Formulations of synergistic microbial consortia for enhanced systemic resistance against Fusarium wilt in cumin.

The study aimed to understand the dynamic interplay between plants and their associated microbes to develop an efficient microbial consortium for managing Fusarium wilt of cumin. A total of 601 rhizospheric and endophytic bacteria and fungi were screened for antagonistic activity against Fusarium oxysporum f.sp. cumini (Foc). Subsequently, ten bacteria and ten fungi were selected for characterizing their growth promotion traits and ability to withstand abiotic stress. Furthermore, a pot experiment was conducted to evaluate the bioefficacy of promising biocontrol isolates-1F, 16B, 31B, and 223B in mono and consortium mode, focusing on disease severity, plant growth, and defense responses in cumin challenged with Foc. Promising isolates were identified as Trichoderma atrobruneum 15F, Pseudomonas sp. 2B, Bacillus amyloliquefaciens 9B, and Bacillus velezensis 32B. In planta, results revealed that cumin plants treated with consortia of 15F, 2B, 9B, and 32B showed highest percent disease control (76.35%) in pot experiment. Consortia of biocontrol agents significantly enhanced production of secondary metabolites and activation of antioxidant-defense enzymes compared to individual strain. Moreover, consortium treatments effectively reduced electrolyte leakage over the individual strain and positive control. The four-microbe consortium significantly enhanced chlorophyll (~ 2.74-fold), carotenoid content (~ 2.14-fold), plant height (~ 1.8-fold), dry weight (~ 1.96-fold), and seed yield (~ 19-fold) compared to positive control in pot experiment. Similarly, four microbe consortia showed highest percent disease control (72.2%) over the positive control in field trial. Moreover, plant growth, biomass, yield, and yield attributes of cumin were also significantly increased in field trial over the positive control as well as negative control.

Scaling of soil organic carbon in space and time in the Southern Coastal Plain, USA.

Soil organic carbon (SOC) is a dynamic soil property (DSP) that represents the largest portion of terrestrial carbon. Its relevance to carbon sequestration and the potential effects of land use on SOC storage, make it imperative to map across both space and time. Most regional-scale studies mapping SOC give static estimates and train different models for different periods with varying accuracies. We developed a flexible modeling approach called DSP-Scale to map SOC in both space and time. DSP-Scale uses ecological concepts and empirical data to predict DSP dynamics using inherent soil properties (static factors) and land cover changes (dynamic factors). We compiled SOC data for the 0-20 cm depth (SOC20) from 1441 points spanning a 25 million ha study area in the southeastern U.S. Coastal Plain, incorporating data from the Rapid Carbon Assessment, National Cooperative Soil Survey Soil Characterization database, and other regional studies. We developed a random forest model using climate, topography, soil survey, and land cover changes to predict SOC20 dynamics for five-year periods between 2001 and 2019. Our model explained 66 % and 59 % of the variation for the training and test data, respectively. Top predictors included mean annual precipitation, slope, and soil erosion class. Land cover 10 years before measurements of SOC20 was more important than current land cover for estimating SOC20. We estimated total SOC stocks of 207.1 and 208.3 Tg for 2001 and 2019, respectively. Highest gains of total SOC stock (0.9 Tg from 2001 to 2019) were associated with land cover change from mixed to evergreen forest. The greatest loss of total SOC stock (0.2 Tg) in the same period was associated with land cover change from pasture/hay to evergreen forest. We concluded that the DSP-Scale approach provides a flexible way to use dynamic and static factors affecting SOC stocks to predict changes in space and time at regional scales.

Quinoxalinone substituted pyrrolizine (4h)-induced dual inhibition of AKT and ERK instigates apoptosis in breast and colorectal cancer by modulating mitochondrial membrane potential.

AKT and ERK 1/2 play a pivotal role in cancer cell survival, proliferation, migration, and angiogenesis. Therefore, AKT and ERK 1/2 are considered crucial targets for cancer intervention. In this study, we envisaged the role of AKT and ERK signaling in apoptosis regulation in presence of compound 4h, a novel synthetic derivative of quinoxalinone substituted spiropyrrolizines exhibiting substantial antiproliferative activity in various cancer cell lines. Structurally 4h is a spiropyrrolizine derivative. Molecular docking analysis revealed that compound 4h shows strong binding affinity with AKT-1 (-9.5 kcal/mol) and ERK2 (-9.0 kcal/mol) via binding at allosteric sites of AKT and active site of ERK2. The implications of 4h binding with these two survival kinases resulted in the obstruction for ATP binding, hence, hampering their phosphorylation dependent activation. We demonstrate that 4h mediated apoptotic induction via disruption in the mitochondrial membrane potential of MCF-7 and HCT-116 cells and 4h-mediated inhibition of survival pathways occurred in a wild type PTEN background and is diminished in PTEN-/- cells. In 4T1 mammary carcinoma model, 4h exhibited pronounced reduction in the tumor size and tumor volume at significantly low doses. Besides, 4h reached the highest plasma concentration of 5.8 µM within a period of 1 h in mice model intraperitoneally. Furthermore, 4h showed acceptable clearance with an adequate elimination half-life and satisfactory pharmacokinetic behaviour, thus proclaiming as a potential lead molecule against breast and colorectal cancer by specifically inhibiting simultaneously AKT and ERK1/2 kinases.

An embedded element based 2D finite element model for the strength prediction of mineralized collagen fibril using Monte-Carlo type of simulations.

A computationally efficient statistical model for the prediction of the strength of mineralized collagen fibril (a basic building block of bone) is presented by taking into account the uncertainties associated with the geometrical and material parameters of collagen and mineral phases. The mineral plates have been considered as one-dimensional bar elements embedded in the two-dimensional plane stress collagen matrix. The mineral phase is considered as linear elastic and a hyperelastic material model is adopted for the collagen phase. Further, the crack initiation and propagation in the collagen phase have been modeled using a damage plasticity approach. Different realizations of the arrangement of mineral plates have been generated to account for the associated geometrical uncertainties using an in-house MATLAB® code. Monte-Carlo type simulations have been performed on the different realizations of mineralized collagen fibril to predict its characteristic stress-strain response under tensile load. The characteristic strength of 3.64 GPa is obtained for mineralized collagen fibril using Weibull's analysis which is found to be in agreement with the molecular dynamics simulation data and numerical studies reported in the past. A parameter sensitivity analysis concluded that mineral modulus has a significant effect on the overall tangent modulus of mineralized collagen fibril in large strain regime.

Fuzzy reinforcement learning based intelligent classifier for power transformer faults.

In this work a fuzzy reinforcement learning (RL) based intelligent classifier for power transformer incipient faults is proposed. Fault classifiers proposed till date have low identification accuracy and do not identify all types of transformer faults. Herein, an attempt has been made to design an adaptive, intelligent transformer fault classifier that progressively learns to identify faults on-line with high accuracy for all fault types. In the proposed approach, dissolved gas analysis (DGA) data of oil samples collected from real power transformers (and from credible sources) has been used, which serves as input to a fuzzy RL based classifier. Typically, classification accuracy is heavily dependent on the number of input variables chosen. This has been resolved by using the J48 algorithm to select 8 most appropriate input variables from the 24 variables obtained using DGA. Proposed fuzzy RL approach achieves a fault identification accuracy of 99.7%, which is significantly higher than other contemporary soft computing based identifiers. Experimental results and comparison with other state-of-the-art approaches, highlights superiority and efficacy of the proposed fuzzy RL technique for transformer fault classification.

Monte Carlo Type Simulations of Mineralized Collagen Fibril Based on Two Scale Asymptotic Homogenization.

A multiscale model for mineralized collagen fibril (MCF) is proposed by taking into account the uncertainties associated with the geometrical properties of the mineral phase and its distribution in the organic matrix. The asymptotic homogenization approach along with periodic boundary conditions has been used to derive the effective elastic moduli of bone's nanostructure at two hierarchical length scales, namely: microfibril (MF) and MCF. The uncertainties associated with the mineral plates have been directly included in the finite element mesh by randomly varying their sizes and structural arrangements. A total of 100 realizations for the MCF model with random distribution have been generated using an in-house MATLAB code, and Monte Carlo type of simulations have been performed under tension load to obtain the statistical equivalent modulus. The deformation response has been studied in both small (≤10%) and large (≥10%) strain regimes. The stress transformation mechanism has also been explored in MF which showed stress relaxation in the organic phase upon different stages of mineralization. The elastic moduli for MF under small and large strains have been obtained as 1.88 and 6.102 GPa, respectively, and have been used as an input for the upper scale homogenization procedure. Finally, the characteristic longitudinal moduli of the MCF in the small and large strain regimes are obtained as 4.08 ± 0.062 and 12.93 ± 0.148 GPa, respectively. All the results are in good agreement to those obtained from previous experiments and molecular dynamics (MD) simulations in the literature with a significant reduction in the computational cost.

Fuzzy Lyapunov Reinforcement Learning for Non Linear Systems.

We propose a fuzzy reinforcement learning (RL) based controller that generates a stable control action by lyapunov constraining fuzzy linguistic rules. In particular, we attempt at lyapunov constraining the consequent part of fuzzy rules in a fuzzy RL setup. Ours is a first attempt at designing a linguistic RL controller with lyapunov constrained fuzzy consequents to progressively learn a stable optimal policy. The proposed controller does not need system model or desired response and can effectively handle disturbances in continuous state-action space problems. Proposed controller has been employed on the benchmark Inverted Pendulum (IP) and Rotational/Translational Proof-Mass Actuator (RTAC) control problems (with and without disturbances). Simulation results and comparison against a) baseline fuzzy Q learning, b) Lyapunov theory based Actor-Critic, and c) Lyapunov theory based Markov game controller, elucidate stability and viability of the proposed control scheme.

Role of dental restoration materials in oral mucosal lichenoid lesions.

BACKGROUND: Dental restorative materials containing silver-mercury compounds have been known to induce oral lichenoid lesions. OBJECTIVES: To determine the frequency of contact allergy to dental restoration materials in patients with oral lichenoid lesions and to study the effect of removal of the materials on the lesions. RESULTS: Forty-five patients were recruited in three groups of 15 each: Group A (lesions in close contact with dental materials), Group B (lesions extending 1 cm beyond the area of contact) and Group C (no topographic relationship). Thirty controls were recruited in two groups of 15 individuals each: Group D (oral lichenoid lesions but no dental material) and Group E (dental material but no oral lichenoid lesions). Patch tests were positive in 20 (44.5%) patients. Mercury was the most common allergen to elicit a positive reaction in eight patients, followed by nickel (7), palladium (5), potassium dichromate (3), balsam of Peru, gold sodium thiosulphate 2 and tinuvin (2) and eugenol (1), cobalt chloride (1) and carvone (1). Seven patients elicited positive response to more than one allergen. In 13 of 20 patients who consented to removal of the dental material, complete healing was observed in 6 (30%), marked improvement in 7 (35%) and no improvement in 7 (35%) patients. Relief of symptoms was usually observed 3 months after removal. LIMITATIONS: Limited number of study subjects and short follow up after removal/replacement of dental restoration materials are the main limitations of this study. CONCLUSION: Contact allergy to amalgam is an important etiologic factor in oral lichenoid lesions and removal of restorative material should be offered to patients who have lesions in close proximity to the dental material.

Extraintestinal manifestations of idiopathic ulcerative colitis in northwestern India.

OBJECTIVE: To determine the frequency of extraintestinal manifestations in patients with idiopathic ulcerative colitis. METHODS: 46 patients underwent detailed clinical, biochemical and radiological evaluation. RESULTS: One patient (2%) had peripheral arthritis and two patients (4%) had ocular involvement in the form of anterior uveitis. No patient had mucocutaneous, vascular, or hepatobiliary manifestations, or sacroiliitis. CONCLUSIONS: The frequency of extraintestinal manifestations in patients with IUC in northwestern India is low.