Phyllanthus emblica (Amla) methanolic extract regulates multiple checkpoints in 15-lipoxygenase mediated inflammopathies: Computational simulation and in vitro evidence.

Amla (Phyllanthus emblica) has long been used in traditional folk medicine to prevent and cure a variety of inflammatory diseases. In this study, the antioxidant activity (DPPH scavenging and reducing power), anti-inflammatory activity (RBC Membrane Stabilization and 15-LOX inhibition), and anticoagulation activity (Serin protease inhibition and Prothrombin Time assays) of the methanolic extract of amla were conducted. Amla exhibited a substantial amount of phenolic content (TPC: 663.53 mg GAE/g) and flavonoid content (TFC: 418.89 mg GAE/g). A strong DPPH scavenging effect was observed with an IC50 of 311.31 µg/ml as compared to standard ascorbic acid with an IC50 of 130.53 µg/ml. In reducing power assay, the EC50 value of the extract was found to be 196.20 µg/ml compared to standard ascorbic acid (EC50 = 33.83 µg/ml). The IC50 value of the RBC membrane stabilization and 15-LOX assays was observed as 101.08 µg/ml (IC50 of 58.62 µg/ml for standard aspirin) and 195.98 µg/ml (IC50 of 19.62 µg/ml for standard quercetin), respectively. The extract also strongly inhibited serine protease (trypsin) activity with an IC50 of 505.81 µg/ml (IC50 of 295.44 µg/ml for standard quercetin). The blood coagulation time (PTT) was found to be 11.91 min for amla extract and 24.11 min for standard Warfarin. Thus, the findings of an in vitro study revealed that the methanolic extract of amla contains significant antioxidant, anti-inflammatory, and anticoagulation activity. Furthermore, in silico docking and simulation of reported phytochemicals of amla with human 15-LOXA and 15-LOXB were carried out to validate the anti-inflammatory activity of amla. In this analysis, epicatechin and catechin showed greater molecular interaction and were considerably stable throughout the 100 ns simulation with 15-lipoxygenase A (15-LOXA) and 15-lipoxygenase B (15-LOXB) respectively.

The impact of deontological and teleological variables on the intention to visit green hotel: The moderating role of trust.

Green hotels have grown in popularity due to customers' increased awareness of environmental issues. This study aims to construct and evaluate a model that combines the theory of Planned Behavior (TPB) and the theory of ethics to explain green hotel visitors' intentions and behavior. The study also considers the role of trust & subjective norms as a moderator. The framework of the study was evaluated using a quantitative method. Most of the respondents to the study, which was carried out in Noakhali, Bangladesh, were students at Noakhali Science and Technology University and their family members. The data was collected from 414 respondents and analyzed using the structural equation modeling (SEM) technique. The data collection took around two weeks, starting from December 3, 2021. According to the study's findings, the deontological (Moral obligation and justice) and teleological variables (perceived benefit and perceived risk) significantly influence green hotel visitors' intentions and actual behavior. Moreover, trust noticeably influences the relationship between subjective norm (SN) and Intention, and subjective norm affects the connection between attitude and intention. Therefore, hotel management can utilize this research to examine and understand visitors' intention and actual behavior to visit green hotels, which will assist them in attracting guests by portraying their services as eco-friendly. Furthermore, the findings may help hotel management formulate competitive marketing strategies, design effective promotional tools, and help generate an eco-conscious customer base.

Predicting multi-enzyme inhibition in the arachidonic acid metabolic network by Heritiera fomes extracts.

Heritiera fomes is a mangrove plant with a rich history of ethnomedicinal usage against chronic inflammation. Biochemical analyses of H. fomes have exposed a plethora of bioactive phytochemicals that contribute to this therapeutic effect by perturbing enzymes of a complex inflammatory network mediated by arachidonic acid (AA) metabolism. This study is the first instance of utilizing cheminformatic approaches to elucidate a molecular linkage between these phytochemical interventions and the multi-enzyme AA metabolic network regulation. Analysis of the simulations reflects H. fomes as a functional reservoir of multiple safe and potent natural anti-inflammatory compounds. The investigation suggests two phytocompounds extracted from the plant: a sesquiterpene lactone and a flavone glycoside, as candidate inhibitors of multiple catalytic checkpoints of the inflammatory network. The outcomes of this research act as a primary guideline for future laboratory and clinical testing of anti-inflammatory potentials of H. fomes as an exploitable source of safe and potent drug-like molecules.Communicated by Ramaswamy H. Sarma.

Marine phycocompound screening reveals a potential source of novel senotherapeutics.

Cells undergo a controlled and systematic cycle of growth, replication and death. However, the integrity of this process gradually declines, leading to accumulation of senescent cells, a major hallmark of biological ageing. Dietary algae, particularly marine algae, have been long reported to exert anti-ageing benefits as cosmeceuticals and nutraceuticals with limited understanding of the molecular mechanisms underlying their activity. In this study, we have incorporated 1,202 previously reported bioactive small phycocompounds and subjected them to cheminformatic queries to assess these interactions. In-silico ADMET, 2-phase docking, metabolic pathway interaction and molecular dynamics simulations reveal multiple marine phycocompounds to have safe and effective senolytic potentials. We employed a novel deep convolutional neural network driven screening approach to identify (2R*, 3S*, 6R*, 7S*, 10R*, 13R*)-7,13-Dihydroxy-2,6-cyclo-1(9),14-xenicadiene-18,19-dial derived from Dilophus Fasciola, Laurendecumenyne A from Laurencia decumbens and 4-Bromo-3-ethyl-9-[(2E)-2-penten-4-yn-1-yl]-2,8-dioxabicyclo[5.2.1]decan-6-ol from Laurencia sp. to be potent inhibitors of multiple target senescent-cell anti-apoptotic pathway proteins. We simulated the best overall target inhibitors, specific protein inhibitors and molecular pathway regulators with each target protein and found stable interactions with minimum deviations (mean RMSD = 0.17 ± 0.01 nm) and gyrations (mean Rg = 1.64 ± 0.16 nm) of the simulated protein-compound complexes. Finally, molecular mechanics calculation suggests potent (mean ΔG = -69.56 ± 27.19 kCal/mol) and frequent hydrophobic interactions between the top performing marine phycocompounds and target proteins.

Generalized Pruritus and Gradual Loss of Vision as the Presenting Complaints of Acute HIV Infection: Management Challenges during COVID-19 Pandemic.

BACKGROUND: Although the prevalence of HIV is low in Bangladesh, there is a potential for an increased number of cases. This is because of high cross-border mobility (India and Myanmar) of people and increased injection drug abusers amongst youth in the cities and rural areas, HIV can present in many ways, from asymptomatic to advanced disease, including various atypical (generalized itching) and advanced (loss of vision) manifestations. A high degree of suspicion is required to diagnose HIV in a country like Bangladesh. Early diagnosis and prompt treatment are essential to have a better outcome. METHODS: Here, we report two thought-provoking cases where patients were suffering from generalized itchy lesions (pruritic papular eruption) throughout the body for a long time and gradual loss of vision in another case. RESULTS: Due to lack of suspicion, initially, HIV screening was not done. Both patients visited several health centres, but no diagnosis was made. Moreover, COVID-19 pandemic worsens the situation. Finally, they were diagnosed with HIV; unfortunately, one of them lost her vision due to CMV retinitis and another patient died of other complications. CONCLUSION: Ongoing COVID-19 pandemic put many challenges to ensure optimum care, especially for patients with long-sufferings like HIV. Clinicians have to have a very high degree of suspicion while dealing with patients presented with rare manifestations, particularly in a low endemic clinical setting.

Anti-MRSA activity of oxysporone and xylitol from the endophytic fungus Pestalotia sp. growing on the Sundarbans mangrove plant Heritiera fomes.

Heritiera fomes Buch.-Ham., a mangrove plant from the Sundarbans, has adapted to a unique habitat, muddy saline water, anaerobic soil, brackish tidal activities, and high microbial competition. Endophytic fungal association protects this plant from adverse environmental conditions. This plant is used in Bangladeshi folk medicine, but it has not been extensively studied phytochemically, and there is hardly any report on investigation on endophytic fungi growing on this plant. In this study, endophytic fungi were isolated from the surface sterilized cladodes and leaves of H. fomes. The antimicrobial activities were evaluated against two Gram-positive and two Gram-negative bacteria and the fungal strain, Candida albicans. Extracts of Pestalotia sp. showed activities against all test bacterial strains, except that the ethyl acetate extract was inactive against Escherichia coli. The structures of the purified compounds, oxysporone and xylitol, were elucidated by spectroscopic means. The anti-MRSA potential of the isolated compounds were determined against various MRSA strains, that is, ATCC 25923, SA-1199B, RN4220, XU212, EMRSA-15, and EMRSA-16, with minimum inhibitory concentration values ranging from 32 to 128 µg/ml. This paper, for the first time, reports on the anti-MRSA property of oxysporone and xylitol, isolation of the endophyte Pestalotia sp. from H. fomes, and isolation of xylitol from a Pestalotia sp.

A new statistical detector for DWT-based additive image watermarking using the Gauss-hermite expansion.

Traditional statistical detectors of the discrete wavelet transform (DWT)-based image watermarking use probability density functions (PDFs) that show inadequate matching with the empirical PDF of image coefficients in view of the fact that they use a fixed number of parameters. Hence, the decision values obtained from the estimated thresholds of these detectors provide substandard detection performance. In this paper, a new detector is proposed for the DWT-based additive image watermarking, wherein a PDF based on the Gauss-Hermite expansion is used, in view of the fact that this PDF provides a better statistical match to the empirical PDF by utilizing an appropriate number of parameters estimated from higher-order moments of the image coefficients. The decision threshold and the receiver operating characteristics are derived for the proposed detector. Experimental results on test images demonstrate that the proposed watermark detector performs better than other standard detectors such as the Gaussian and generalized Gaussian (GG), in terms of the probabilities of detection and false alarm as well as the efficacy. It is also shown that detection performance of the proposed detector is more robust than the competitive GG detector in the case of compression, additive white Gaussian noise, filtering, or geometric attack.

Bayesian wavelet-based image denoising using the Gauss-Hermite expansion.

The probability density functions (PDFs) of the wavelet coefficients play a key role in many wavelet-based image processing algorithms, such as denoising. The conventional PDFs usually have a limited number of parameters that are calculated from the first few moments only. Consequently, such PDFs cannot be made to fit very well with the empirical PDF of the wavelet coefficients of an image. As a result, the shrinkage function utilizing any of these density functions provides a substandard denoising performance. In order for the probabilistic model of the image wavelet coefficients to be able to incorporate an appropriate number of parameters that are dependent on the higher order moments, a PDF using a series expansion in terms of the Hermite polynomials that are orthogonal with respect to the standard Gaussian weight function, is introduced. A modification in the series function is introduced so that only a finite number of terms can be used to model the image wavelet coefficients, ensuring at the same time the resulting PDF to be non-negative. It is shown that the proposed PDF matches the empirical one better than some of the standard ones, such as the generalized Gaussian or Bessel K-form PDF. A Bayesian image denoising technique is then proposed, wherein the new PDF is exploited to statistically model the subband as well as the local neighboring image wavelet coefficients. Experimental results on several test images demonstrate that the proposed denoising method, both in the subband-adaptive and locally adaptive conditions, provides a performance better than that of most of the methods that use PDFs with limited number of parameters.