Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Ghosh, Subhasis" wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-3 z 3
    Tytuł:
    Bioavailability prediction of phytochemicals present in Calotropis procera (Aiton) R. Br. by using Swiss-ADME tool
    Autorzy:
    Tripathi, Puja
    Ghosh, Subhasis
    Talapatra, Soumendra Nath
    Powiązania:
    https://bibliotekanauki.pl/articles/1066215.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Bioavailability
    Calotropis procera
    Drug-likeness
    Medicinal chemistry
    Pharmacokinetics
    Phytocompounds
    Synthetic compounds
    Opis:
    The medicinal plant, Calotropis procera (Aiton) R. Br. is a common shrub and this plant has several phytochemicals that act as analgesic and anti-inflammatory agents. The aim of the present study was to detect bioavailability potential through absorption, distribution, metabolism and excretion (ADME) of phytocompounds established in C. procera plant parts. In silico study, especially pharmacokinetics, bioavailability, drug-likeness and medicinal chemistry friendliness prediction was performed by using the SwissADME online tool to know the lead phytocompound for the drug candidate for the prevention of pain and inflammation. The common established eleven phytocompounds such as Methyl myrisate, Methyl behenate, Anthocyanin, Uzarigenin, Lupeol, β-amyrin, α-amyrin, Uscharin, Calotropin, β-sitosterol and Quercetin-3-rutinoside as well as 2 synthetic anti-inflammatory medicines were selected for the present computational prediction. The predictions of pharmacokinetics, bioavailability, drug-likeness and medicinal chemistry friendliness obtained a suitable phytocompound Uzarigenin of C. procera, which showed resemblance with several parameters of Ibuprofen and the synthetic drug Ibuprofen is well-established analgesic and anti-inflammatory agent. In conclusion, the small molecule, Uzarigenin can be suitable drug candidate. Further study should be done by in vitro and in vivo assay for toxicology, pharmacology and experimental bioavailability for pain and inflammation reliving phytomedicine to confirm the present predictions.
    Źródło:
    World Scientific News; 2019, 131; 147-163
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    CellProfiler and WEKA Tools: Image Analysis for Fish Erythrocytes Shape and Machine Learning Model Algorithm Accuracy Prediction of Dataset
    Autorzy:
    Talapatra, Soumendra Nath
    Chaudhuri, Rupa
    Ghosh, Subhasis
    Powiązania:
    https://bibliotekanauki.pl/articles/1193348.pdf
    Data publikacji:
    2021
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Automatic image analysis
    CellProfiler tool
    Fish erythrocytes quantification
    Machine learning algorithm
    Model classifier accuracy
    Shapes measurement
    WEKA tool
    Opis:
    The first part of the study was detected the number of cells and measurement of shape of cells, cytoplasm, and nuclei in an image of Giemsa-stained of fish peripheral erythrocytes by using CellProfiler (CP, version 2.1.0) tool, an image analysis tool. In the second part, it was evaluated machine learning (ML) algorithm models viz. BayesNet (BN), NaiveBayes (NB), logistic regression (LR), Lazy.KStar (K*), decision tree (DT) J48, Random forest (RF) and Random tree (RT) in the WEKA tool (version 3.8.5) for the prediction of the accuracy of the dataset generated from an image. The CP predicts the numbers and individual cellular area shape (arbitrary unit) of cells, cytoplasm, and nuclei as primary, secondary, and tertiary object data in an image. The performance of model accuracy of studied ML algorithm classifications as per correctly and incorrectly classified instances, the highest values were observed in RF and RT followed by K*, LR, BN and DTJ48 and lowest in NB as per training and testing set of correctly classified instances. In case of performance accuracy of class for K value, the highest values were observed in RF and RT followed by K*, LR, BN and DTJ48 and lowest in NB while lowest values were obtained for mean absolute error (MAE) and root mean squared error (RMSE) in case of RT followed by RF, K*, LR, BN and DTJ48 and comparatively highest value in case of NB as per training and testing set. In conclusion, both tools performed well as an image to the dataset and obtained dataset to rich information through ML modelling and future study in WEKA tool can easily be analysed many biological big data to predict classifier accuracy.
    Źródło:
    World Scientific News; 2021, 154; 101-116
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    In silico study by using ProTox-II webserver for oral acute toxicity, organ toxicity, immunotoxicity, genetic toxicity endpoints, nuclear receptor signalling and stress response pathways of synthetic pyrethroids
    Autorzy:
    Ghosh, Subhasis
    Tripathi, Puja
    Talukdar, Partha
    Talapatra, Soumendra Nath
    Powiązania:
    https://bibliotekanauki.pl/articles/1065392.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    In silico study
    Molecular mechanism of toxicity
    Nuclear receptor signalling and stress response pathways
    Predictive toxicology
    Synthetic pyrethroids
    Opis:
    Till date, it is well-known that synthetic pyrethroids are safe to mammal but toxic to non-mammals. The present objective was an in silico study to detect oral acute toxicity, organ toxicity, immunotoxicity, genetic toxicity endpoints, nuclear receptor signalling, and stress response pathways of common synthetic pyrethroids by using ProTox-II webserver. The chemical compounds especially different synthetic pyrethroids such as pyrethrin I, Cinerin I and Jasmolin I (esters of Chrysanthemic acid), Pyrethrin-II, Cinerin II and Jasmolin II (Esters of Pyrethric acid), type I pyrethroids (esters without alpha-cyano group) such as allethrin, resmethrin, permethrin and bifenthrin and type II pyrethroids (esters with alpha-cyano group) such as fenvalerate, cyhalothrin, cypermethrin and deltamethrinwere selected from available literature. ProTox-II webserver was used for toxicological assessment in organism, organs, cell and gene level along with molecular mechanisms of toxicity. The predictive results for the toxicity of common synthetic pyrethroids compounds, Deltamethrin showed highly toxic compound among 14 compounds as fatal if swallowed as class II followed by Cypermethrin, Cyhalothrin, Bifenthrin, Resmethrin, Fenvalerate and Permethrin but hepatotoxic potential was only Deltamethrin and Fenvalerate while immunotoxic was obtained Permethrin. On the other hand, none of the compounds were obtained cytotoxic and carcinogenic but 9 compounds viz. Pyrethrin I, II Cinerin I, II, Jasmolin I, II, Allethrin, Resmethrin and Permethrin were observed mutagenic active. In case of NR signalling pathways, all compounds were inactive but eight compounds such as Pyrethrin I, II, Cinerin I, II, Jasmolin I, II, Allethrin and Resmethrin were obtained nrf2/ARE and HSE active while MMP active compounds were obtained Fenvalerate, Cyhalothrin and Deltamethrin respectively. For p53 and ATAD5 parameters, all fourteen compounds such as were obtained inactive. In conclusion, the present predictive results are suitable for academician, researchers, industries, etc. those who are making drugs and environmental chemicals. This web server helps faster screening of large numbers of compounds within short duration and no animal testing. This present in silico study easily detects toxin(s), which can be validated in future through in vitro and in vivo experimental assay.
    Źródło:
    World Scientific News; 2019, 132; 35-51
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies