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  1. Article ; Online: Novel insights into the structural changes induced by disease-associated mutations in TDP-43: a computational approach.

    Sharma, Abhibhav / Dey, Pinki

    Journal of biomolecular structure & dynamics

    2022  Volume 41, Issue 12, Page(s) 5624–5634

    Abstract: Over the last two decades, the pathogenic aggregation of TAR DNA-binding protein 43 (TDP-43) is found to be strongly associated with several fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar ... ...

    Abstract Over the last two decades, the pathogenic aggregation of TAR DNA-binding protein 43 (TDP-43) is found to be strongly associated with several fatal neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTD), etc. While the mutations and truncation in TDP-43 protein have been suggested to be responsible for TDP-43 pathogenesis by accelerating the aggregation process, the effects of these mutations on the bio-mechanism of pathological TDP-43 protein remained poorly understood. Investigating this at the molecular level, we formulized an integrated workflow of molecular dynamic simulation and machine learning models (MD-ML). By performing an extensive structural analysis of three disease-related mutations (i.e., I168A, D169G, and I168A-D169G) in the conserved RNA recognition motifs (RRM1) of TDP-43, we observed that the I168A-D169G double mutant delineates the highest packing of the protein inner core as compared to the other mutations, which may indicate more stability and higher chances of pathogenesis. Moreover, through our MD-ML workflow, we identified the biological descriptors of TDP-43 which includes the interacting residue pairs and individual protein residues that influence the stability of the protein and could be experimentally evaluated to develop potential therapeutic strategies.Communicated by Ramaswamy H. Sarma.
    MeSH term(s) Humans ; Mutation ; Amyotrophic Lateral Sclerosis/pathology ; Molecular Dynamics Simulation ; Neurodegenerative Diseases ; DNA-Binding Proteins/chemistry
    Chemical Substances DNA-Binding Proteins
    Language English
    Publishing date 2022-06-24
    Publishing country England
    Document type Journal Article
    ZDB-ID 49157-3
    ISSN 1538-0254 ; 0739-1102
    ISSN (online) 1538-0254
    ISSN 0739-1102
    DOI 10.1080/07391102.2022.2092551
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: A machine learning approach to unmask novel gene signatures and prediction of Alzheimer's disease within different brain regions.

    Sharma, Abhibhav / Dey, Pinki

    Genomics

    2021  Volume 113, Issue 4, Page(s) 1778–1789

    Abstract: Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies ... ...

    Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unraveled the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.
    MeSH term(s) Alzheimer Disease/genetics ; Brain ; Humans ; Machine Learning ; Mitochondrial Proteins ; Nuclear Matrix-Associated Proteins ; Nucleocytoplasmic Transport Proteins ; Phosphate Transport Proteins
    Chemical Substances Mitochondrial Proteins ; Nuclear Matrix-Associated Proteins ; Nucleocytoplasmic Transport Proteins ; Phosphate Transport Proteins ; RAE1 protein, human ; SLC25A46 protein, human
    Language English
    Publishing date 2021-04-18
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 356334-0
    ISSN 1089-8646 ; 0888-7543
    ISSN (online) 1089-8646
    ISSN 0888-7543
    DOI 10.1016/j.ygeno.2021.04.028
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: A machine learning approach to unmask novel gene signatures and prediction of Alzheimer's disease within different brain regions

    Sharma, Abhibhav / Dey, Pinki

    Genomics. 2021 July, v. 113, no. 4

    2021  

    Abstract: Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies ... ...

    Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unraveled the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.
    Keywords Alzheimer disease ; biomarkers ; data collection ; etiology ; genes ; genetic markers ; genomics ; hippocampus ; microarray technology ; neurodegenerative diseases ; non-coding RNA ; prediction ; prefrontal cortex ; regression analysis ; risk factors
    Language English
    Dates of publication 2021-07
    Size p. 1778-1789.
    Publishing place Elsevier Inc.
    Document type Article
    ZDB-ID 356334-0
    ISSN 1089-8646 ; 0888-7543
    ISSN (online) 1089-8646
    ISSN 0888-7543
    DOI 10.1016/j.ygeno.2021.04.028
    Database NAL-Catalogue (AGRICOLA)

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  4. Article ; Online: AE-LGBM: Sequence-based novel approach to detect interacting protein pairs via ensemble of autoencoder and LightGBM.

    Sharma, Abhibhav / Singh, Buddha

    Computers in biology and medicine

    2020  Volume 125, Page(s) 103964

    Abstract: Protein-protein interactions (PPIs) play a crucial role in biological processes of living organisms. Correct prediction of PPI can prove to be extremely valuable in probing protein functions which can aid in the development of new and powerful therapies ... ...

    Abstract Protein-protein interactions (PPIs) play a crucial role in biological processes of living organisms. Correct prediction of PPI can prove to be extremely valuable in probing protein functions which can aid in the development of new and powerful therapies for disease prevention. Many experimental studies have been previously performed to investigate PPIs. However, in-vitro techniques to investigate PPIs are resource-extensive and time-consuming. Although various in-silico approaches to predict PPI have been developed in recent years, they could be fallible in terms of accuracy and false-positive rate. To overcome these shortcomings, we propose a novel approach, AE-LGBM to predict the PPIs more accurately. It employs LightGBM classifier and utilizes the Autoencoder, which is an artificial neural network, to efficiently produce lower-dimensional, discriminative, and noise-free features. We incorporate conjoint triad (CT) and Composition-Transition-Distribution (CTD) features into the AE-LGBM framework. On performing ten-fold cross-validation, the prediction accuracies obtained by AE-LGBM for Human and Yeast datasets are 98.7% and 95.4% respectively. AE-LGBM was further evaluated on independent datasets and has achieved excellent accuracies of 100%, 100%, 99.9%, 99.3%, 99.2% on E. coli, M. musculus, C. elegans, H. pylori and H. sapiens respectively. AE-LGBM has also obtained the best accuracy when tested over three important PPI networks namely single-core network (CD9), the multiple-core network (The Ras/Raf/MEK/ERK pathway) and the cross-connection network (Wnt Network). The outstanding generalization ability of AE-LGBM makes it a versatile, efficient, and robust PPIs prediction model.
    MeSH term(s) Animals ; Caenorhabditis elegans ; Computational Biology ; Escherichia coli ; Humans ; Neural Networks, Computer ; Protein Interaction Mapping ; Saccharomyces cerevisiae
    Language English
    Publishing date 2020-08-19
    Publishing country United States
    Document type Journal Article
    ZDB-ID 127557-4
    ISSN 1879-0534 ; 0010-4825
    ISSN (online) 1879-0534
    ISSN 0010-4825
    DOI 10.1016/j.compbiomed.2020.103964
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: A Comparative Study to Find a Suitable Model for an Improved Real-Time Monitoring of The Interventions to Contain COVID-19 Outbreak in The High Incidence States of India

    G.S, Amrutha / Sharma, Abhibhav / Sharma, Anudeepti

    medRxiv

    Abstract: Background On March 11, 2020, The World Health Organization (WHO) declared coronavirus disease (COVID-19) as a global pandemic. There emerged a need for reliable models to estimate the imminent incidence and overall assessment of the outbreak, in order ... ...

    Abstract Background On March 11, 2020, The World Health Organization (WHO) declared coronavirus disease (COVID-19) as a global pandemic. There emerged a need for reliable models to estimate the imminent incidence and overall assessment of the outbreak, in order to develop effective interventions and control strategies. One such vital metrics for monitoring the transmission trends over time is the time-dependent effective reproduction number (Rt). Rt is an estimate of secondary cases caused by an infected individual at a time during the outbreak, given that a certain population proportion is already infected. Misestimated Rt is particularly concerning when probing the association between the changes in transmission rate and the changes in the implemented policies. In this paper, we substantiate the implementation of the instantaneous reproduction number (Rins) method over the conventional method to estimate Rt viz case reproduction number (Rcase), by unmasking the real-time estimation ability of both methodologies using credible datasets. Materials & Methods We employed the daily incidence dataset of COVID-19 for India and high incidence states to estimate Rins and Rcase. We compared the real-time projection obtained through these methods by corroborating those states that are containing a high number of COVID19 cases and are conducting high and efficient COVID-19 testing. The Rins and Rcase were estimated using R0 and EpiEstim packages respectively in R software 4.0.0. Results Although, both the Rins and Rcase for the selected states were higher during the lockdown phases (March 25 - June 1, 2020) and subsequently stabilizes co-equally during the unlock phase (June 1- August 23, 2020), Rins demonstrated variations in accordance with the interventions while Rcase remained generalized and under- & overestimated. A larger difference in Rins and Rcase estimates were also observed for states that are conducting high testing. Conclusion Of the two methods, Rins elucidated a better real-time progression of the COVID-19 outbreak conceptually and empirically, than that of Rcase. However, we also suggest considering the assumptions corroborated in the implementations which may result in misleading conclusions in the real world.
    Keywords covid19
    Language English
    Publishing date 2020-09-15
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2020.09.14.20190447
    Database COVID19

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  6. Article ; Online: BCG vaccination policy and preventive chloroquine usage

    Abhibhav Sharma / Saurabh Kumar Sharma / Yufang Shi / Enrico Bucci / Ernesto Carafoli / Gerry Melino / Arnab Bhattacherjee / Gobardhan Das

    Cell Death and Disease, Vol 11, Iss 7, Pp 1-

    do they have an impact on COVID-19 pandemic?

    2020  Volume 10

    Abstract: Abstract Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. ... ...

    Abstract Abstract Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the global spreading of the disease is not uniform, but has so far left some countries relatively less affected. The reason(s) for this anomalous behavior are not fully understood, but distinct hypotheses have been proposed. Here we discuss the plausibility of two of them: the universal vaccination with Bacillus Calmette–Guerin (BCG) and the widespread use of the antimalarial drug chloroquine (CQ). Both have been amply discussed in the recent literature with positive and negative conclusions: we felt that a comprehensive presentation of the data available on them would be useful. The analysis of data for countries with over 1000 reported COVID-19 cases has shown that the incidence and mortality were higher in countries in which BCG vaccination is either absent or has been discontinued, as compared with the countries with universal vaccination. We have performed a similar analysis of the data available for CQ, a widely used drug in the African continent and in other countries in which malaria is endemic; we discuss it here because CQ has been used as the drug to treat COVID-19 patients. Several African countries no longer recommend it officially for the fight against malaria, due to the development of resistance to Plasmodium, but its use across the continent is still diffuse. Taken together, the data in the literature have led to the suggestion of a possible inverse correlation between BCG immunization and COVID-19 disease incidence and severity.
    Keywords Cytology ; QH573-671 ; covid19
    Subject code 306
    Language English
    Publishing date 2020-07-01T00:00:00Z
    Publisher Nature Publishing Group
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: BCG vaccination policy and preventive chloroquine usage: do they have an impact on COVID-19 pandemic?

    Sharma, Abhibhav / Kumar Sharma, Saurabh / Shi, Yufang / Bucci, Enrico / Carafoli, Ernesto / Melino, Gerry / Bhattacherjee, Arnab / Das, Gobardhan

    Cell death & disease

    2020  Volume 11, Issue 7, Page(s) 516

    Abstract: Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the ... ...

    Abstract Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the global spreading of the disease is not uniform, but has so far left some countries relatively less affected. The reason(s) for this anomalous behavior are not fully understood, but distinct hypotheses have been proposed. Here we discuss the plausibility of two of them: the universal vaccination with Bacillus Calmette-Guerin (BCG) and the widespread use of the antimalarial drug chloroquine (CQ). Both have been amply discussed in the recent literature with positive and negative conclusions: we felt that a comprehensive presentation of the data available on them would be useful. The analysis of data for countries with over 1000 reported COVID-19 cases has shown that the incidence and mortality were higher in countries in which BCG vaccination is either absent or has been discontinued, as compared with the countries with universal vaccination. We have performed a similar analysis of the data available for CQ, a widely used drug in the African continent and in other countries in which malaria is endemic; we discuss it here because CQ has been used as the drug to treat COVID-19 patients. Several African countries no longer recommend it officially for the fight against malaria, due to the development of resistance to Plasmodium, but its use across the continent is still diffuse. Taken together, the data in the literature have led to the suggestion of a possible inverse correlation between BCG immunization and COVID-19 disease incidence and severity.
    MeSH term(s) Africa/epidemiology ; Antiviral Agents/therapeutic use ; BCG Vaccine/therapeutic use ; Betacoronavirus/drug effects ; COVID-19 ; Chloroquine/therapeutic use ; Coronavirus Infections/drug therapy ; Coronavirus Infections/epidemiology ; Coronavirus Infections/prevention & control ; Humans ; Incidence ; Pandemics/prevention & control ; Pneumonia, Viral/drug therapy ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/prevention & control ; SARS-CoV-2 ; Vaccination
    Chemical Substances Antiviral Agents ; BCG Vaccine ; Chloroquine (886U3H6UFF)
    Keywords covid19
    Language English
    Publishing date 2020-07-08
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2541626-1
    ISSN 2041-4889 ; 2041-4889
    ISSN (online) 2041-4889
    ISSN 2041-4889
    DOI 10.1038/s41419-020-2720-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: BCG vaccination policy and preventive chloroquine usage

    Sharma, Abhibhav / Kumar Sharma, Saurabh / Shi, Yufang / Bucci, Enrico / Carafoli, Ernesto / Melino, Gerry / Bhattacherjee, Arnab / Das, Gobardhan

    Cell Death & Disease

    do they have an impact on COVID-19 pandemic?

    2020  Volume 11, Issue 7

    Keywords Immunology ; Cell Biology ; Cancer Research ; Cellular and Molecular Neuroscience ; covid19
    Language English
    Publisher Springer Science and Business Media LLC
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2541626-1
    ISSN 2041-4889
    ISSN 2041-4889
    DOI 10.1038/s41419-020-2720-9
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: BCG vaccination policy and preventive chloroquine usage

    Sharma, Abhibhav / Kumar Sharma, Saurabh / Shi, Yufang / Bucci, Enrico / Carafoli, Ernesto / Melino, Gerry / Bhattacherjee, Arnab / Das, Gobardhan

    do they have an impact on COVID-19 pandemic?

    2020  

    Keywords Humans ; Pneumonia ; Viral ; Coronavirus Infections ; Chloroquine ; BCG Vaccine ; Antiviral Agents ; Vaccination ; Incidence ; Africa ; Pandemics ; Betacoronavirus ; covid19
    Language English
    Publishing date 2020-07-08
    Publisher Cell death & disease
    Publishing country uk
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article: BCG vaccination policy and preventive chloroquine usage: do they have an impact on COVID-19 pandemic?

    Sharma, Abhibhav / Kumar Sharma, Saurabh / Shi, Yufang / Bucci, Enrico / Carafoli, Ernesto / Melino, Gerry / Bhattacherjee, Arnab / Das, Gobardhan

    Cell Death Dis

    Abstract: Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the ... ...

    Abstract Coronavirus disease 2019 (COVID-19) is a severe acute respiratory syndrome caused by Coronavirus 2 (SARS-CoV-2). In the light of its rapid global spreading, on 11 March 2020, the World Health Organization has declared it a pandemic. Interestingly, the global spreading of the disease is not uniform, but has so far left some countries relatively less affected. The reason(s) for this anomalous behavior are not fully understood, but distinct hypotheses have been proposed. Here we discuss the plausibility of two of them: the universal vaccination with Bacillus Calmette-Guerin (BCG) and the widespread use of the antimalarial drug chloroquine (CQ). Both have been amply discussed in the recent literature with positive and negative conclusions: we felt that a comprehensive presentation of the data available on them would be useful. The analysis of data for countries with over 1000 reported COVID-19 cases has shown that the incidence and mortality were higher in countries in which BCG vaccination is either absent or has been discontinued, as compared with the countries with universal vaccination. We have performed a similar analysis of the data available for CQ, a widely used drug in the African continent and in other countries in which malaria is endemic; we discuss it here because CQ has been used as the drug to treat COVID-19 patients. Several African countries no longer recommend it officially for the fight against malaria, due to the development of resistance to Plasmodium, but its use across the continent is still diffuse. Taken together, the data in the literature have led to the suggestion of a possible inverse correlation between BCG immunization and COVID-19 disease incidence and severity.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #638449
    Database COVID19

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