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  1. Article ; Online: Current Trends and Future Approaches in Small-Molecule Therapeutics for COVID-19.

    Laws, Mark / Surani, Yasmin M / Hasan, Md Mahbub / Chen, Yiyuan / Jin, Peiqin / Al-Adhami, Taha / Chowdhury, Madiha / Imran, Aqeel / Psaltis, Ioannis / Jamshidi, Shirin / Nahar, Kazi S / Rahman, Khondaker Miraz

    Current medicinal chemistry

    2020  Volume 28, Issue 19, Page(s) 3803–3824

    Abstract: The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is ... ...

    Abstract The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is likely to takes at least 12-18 months to develop a new vaccine. Therefore, there is an urgent need to find new therapeutics that can be progressed to clinical development as soon as possible. Repurposing regulatory agency-approved drugs and experimental drugs with known safety profiles can provide important repositories of compounds that can be fast-tracked to clinical development. Globally, over 500 clinical trials involving repurposed drugs have been registered, and over 150 have been initiated, including some backed by the World Health Organisation (WHO). This review is intended as a guide to research into small-molecule therapies to treat COVID-19; it discusses the SARS-CoV-2 infection cycle and identifies promising viral therapeutic targets, reports on a number of promising pre-approved small-molecule drugs with reference to over 150 clinical trials worldwide, and offers a perspective on the future of the field.
    MeSH term(s) Antiviral Agents/therapeutic use ; COVID-19 ; Drug Repositioning ; Humans ; Pandemics ; SARS-CoV-2
    Chemical Substances Antiviral Agents
    Keywords covid19
    Language English
    Publishing date 2020-07-22
    Publishing country United Arab Emirates
    Document type Journal Article ; Review
    ZDB-ID 1319315-6
    ISSN 1875-533X ; 0929-8673
    ISSN (online) 1875-533X
    ISSN 0929-8673
    DOI 10.2174/0929867327666200721161840
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Detection of COVID-19 Disease from Chest X-Ray Images: A Deep Transfer Learning Framework

    Sakib, Shadman / Siddique, Md. Abu Bakr / Khan, Mohammad Mahmudur Rahman / Yasmin, Nowrin / Aziz, Anas / Chowdhury, Madiha / Tasawar, Ihtyaz Kader

    medRxiv

    Abstract: The world economy as well as public health have been facing a devastating effect caused by the disease termed Coronavirus (COVID-19). A significant step of COVID-19 affected patient9s treatment is the faster and accurate detection of the disease which is ...

    Abstract The world economy as well as public health have been facing a devastating effect caused by the disease termed Coronavirus (COVID-19). A significant step of COVID-19 affected patient9s treatment is the faster and accurate detection of the disease which is the motivation of this study. In this paper, the implementation of a deep transfer learning-based framework using a pre-trained network (ResNet-50) for detecting COVID-19 from the chest X-rays was done. Our dataset consists of 2905 chest X-ray images of three categories: COVID-19 affected (219 cases), Viral Pneumonia affected (1345 cases), and Normal Chest X-rays (1341 cases). The implemented neural network demonstrates significant performance in classifying the cases with an overall accuracy of 96%. Most importantly, the model has shown significantly good performance over the current research-based methods in detecting the COVID-19 cases in the test dataset (Precision = 1.00, Recall = 1.00, F1-score = 1.00, and Specificity = 1.00). Therefore, our proposed approach can be adapted as a reliable method for faster and accurate COVID-19 affected case detection.
    Keywords covid19
    Language English
    Publishing date 2020-11-12
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.11.08.20227819
    Database COVID19

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  3. Book ; Online: Deep Convolutional Neural Networks Model-based Brain Tumor Detection in Brain MRI Images

    Siddique, Md. Abu Bakr / Sakib, Shadman / Khan, Mohammad Mahmudur Rahman / Tanzeem, Abyaz Kader / Chowdhury, Madiha / Yasmin, Nowrin

    2020  

    Abstract: Diagnosing Brain Tumor with the aid of Magnetic Resonance Imaging (MRI) has gained enormous prominence over the years, primarily in the field of medical science. Detection and/or partitioning of brain tumors solely with the aid of MR imaging is achieved ... ...

    Abstract Diagnosing Brain Tumor with the aid of Magnetic Resonance Imaging (MRI) has gained enormous prominence over the years, primarily in the field of medical science. Detection and/or partitioning of brain tumors solely with the aid of MR imaging is achieved at the cost of immense time and effort and demands a lot of expertise from engaged personnel. This substantiates the necessity of fabricating an autonomous model brain tumor diagnosis. Our work involves implementing a deep convolutional neural network (DCNN) for diagnosing brain tumors from MR images. The dataset used in this paper consists of 253 brain MR images where 155 images are reported to have tumors. Our model can single out the MR images with tumors with an overall accuracy of 96%. The model outperformed the existing conventional methods for the diagnosis of brain tumor in the test dataset (Precision = 0.93, Sensitivity = 1.00, and F1-score = 0.97). Moreover, the proposed model's average precision-recall score is 0.93, Cohen's Kappa 0.91, and AUC 0.95. Therefore, the proposed model can help clinical experts verify whether the patient has a brain tumor and, consequently, accelerate the treatment procedure.

    Comment: 4th International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC 2020), IEEE, 7-9 October 2020, TamilNadu, INDIA
    Keywords Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Machine Learning ; Computer Science - Neural and Evolutionary Computing
    Subject code 006
    Publishing date 2020-10-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article: Current Trends and Future Approaches in Small-Molecule Therapeutics for COVID-19

    Laws, Mark / Surani, Yasmin M / Hasan, Md Mahbub / Chen, Yiyuan / Jin, Peiqin / AlAdhami, Taha / Chowdhury, Madiha / Imran, Aqeel / Psaltis, Ioannis / Jamshidi, Shirin / Nahar, Kazi S / Rahman, Khondaker Miraz

    Curr. med. chem

    Abstract: The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is ... ...

    Abstract The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is likely to take at least 12-18 months to develop a new vaccine. Therefore, there is an urgent need to find new therapeutics that can be progressed to clinical development as soon as possible. Repurposing regulatory agencyapproved drugs and experimental drugs with known safety profiles can provide important repositories of compounds that can be fast-tracked to clinical development. Globally, over 500 clinical trials involving repurposed drugs have been registered, and over 150 have been initiated, including some backed by the World Health Organisation (WHO). This review is intended as a guide to research into small-molecule therapies to treat COVID-19; it discusses the SARS-CoV-2 infection cycle and identifies promising viral therapeutic targets, reports on a number of promising pre-approved small-molecule drugs with reference to over 150 clinical trials worldwide, and offers a perspective on the future of the field.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #659720
    Database COVID19

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  5. Article ; Online: Current Trends and Future Approaches in Small-Molecule Therapeutics for COVID-19

    Laws, Mark / Surani, Yasmin M. / Hasan, Md. Mahbub / Chen, Yiyuan / Jin, Peiqin / AlAdhami, Taha / Chowdhury, Madiha / Imran, Aqeel / Psaltis, Ioannis / Jamshidi, Shirin / Nahar, Kazi S. / Rahman, Khondaker Miraz

    Current Medicinal Chemistry

    2020  Volume 27

    Abstract: The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is ... ...

    Abstract : The novel coronavirus (SARS-CoV-2) pandemic has created a global public health emergency. The pandemic is causing substantial morbidity, mortality and significant economic loss. Currently, no approved treatments for COVID-19 are available, and it is likely to take at least 12-18 months to develop a new vaccine. Therefore, there is an urgent need to find new therapeutics that can be progressed to clinical development as soon as possible. Repurposing regulatory agencyapproved drugs and experimental drugs with known safety profiles can provide important repositories of compounds that can be fast-tracked to clinical development. Globally, over 500 clinical trials involving repurposed drugs have been registered, and over 150 have been initiated, including some backed by the World Health Organisation (WHO). This review is intended as a guide to research into small-molecule therapies to treat COVID-19; it discusses the SARS-CoV-2 infection cycle and identifies promising viral therapeutic targets, reports on a number of promising pre-approved small-molecule drugs with reference to over 150 clinical trials worldwide, and offers a perspective on the future of the field.
    Keywords Molecular Medicine ; Pharmacology ; covid19
    Language English
    Publisher Bentham Science Publishers Ltd.
    Publishing country nl
    Document type Article ; Online
    ZDB-ID 1319315-6
    ISSN 1875-533X ; 0929-8673
    ISSN (online) 1875-533X
    ISSN 0929-8673
    DOI 10.2174/0929867327666200721161840
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 4432: Show issues Location:
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  6. Article ; Online: Novel pyridyl nitrofuranyl isoxazolines show antibacterial activity against multiple drug resistant Staphylococcus species.

    Picconi, Pietro / Prabaharan, Priya / Auer, Jennifer L / Sandiford, Stephanie / Cascio, Francesco / Chowdhury, Madiha / Hind, Charlotte / Wand, Matthew E / Sutton, J Mark / Rahman, Khondaker M

    Bioorganic & medicinal chemistry

    2017  Volume 25, Issue 15, Page(s) 3971–3979

    Abstract: A novel series of pyridyl nitrofuranyl isoxazolines were synthesized and evaluated for their antibacterial activity against multiple drug resistant (MDR) Staphylococcus strains. Compounds with piperazine linker between the pyridyl group and isoxazoline ... ...

    Abstract A novel series of pyridyl nitrofuranyl isoxazolines were synthesized and evaluated for their antibacterial activity against multiple drug resistant (MDR) Staphylococcus strains. Compounds with piperazine linker between the pyridyl group and isoxazoline ring showed better activity when compared to compounds without the piperazine linker. 3-Pyridyl nitrofuranyl isoxazoline with a piperazine linker was found to be more active than corresponding 2-and 4-pyridyl analogues with MICs in the range of 4-32µg/mL against MDR Staphylococcus strains. The eukaryotic toxicity of the compounds was tested by MTT assay and were found to be non-toxic against both non-tumour lung fibroblast WI-38 and cervical cancer cell line HeLa. The most active pyridyl nitrofuranyl isoxazoline compound showed improved activity against a panel of Staphylococcus strains compared to nitrofuran group containing antibiotic nitrofurantoin.
    Language English
    Publishing date 2017-08-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 1161284-8
    ISSN 1464-3391 ; 0968-0896
    ISSN (online) 1464-3391
    ISSN 0968-0896
    DOI 10.1016/j.bmc.2017.05.037
    Database MEDical Literature Analysis and Retrieval System OnLINE

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