9 research outputs found

    ANTIBACTERIAL ACTIVITY OF POLYSCIAS SCUTELLARIA FOSBERG AGAINST ACINETOBACTER SP.

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    Objective: Polyscias scutellaria Fosberg as one of the indigenous plants from Indonesia has been used as traditional medicines for several ailments, such as reduce body odor. However, there is no scientific research to verify this property. This study aimed to evaluate the antibacterial activity of P. scutellaria Fosberg against bacteria that cause body odor.Methods: Since body odor is caused by activities of bacteria that live in the armpits, bacteria from human armpit were isolated and identified as Acinetobacter sp. The bacteria have the potential to be pathogenic and resistant to common antibiotics. P. scutellaria was extracted using different solvents, i.e., hexane, ethyl acetate, and methanol. Using these extracts, the antibacterial activity of P. scutellaria against Acinetobacter sp. was tested through well diffusion and colony-forming unit methods.Results: Hexane and ethyl acetate fractions of P. scutellaria extract showed strong antibacterial activities against Acinetobacter sp., while methanol fraction did not exhibit any antibacterial activity against these bacteria.Conclusion: P. scutellaria extract has the potential to be used as an antibacterial agent against Acinetobacter sp. on human armpit

    Predictors of SARS-CoV-2 Omicron breakthrough infection after receipt of AZD7442 (tixagevimab-cilgavimab) for pre-exposure prophylaxis among hematologic malignancy patients

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    AZD7442 (tixagevimab-cilgavimab) is a combination of two human monoclonal antibodies for pre-exposure prophylaxis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among high-risk patients who do not mount a reliable vaccine response. Foremost among these are hematologic malignancy patients with limited clinical trial or realworld experience to assess the effectiveness of this combination treatment since the emergence of Omicron and its subvariants. We performed a retrospective study of 892 high-risk hematologic malignancy patients who received AZD7442 at Memorial Sloan Kettering Cancer Center in New York City from January 1, 2022 to July 31, 2022. We evaluated demographic, clinical, and laboratory characteristics and performed regression analyses to evaluate risk factors for breakthrough infection. We also evaluated the impact of updated AZD7442 dosing regimens on the risk of breakthrough infection. Among 892 patients, 98 (10.9%) had a breakthrough infection during the study period. A majority received early outpatient treatment (82%) and eventually eight (8.2%) required hospitalization for management of Coronavirus Disease 2019 (COVID-19), with a single instance of severe COVID-19 and death. Patients who received a repeat dose or a higher firsttime dose of AZD7442 had a lower incidence of breakthrough infection. Univariate analyses did not reveal any significant predictors of breakthrough infection. While AZD7442 is effective at reducing SARS-CoV-2 breakthrough infection in patients with hematologic malignancies, no risk factors reliably predicted risk of infection. Patients who received updated dosing regimens as per Food and Drug Administration guidelines had better protection against breakthrough infection

    AI is a viable alternative to high throughput screening: a 318-target study

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    : High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

    In-vitro and in-silico analyses of the thrombolytic potential of green kiwifruit

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    Abstract Cardiovascular diseases (CVDs), mainly caused by thrombosis complications, are the leading cause of mortality worldwide, making the development of alternative treatments highly desirable. In this study, the thrombolytic potential of green kiwifruit (Actinidia deliciosa cultivar Hayward) was assessed using in-vitro and in-silico approaches. The crude green kiwifruit extract demonstrated the ability to reduce blood clots significantly by 73.0 ± 1.12% (P < 0.01) within 6 h, with rapid degradation of Aα and Bβ fibrin chains followed by the γ chain in fibrinolytic assays. Molecular docking revealed six favorable conformations for the kiwifruit enzyme actinidin (ADHact) and fibrin chains, supported by spontaneous binding energies and distances. Moreover, molecular dynamics simulation confirmed the binding stability of the complexes of these conformations, as indicated by the stable binding affinity, high number of hydrogen bonds, and consistent distances between the catalytic residue Cys25 of ADHact and the peptide bond. The better overall binding affinity of ADHact to fibrin chains Aα and Bβ may contribute to their faster degradation, supporting the fibrinolytic results. In conclusion, this study demonstrated the thrombolytic potential of the green kiwifruit-derived enzyme and highlighted its potential role as a natural plant-based prophylactic and therapeutic agent for CVDs

    Reproducibility of fluorescent expression from engineered biological constructs in E. coli

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    We present results of the first large-scale interlaboratory study carried out in synthetic biology, as part of the 2014 and 2015 International Genetically Engineered Machine (iGEM) competitions. Participants at 88 institutions around the world measured fluorescence from three engineered constitutive constructs in E. coli. Few participants were able to measure absolute fluorescence, so data was analyzed in terms of ratios. Precision was strongly related to fluorescent strength, ranging from 1.54-fold standard deviation for the ratio between strong promoters to 5.75-fold for the ratio between the strongest and weakest promoter, and while host strain did not affect expression ratios, choice of instrument did. This result shows that high quantitative precision and reproducibility of results is possible, while at the same time indicating areas needing improved laboratory practices.Peer reviewe
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