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  1. Article ; Online: Epigenetic Regulation of Adipogenesis in Development of Metabolic Syndrome

    Richa Pant / Priyanka Firmal / Vibhuti Kumar Shah / Aftab Alam / Samit Chattopadhyay

    Frontiers in Cell and Developmental Biology, Vol

    2021  Volume 8

    Abstract: Obesity is one of the biggest public health concerns identified by an increase in adipose tissue mass as a result of adipocyte hypertrophy and hyperplasia. Pertaining to the importance of adipose tissue in various biological processes, any alteration in ... ...

    Abstract Obesity is one of the biggest public health concerns identified by an increase in adipose tissue mass as a result of adipocyte hypertrophy and hyperplasia. Pertaining to the importance of adipose tissue in various biological processes, any alteration in its function results in impaired metabolic health. In this review, we discuss how adipose tissue maintains the metabolic health through secretion of various adipokines and inflammatory mediators and how its dysfunction leads to the development of severe metabolic disorders and influences cancer progression. Impairment in the adipocyte function occurs due to individuals’ genetics and/or environmental factor(s) that largely affect the epigenetic profile leading to altered gene expression and onset of obesity in adults. Moreover, several crucial aspects of adipose biology, including the regulation of different transcription factors, are controlled by epigenetic events. Therefore, understanding the intricacies of adipogenesis is crucial for recognizing its relevance in underlying disease conditions and identifying the therapeutic interventions for obesity and metabolic syndrome.
    Keywords obesity ; adipogenesis ; insulin resistance ; metabolic syndrome ; transgenerational inheritance ; Biology (General) ; QH301-705.5
    Language English
    Publishing date 2021-01-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Overview of Immune Response During SARS-CoV-2 Infection

    Vibhuti Kumar Shah / Priyanka Firmal / Aftab Alam / Dipyaman Ganguly / Samit Chattopadhyay

    Frontiers in Immunology, Vol

    Lessons From the Past

    2020  Volume 11

    Abstract: After the 1918 flu pandemic, the world is again facing a similar situation. However, the advancement in medical science has made it possible to identify that the novel infectious agent is from the coronavirus family. Rapid genome sequencing by various ... ...

    Abstract After the 1918 flu pandemic, the world is again facing a similar situation. However, the advancement in medical science has made it possible to identify that the novel infectious agent is from the coronavirus family. Rapid genome sequencing by various groups helped in identifying the structure and function of the virus, its immunogenicity in diverse populations, and potential preventive measures. Coronavirus attacks the respiratory system, causing pneumonia and lymphopenia in infected individuals. Viral components like spike and nucleocapsid proteins trigger an immune response in the host to eliminate the virus. These viral antigens can be either recognized by the B cells or presented by MHC complexes to the T cells, resulting in antibody production, increased cytokine secretion, and cytolytic activity in the acute phase of infection. Genetic polymorphism in MHC enables it to present some of the T cell epitopes very well over the other MHC alleles. The association of MHC alleles and its downregulated expression has been correlated with disease severity against influenza and coronaviruses. Studies have reported that infected individuals can, after recovery, induce strong protective responses by generating a memory T-cell pool against SARS-CoV and MERS-CoV. These memory T cells were not persistent in the long term and, upon reactivation, caused local damage due to cross-reactivity. So far, the reports suggest that SARS-CoV-2, which is highly contagious, shows related symptoms in three different stages and develops an exhaustive T-cell pool at higher loads of viral infection. As there are no specific treatments available for this novel coronavirus, numerous small molecular drugs that are being used for the treatment of diseases like SARS, MERS, HIV, ebola, malaria, and tuberculosis are being given to COVID-19 patients, and clinical trials for many such drugs have already begun. A classical immunotherapy of convalescent plasma transfusion from recovered patients has also been initiated for the neutralization of viremia in terminally ill COVID-19 patients. Due to the limitations of plasma transfusion, researchers are now focusing on developing neutralizing antibodies against virus particles along with immuno-modulation of cytokines like IL-6, Type I interferons (IFNs), and TNF-α that could help in combating the infection. This review highlights the similarities of the coronaviruses that caused SARS and MERS to the novel SARS-CoV-2 in relation to their pathogenicity and immunogenicity and also focuses on various treatment strategies that could be employed for curing COVID-19.
    Keywords coronavirus ; immune response ; COVID-19 ; T cells ; MHC presentation ; HLA ; Immunologic diseases. Allergy ; RC581-607 ; covid19
    Subject code 570
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher Frontiers Media S.A.
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Development and clinical validation of Swaasa AI platform for screening and prioritization of pulmonary TB

    Gayatri Devi Yellapu / Gowrisree Rudraraju / Narayana Rao Sripada / Baswaraj Mamidgi / Charan Jalukuru / Priyanka Firmal / Venkat Yechuri / Sowmya Varanasi / Venkata Sudhakar Peddireddi / Devi Madhavi Bhimarasetty / Sidharth Kanisetti / Niranjan Joshi / Prasant Mohapatra / Kiran Pamarthi

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    2023  Volume 11

    Abstract: Abstract Acoustic signal analysis has been employed in various medical devices. However, studies involving cough sound analysis to screen the potential pulmonary tuberculosis (PTB) suspects are very few. The main objective of this cross-sectional ... ...

    Abstract Abstract Acoustic signal analysis has been employed in various medical devices. However, studies involving cough sound analysis to screen the potential pulmonary tuberculosis (PTB) suspects are very few. The main objective of this cross-sectional validation study was to develop and validate the Swaasa AI platform to screen and prioritize at risk patients for PTB based on the signature cough sound as well as symptomatic information provided by the subjects. The voluntary cough sound data was collected at Andhra Medical College-India. An Algorithm based on multimodal convolutional neural network architecture and feedforward artificial neural network (tabular features) was built and validated on a total of 567 subjects, comprising 278 positive and 289 negative PTB cases. The output from these two models was combined to detect the likely presence (positive cases) of PTB. In the clinical validation phase, the AI-model was found to be 86.82% accurate in detecting the likely presence of PTB with 90.36% sensitivity and 84.67% specificity. The pilot testing of model was conducted at a peripheral health care centre, RHC Simhachalam-India on 65 presumptive PTB cases. Out of which, 15 subjects truly turned out to be PTB positive with a positive predictive value of 75%. The validation results obtained from the model are quite encouraging. This platform has the potential to fulfil the unmet need of a cost-effective PTB screening method. It works remotely, presents instantaneous results, and does not require a highly trained operator. Therefore, it could be implemented in various inaccessible, resource-poor parts of the world.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2023-03-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Author Correction

    Gayatri Devi Yellapu / Gowrisree Rudraraju / Narayana Rao Sripada / Baswaraj Mamidgi / Charan Jalukuru / Priyanka Firmal / Venkat Yechuri / Sowmya Varanasi / Venkata Sudhakar Peddireddi / Devi Madhavi Bhimarasetty / Sidharth Kanisetti / Niranjan Joshi / Prasant Mohapatra / Kiran Pamarthi

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    Development and clinical validation of Swaasa AI platform for screening and prioritization of pulmonary TB

    2023  Volume 1

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2023-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Screening COVID-19 by Swaasa AI platform using cough sounds

    Padmalatha Pentakota / Gowrisree Rudraraju / Narayana Rao Sripada / Baswaraj Mamidgi / Charishma Gottipulla / Charan Jalukuru / Shubha Deepti Palreddy / Nikhil Kumar Reddy Bhoge / Priyanka Firmal / Venkat Yechuri / Manmohan Jain / Venkata Sudhakar Peddireddi / Devi Madhavi Bhimarasetty / S. Sreenivas / Kesava Lakshmi Prasad K / Niranjan Joshi / Shibu Vijayan / Sanchit Turaga / Vardhan Avasarala

    Scientific Reports, Vol 13, Iss 1, Pp 1-

    a cross-sectional study

    2023  Volume 11

    Abstract: Abstract The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than six million lives to date and therefore, needs a robust screening ... ...

    Abstract Abstract The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than six million lives to date and therefore, needs a robust screening technique to control the disease spread. In the present study we created and validated the Swaasa AI platform, which uses the signature cough sound and symptoms presented by patients to screen and prioritize COVID-19 patients. We collected cough data from 234 COVID-19 suspects to validate our Convolutional Neural Network (CNN) architecture and Feedforward Artificial Neural Network (FFANN) (tabular features) based algorithm. The final output from both models was combined to predict the likelihood of having the disease. During the clinical validation phase, our model showed a 75.54% accuracy rate in detecting the likely presence of COVID-19, with 95.45% sensitivity and 73.46% specificity. We conducted pilot testing on 183 presumptive COVID subjects, of which 58 were truly COVID-19 positive, resulting in a Positive Predictive Value of 70.73%. Due to the high cost and technical expertise required for currently available rapid screening methods, there is a need for a cost-effective and remote monitoring tool that can serve as a preliminary screening method for potential COVID-19 subjects. Therefore, Swaasa would be highly beneficial in detecting the disease and could have a significant impact in reducing its spread.
    Keywords Medicine ; R ; Science ; Q
    Subject code 670
    Language English
    Publishing date 2023-10-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: TopicalPdb

    Deepika Mathur / Ayesha Mehta / Priyanka Firmal / Gursimran Bedi / Charu Sood / Ankur Gautam / Gajendra P S Raghava

    PLoS ONE, Vol 13, Iss 2, p e

    A database of topically delivered peptides.

    2018  Volume 0190134

    Abstract: TopicalPdb (http://crdd.osdd.net/raghava/topicalpdb/) is a repository of experimentally verified topically delivered peptides. Data was manually collected from research articles. The current release of TopicalPdb consists of 657 entries, which includes ... ...

    Abstract TopicalPdb (http://crdd.osdd.net/raghava/topicalpdb/) is a repository of experimentally verified topically delivered peptides. Data was manually collected from research articles. The current release of TopicalPdb consists of 657 entries, which includes peptides delivered through the skin (462 entries), eye (173 entries), and nose (22 entries). Each entry provides comprehensive information related to these peptides like the source of origin, nature of peptide, length, N- and C-terminal modifications, mechanism of penetration, type of assays, cargo and biological properties of peptides, etc. In addition to natural peptides, TopicalPdb contains information of peptides having non-natural, chemically modified residues and D-amino acids. Besides this primary information, TopicalPdb stores predicted tertiary structures as well as peptide sequences in SMILE format. Tertiary structures of peptides were predicted using state-of-art method PEPstrMod. In order to assist users, a number of web-based tools have been integrated that includes keyword search, data browsing, similarity search and structural similarity. We believe that TopicalPdb is a unique database of its kind and it will be very useful in designing peptides for non-invasive topical delivery.
    Keywords Medicine ; R ; Science ; Q
    Subject code 540
    Language English
    Publishing date 2018-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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