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Wyświetlanie 1-3 z 3
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
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:
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
    Wyświetlanie 1-3 z 3

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