Potential of formulated Dyadobacter jiangsuensis strain 12851 for enhanced bioremediation of chlorpyrifos contaminated soil.

Chlorpyrifos (O, O-diethyl O-3, 5, 6-trichloropyridin-2-yl phosphorothioate) is a toxic and chlorinated organic contaminant in soils across the globe. The present study examines the chlorpyrifos (CP) degrading potential of gram-negative bacterium Dyadobacter jiangsuensis (MTCC 12851), to be a promising and sustainable remedial approach. The proliferation of D. jiangsuensis in the chlorpyrifos spiked minimal salt media indicated the ability of this strain to utilize CP as a sole carbon source and also confirmed the utilization of 3,5,6- trichloro-2-pyridinyl (TCP) through silver nitrate assay. The strain 12851 degraded 80.36% and 76.93% chlorpyrifos (CP) in aqueous medium and soil environment, respectively. The water dispersible granules (WDG) of 45% (v/w) inoculum (bacterial suspension) were developed using talcum powder, acacia gum and alginic acid as key ingredients. The formulated strain (12851) achieved 21.13% enhanced CP degradation in soil under microcosm condition as compared to the unformulated one on 15th day of the treatment. The intermediate metabolites namely 3,5,6-trichloro-2-pyridinol (TCP), tetrahydropyridine, thiophosphate and phenol, 1, 3-bis (1,1-dimethylethyl) were detected during the CP degradation. The current investigation reveals D. jiangsuensis as a potential microbe for CP degradation and opens up the possibility of exploiting its formulations to remediate the CP polluted soils.

Enhancing hexahydro-1, 3, 5-trinitro-1, 3, 5-triazine (RDX) remediation through water-dispersible Microbacterium esteraromaticum granules.

In the current manuscript, we explored the remediation potential of Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) by Gram-positive Microbacterium esteraromaticum 12849. The strain detoxified 70.9 and 63.93% RDX in minimal nutrient medium and soil, respectively. Subsequently, the strain 12849 was formulated in form of water-dispersible granules (WDG) using talcum powder and alginic acid as inert ingredients. During the microcosm study, WDG exhibited 8.98% enhanced RDX degradation in contrast to the unformulated Microbacterium esteraromaticum. The LC-MS analysis revealed the presence of two intermediates, namely N-methyl-N, N'-dinitromethanediamine, and methylenedintramine, during the RDX degradation by strain 12849 in soil. Interestingly, no significant difference was observed in the rate of RDX degradation by strain 12849 due to the formulation process. The first-order kinetics was seen in RDX degradation with a degradation coefficient of 0.04 and 0.0339 day-1 by formulated and unformulated strain, respectively. The current investigation implies M. esteraromaticum as a potential microbe for RDX degradation and opens up the possibility of exploiting it in its effective WDG form for explosive contaminated sites.

Effect of non-surgical periodontal therapy on salivary and gingival crevicular fluid concentration of visfatin in periodontal health and disease.

Background and objective: Visfatin, a pleotropic mediator mostly produced by visceral fat, is crucial in controlling the immunological and defensive systems. It serves the roles of a cytokine, an enzyme involved in energy metabolism, and a growth factor. The objective of the present study was to assess the impact of non-surgical periodontal therapy (scaling and root planing) on visfatin concentrations in saliva and gingival crevicular fluid in individuals with Periodontitis (stage-II grade-A). Materials and methods: 54 individuals were divided into Group A (Periodontally Healthy) and Group B1(Periodontitis baseline) based on periodontal parameters including plaque index (PI), gingival index (GI), probing pocket depth (PPD), clinical attachment level (CAL), and radiographic parameters. After NSPT (SRP), Group B1 patients were recalled after 4 weeks, constituting Group B2 (post NSPT group B1). At baseline and 4 weeks after non-surgical periodontal therapy (SRP), all clinical parameters, salivary and GCF samples were recorded. An ELISA kit was used to measure the levels of visfatin. Using the paired t-test, unpaired t-test, and Pearson's correlation coefficient, data were analysed using SPSS 15. Results: After non-surgical periodontal treatment (SRP), the mean salivary and gingival crevicular fluid concentration of visfatin considerably decreased to a level comparable to periodontal health. In all groups, GCF visfatin concentration was higher than salivary concentration of visfatin. In periodontitis patients, visfatin concentration in GCF was 1.5 times higher than in saliva. Conclusion: The results of this investigation suggest a direct correlation between salivary and gingival crevicular fluid visfatin concentration and periodontal tissue inflammation and disease activity.

Machine Learning-Driven Discovery of Key Descriptors for CO2 Activation over Two-Dimensional Transition Metal Carbides and Nitrides.

Fusing high-throughput quantum mechanical screening techniques with modern artificial intelligence strategies is among the most fundamental ─yet revolutionary─ science activities, capable of opening new horizons in catalyst discovery. Here, we apply this strategy to the process of finding appropriate key descriptors for CO2 activation over two-dimensional transition metal (TM) carbides/nitrides (MXenes). Various machine learning (ML) models are developed to screen over 114 pure and defective MXenes, where the random forest regressor (RFR) ML scheme exhibits the best predictive performance for the CO2 adsorption energy, with a mean absolute error ± standard deviation of 0.16 ± 0.01 and 0.42 ± 0.06 eV for training and test data sets, respectively. Feature importance analysis revealed d-band center (εd), surface metal electronegativity (χM), and valence electron number of metal atoms (MV) as key descriptors for CO2 activation. These findings furnish a fundamental basis for designing novel MXene-based catalysts through the prediction of potential indicators for CO2 activation and their posterior usage.

Metadynamics-based enhanced sampling protocol for virtual screening: case study for 3CLpro protein for SARS-CoV-2.

In recent times, computational methods played an important role in the down selection of chemical compounds, which could be a potential drug candidate with a high affinity to target proteins. However, the screening methodologies, including docking, often fails to identify the most effective compound, which could be a ligand for the target protein. To solve that, here we have integrated meta-dynamics, an enhanced sampling molecular simulation method, with all-atom molecular dynamics to determine a specific compound that could target the main protease of novel severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). This combined computational approach uses the enhanced sampling to explore the free energy surface associated with the protein's binding site (including the ligand) in an explicit solvent. We have implemented this method to find new chemical entities that exhibit high specificity of binding to the 3-chymotrypsin-like cysteine protease (3CLpro) present in the SARS-CoV-2 and segregated to the most strongly bound ligands based on free energy and scoring functions (defined and implemented) from a set of 17 ligands which were prescreened for synthesizability and druggability. Additionally, we have compared these 17 ligands' affinities against controls, N3 and 13b α-ketoamide inhibitors, for which experimental crystal structures are available. Based on our results and analysis from the combined molecular simulation approach, we could identify the best compound which could be further taken as a potential candidate for experimental validation.Communicated by Ramaswamy H. Sarma.