutions, for example in energy storage applications.

Fouling of Reverse Osmosis (RO) and Nanofiltration (NF) Membranes by Low Molecular Weight Organic Compounds (LMWOCs), Part 1: Fundamentals and Mechanism.

Reverse osmosis (RO) and nanofiltration (NF) are ubiquitous technologies in modern water treatment, finding applications across various sectors. However, the availability of high-quality water suitable for RO/NF feed is diminishing due to droughts caused by global warming, increasing demand, and water pollution. As concerns grow over the depletion of precious freshwater resources, a global movement is gaining momentum to utilize previously overlooked or challenging water sources, collectively known as "marginal water". Fouling is a serious concern when treating marginal water. In RO/NF, biofouling, organic and colloidal fouling, and scaling are particularly problematic. Of these, organic fouling, along with biofouling, has been considered difficult to manage. The major organic foulants studied are natural organic matter (NOM) for surface water and groundwater and effluent organic matter (EfOM) for municipal wastewater reuse. Polymeric substances such as sodium alginate, humic acid, and proteins have been used as model substances of EfOM. Fouling by low molecular weight organic compounds (LMWOCs) such as surfactants, phenolics, and plasticizers is known, but there have been few comprehensive reports. This review aims to shed light on fouling behavior by LMWOCs and its mechanism. LMWOC foulants reported so far are summarized, and the role of LMWOCs is also outlined for other polymeric membranes, e.g., UF, gas separation membranes, etc. Regarding the mechanism of fouling, it is explained that the fouling is caused by the strong interaction between LMWOC and the membrane, which causes the water permeation to be hindered by LMWOCs adsorbed on the membrane surface (surface fouling) and sorbed inside the membrane pores (internal fouling). Adsorption amounts and flow loss caused by the LMWOC fouling were well correlated with the octanol-water partition coefficient (log P). In part 2, countermeasures to solve this problem and applications using the LMWOCs will be outlined.

Antimicrobial peptide LyeTx I mn∆K labeled with 68Ga is a potential PET radiopharmaceutical for molecular imaging of infections

BackgroundAntimicrobial peptides have been radiolabeled and investigated as molecular diagnostic probes due to their propensity to accumulate in infectious sites rather than aseptic inflammatory lesions. LyeTx I is a cationic peptide from the venom of Lycosa erythrognatha, exhibiting significant antimicrobial activity. LyeTx I mn∆K is a shortened derivative of LyeTx I, with an optimized balance between antimicrobial and hemolytic activities. This study reports the first 68Ga-radiolabeling of the DOTA-modified LyeTx I mn∆K and primarily preclinical evaluations of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a PET radiopharmaceutical for infection imaging. MethodsDOTA(K)-LyeTx I mn∆K was radiolabeled with freshly eluted 68Ga. Radiochemical yield (RCY), radiochemical purity (RCP), and radiochemical stability (in saline and serum) were evaluated using ascending thin-layer chromatography (TLC) and reversed-phase high-performance liquid chromatography (RP-HPLC). The radiopeptide's lipophilicity was assessed by determining the logarithm of the partition coefficient (Log P). Serum protein binding (SBP) and binding to Staphylococcus aureus (S. aureus) cells were determined in vitro. Ex vivo biodistribution studies and PET/CT imaging were conducted in healthy mice (control) and mice with infection and aseptic inflammation to evaluate the potential of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a specific PET radiopharmaceutical for infections. Results[68Ga]Ga-DOTA(K)-LyeTx I mn∆K was obtained with a high RCY (>90 %), and after purification through a Sep-Pak C18 cartridge, the RCP exceeded 99 %. Ascending TLC and RP-HPLC showed that the radiopeptide remained stable for up to 3.0 h in saline solution and up to 1.5 h in murine serum. [68Ga]Ga-DOTA(K)-LyeTx I mn∆K exhibited hydrophilic characteristics (Log P = −2.4 ± 0.1) and low SPB (ranging from 23.3 ± 0.4 % at 5 min of incubation to 10.5 ± 1.1 % at 60 min of incubation). The binding of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K to S. aureus cells was proportional to bacterial concentration, with binding percentages of 8.8 ± 0.5 % (0.5 × 109 CFU.mL−1), 16.2 ± 1.4 % (1.0 × 109 CFU.mL−1), and 62.2 ± 0.6 % (5.0 × 109 CFU.mL−1). Ex vivo biodistribution studies and PET/CT images showed higher radiopeptide uptake at the infection site compared to the aseptic inflammation site; the latter was similar to the control group. Target-to-non-target (T/NT) ratios obtained by ex vivo biodistribution data were approximately 1.0, 1.3, and 3.0 at all investigated time intervals for the control, aseptic inflammation, and infection groups, respectively. Furthermore, T/NT ratios obtained from PET/CT images were 1.1 ± 0.1 for the control group and 1.4 ± 0.1 for the aseptic inflammation group. For the infection group, T/NT ratio was 5.0 ± 0.3, approximately 5 times greater compared to the former groups. ConclusionsThe results suggest the potential of [68Ga]Ga-DOTA(K)-LyeTx I mn∆K as a PET radiopharmaceutical for molecular imaging of infections.

Solvent screening for the purification of monoterpenoids by countercurrent and centrifugal partition chromatography

AbstractBACKGROUNDCountercurrent chromatography (CCC) and centrifugal partition chromatography (CPC) are efficient techniques to purify terpenoids from essential oils. These methods require suitable solvent systems for the partition between the two immiscible liquid phases. In this study, using the analytical shake‐flask method, we measured the partition coefficients of three model monoterpenoids, namely carvone, eucalyptol and thymol, in 11 biphasic solvent systems, at 298.2 K. Moreover, the predictive COSMO‐RS model was applied to represent the partition coefficients of data measured in this work and retrieved from the literature, the liquid–liquid equilibrium (LLE) data of three solvent families suitable for CCC/CPC separations (i.e., Arizona, Modified Arizona and Green Arizona) and the solute's partition coefficients in the three solvent families.RESULTSThe partition coefficients obtained for thymol and eucalyptol are the first partition data available in the literature. The obtained root mean square deviations (RMSDs) between the experimental and predicted partition coefficients (log basis) varied between 0.28 and 0.49. For LLE, RMSDs of 0.040 and 0.048 were achieved for the Arizona and Green Arizona families, respectively.CONCLUSIONThe predictive COSMO‐RS model describes the monoterpenoid partition coefficients and the LLE data of the solvent families well. The most favorable solvent systems to perform the separations were identified, showing that systems with low and intermediate‐to‐low polarities are the most promising options for separating the selected monoterpenoids from their natural matrices by CCC/CPC techniques. © 2024 Society of Chemical Industry (SCI).

Quantifying the sediment sorption of organic ultraviolet filter chemicals using solvophobic theory

Hydrophobic organic chemicals (HOCs) that enter the aquatic environment often negatively impact organisms, endangering aquatic biodiversity. Understanding sediment sorption equilibria for these chemicals can properly direct mitigation efforts. In addition, many HOCs of environmental concern lack sufficient environmental fate data to adequately assess their risk to ecosystems and humans. In this study, a sorption method addressing solvophobic effects was used to quantify the sorption of an HOC of current environmental concern, OD-PABA (padimate O, 2-ethylhexyl-4-(dimethylamino)benzoate), to a variety of sediments. OD-PABA is an organic ultraviolet filter chemical used in commercial sun protection products; it has been shown to exhibit cytotoxic effects and is known to photochemically transform under natural sunlight conditions. Given its commercial use, it enters the aquatic environment via recreational use and wastewater treatment plant effluent. OD-PABA is strongly hydrophobic; to mitigate the adsorption of OD-PABA to the container walls during sorption experiments, a precise concentration of methanol was used to avoid solvophobic effects. This sorption method was used to determine the sorption capacities for OD-PABA of four sediment samples, each with unique geochemical characteristics. Sediment-water distribution coefficients (Kd) were quantified and were normalized to various sediment characteristics to assess the main driving force(s) for sorption of OD-PABA. Organic carbon content was found to be a main driving force, with organic carbon-normalized distribution coefficients (log Koc) ranging from 4.4 to 4.6 for sediments with total organic carbon (TOC) > 10%); the clay fraction was also found to be important, especially for sediments with low TOC. The sorption of para-aminobenzoic acid (PABA), a water-soluble analog of OD-PABA was also investigated to assess the experimental approach, yielding a log Koc of 2.1 for the sediment with the greatest TOC.

Molecular Insights of 5-Hydroxymethylfurfural in a Mixture of Ionic Liquids and Alkylated Phenolic Solvents.

This paper presents all-atom molecular dynamics to understand the separation behavior of 5-hydroxymethylfurfural (5-HMF) from 1-butyl-3-methylimidazolium tetrafluoroborate [BMIM]+[BF4]- using alkylated phenols as extractants. We have utilized four solvents such as 4-methyl phenol (4-MP), 4-ethyl phenol (4-EP), 4-propyl phenol (4-PP), and 4-butyl phenol (4-BP). We perform structural, dynamic, and rigorous thermodynamic analyses of 5-HMF in the mixture of ILs and solvents. The [BMIM]+[BF4]- show a strong interaction with phenols. The self-diffusion coefficient of 5-HMF shows a 3-fold increase with a decrease in the methyl group on the phenol. The solvation-free energy (ΔGsolvation) of 5-HMF shows favorably in phenols. On the other hand, the transfer free energy (ΔGtransfer) of 5-HMF presents favorable from ILs to phenols. The partition coefficient (log P) values show favorability for separation of 5-HMF using phenols. Overall, the molecular level analysis provides the role of the alkyl group effect on the phenols for extracting 5-HMF from the ILs.

Experimental and theoretical vibrational analysis, structural conformations, DFT estimations, antibacterial, antifungal, DPPH,H2O2, Nitric oxide scavenging activity drug, in silico molecular docking, and ADMET studies of N-(2-carboxylphenyl) phthalimide (CPPD)

The title compound N-(2-carboxylphenyl) phthalimide (CPPD)was purchased with a stated purity of 99 % from M/S. Sigma-Aldrich Co. and utilized as such with no additional purification,CPPD is a thalidomide based derivative, which have led to the uses of most important drugs from 1950 and their mechanisms of action is essential for a better understanding of molecular targets with broad spectrum of biological activity. The obtained FTIR spectral data of the compound were compared to harmonic vibrational frequencies calculated using the ab initio DFT (B3LYP) technique with 6–311++G (d,p)basis sets. Furthermore, 13C and 1H NMR, first-order hyperpolarizability (βo) associated parameters (π, αo)of the compound, theSubsequent to recording the molecule’sUV–Visible spectra, DFT was used to analyze its electronic characteristics, including its HOMO and LUMO energies, molecular electrostatic potential (MESP), and Mulliken population studies were using ab initio DFT6-311++G (d,p)basis sets. Pharmacological Screening investigation of the title molecule showed a strong broad-spectrum of antifungal and antibacterial activity against various Gram (+) and Gram (−) bacteria using Ciprofloxacin as a positive control. The headline molecule is subjected toIn-silico molecular docking research with the purpose of improved recognize its biological activities, in addition with the minimal binding energy and hydrogen bond interaction that can view by Discovery Studio 4.0 visualizers. and drug likeness using Swiss ADME predictor (http://www.swissadme.ch/index.php) along with AdmetSAR-2.0 online software analysis tools features were investigated. The compound CPPD’s ability to degrade DPPH increased as a dose-dependent manner, with its maximal DPPH scavenging characteristic spanning from (18.2 ± 1.5 % to 73.2 ± 1.7 %) and maximum H2O2 scavenging trait ranging from (35.5 ± 5.3to 88.8 ± 3.1 %). The NO free radical scavenging property is linearly dependent on CPPD concentration. The interaction between the CPPD ligands and the 1HD2 protein is demonstrated by these data, as the protein displays a reduced binding energy value of −7.3 (Kcal/mol) and an inhibitory constant (ki) value of 4.39 μM. In swiss ADME prediction, CPPD is an evident from the physicochemical data that has an efficient receptor site binding mechanism. The lipophilicity of a drug is determined by its partition coefficient (Log P=log Po/w) between water and N-(2-carboxylphenyl) phthalimide. The paper further explains that the title compound can act as promising antibacterial and antioxidant agent throughin-vitro and molecular docking studies.

Predicting the acute aquatic toxicity of organic UV filters used in cosmetic formulations.

Organic UV filters are commonly used in sunscreen and cosmetic formulations to protect against harmful UV radiation. However, concerns have emerged over their potential toxic effects on aquatic organisms. This study aims to investigate the acute aquatic toxicity of 13 organic UV filters and determine whether phospholipid binding, measured through biomimetic chromatographic methods, is a better predictor of toxicity than the traditionally used octanol-water partition coefficient (log P). The chromatographic retention of the 13 UV filters was measured on an immobilized artificial membrane (IAM) stationary phase to assess phospholipid binding. These measurements were then applied to previously established predictive models, originally developed for pharmaceutical compounds, to estimate acute aquatic toxicity endpoints of 48-hour LC50 for fish and the 48-hour EC50 (immobilization) for Daphnia magna. Phospholipid binding was found to be a more reliable predictor of the acute aquatic toxicity of UV filters compared to log P. The toxicity was primarily driven by lipophilicity and charge, with negatively charged compounds exhibiting lower toxicity. The study demonstrates that phospholipid binding is a better descriptor of UV filter toxicity than log P, providing a more accurate method for predicting the environmental risk of these compounds. This insight can guide the development of more environmentally friendly sunscreens by reducing the use of highly lipophilic and positively charged compounds, thus lowering their aquatic toxicity.

Gradient boosting decision tree algorithms for accelerating nanofiltration membrane design and discovery

Interfacial polymerization is the most widely used strategy for nanofiltration membrane fabrication. Despite extensive research on this technology, further improvement in permeance and salt rejection is still essential due to its multidimensional characteristics, including the types of membrane material and the conditions of membrane optimizing fabrication. Herein, we applied four gradient boosting decision tree algorithms to precisely identify the candidate monomers (represented by the molecular descriptors) and their fabrication conditions. The result of the model evaluation indicated the Extreme Gradient Boosting (XGBoost) algorithm had the best predictive performance in accuracy and generalization in predicting membrane permeance and salt rejection, with the corresponding determination coefficients on the test set being 0.76 and 0.88. Shapley additive explanation analysis showed that the aqueous monomer concentration was the most influential fabrication condition in membrane performance. Besides, the partition coefficient (Log P) and topological polar surface area were the most important molecular descriptors in water permeance and salt rejection, respectively. Overall, this study proposed innovative machine learning algorithms to disentangle the multidimensional interactions of various influencing factors on membrane performance, thus initiating a paradigm shift in the development of high-performance nanofiltration membranes.

Co-exposure to Organophosphate esters (OPEs) and Cadmium alleviated their accumulation in rice (Oryza sativa L.) by inhibiting transports' transcription

Combined contamination of Organophosphate esters (OPEs) and heavy metal has been concerning on their potential threaten to human health through food chain. In order to estimate effects of OPEs and heavy metal's combined contamination on crop, the growth of rice seedlings, pollutant accumulations and their involved in transcript regulation pathway under OPEs and Cd contamination were investigated. In results, only single OPEs pollution improved the biomass of rice, while single Cd pollution inhibited the growth of plants. Although the combined contaminations of OPEs and Cd also showed negative effect for plant growth, OPEs could alleviate the negative effect of Cd on rice. The Octanol-water partition coefficients (log Kow) of OPEs were positively correlated with root concentration factor (RCF) values in the trend line and negatively correlated with shoot concentration factor (SCRF) and translocation factor (TF). OPEs and Cd inferred with each other's accumulations in plants through reducing RCF, SCRF and TF. After addition of Cd, the expressions of OsTIL, OsLTP4, OsLTPL1, and OsMLP423 genes involved in OPEs accumulation were downregulated. Moreover, the presence of Cd also affected the binding sites and binding energy of the four proteins with OPEs. Meanwhile, the expression of OsNramp1, OsNramp5, OsHMA2, OsGS1, and OsPCS1 genes involved in Cd accumulation and toleration were also downregulated after addition of OPEs. These results suggested that OPEs and Cd directly repressed each other gene transcript involved in accumulation and toleration process.

Molecular simulation of understanding the structure and separation thermodynamics of BTX (Benzene, Toluene, Xylene) using amino acid based ionic liquids

The separation of aromatics and aliphatic from the hydrocarbon mixture stands a significant challenge. In this manuscript we present atomistic molecular dynamic simulations to understand the structure and separation thermodynamic properties of BTX (Benzene, toluene, xylene) from n-heptane using ionic liquids. Here we considered the amino acid derived ionic liquid considering the tetra butyl phosphonium as cation and valine anion at three different temperatures 298 K, 323 K and 348 K. We observe that IL show strong intermolecular structure with BEN (benzene) when compared to TOL (toluene) and XYL (p-xylene). Based on the solvation free energy (ΔGsolv), transfer free energy (ΔGtransfer) and partition coefficient (log P) analysis of BEN show favourable for the transfer from n-heptane to IL phase when compared to TOL and XYL. Overall results presented in this paper provide molecular level understanding of the design of amino acid-based IL for the separation BTX from the hydrocarbon mixture.