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  1. Yadav DP, Kumar D, Jalal AS, Kumar A, Singh KU, Shah MA
    Sci Rep, 2023 Oct 09;13(1):16988.
    PMID: 37813973 DOI: 10.1038/s41598-023-44210-7
    Leukemia is a cancer of white blood cells characterized by immature lymphocytes. Due to blood cancer, many people die every year. Hence, the early detection of these blast cells is necessary for avoiding blood cancer. A novel deep convolutional neural network (CNN) 3SNet that has depth-wise convolution blocks to reduce the computation costs has been developed to aid the diagnosis of leukemia cells. The proposed method includes three inputs to the deep CNN model. These inputs are grayscale and their corresponding histogram of gradient (HOG) and local binary pattern (LBP) images. The HOG image finds the local shape, and the LBP image describes the leukaemia cell's texture pattern. The suggested model was trained and tested with images from the AML-Cytomorphology_LMU dataset. The mean average precision (MAP) for the cell with less than 100 images in the dataset was 84%, whereas for cells with more than 100 images in the dataset was 93.83%. In addition, the ROC curve area for these cells is more than 98%. This confirmed proposed model could be an adjunct tool to provide a second opinion to a doctor.
  2. Jeet Kaur R, Dutta S, Charan J, Bhardwaj P, Tandon A, Yadav D, et al.
    Int J Gen Med, 2021;14:3909-3927.
    PMID: 34349544 DOI: 10.2147/IJGM.S324349
    BACKGROUND: Thirteen COVID-19 vaccines are granted emergency approval. It is crucial to monitor their adverse events post vaccination. The present study focuses on cardiovascular adverse events post-COVID-19 vaccination and aims to determine adverse events with the administered vaccine.

    METHODOLOGY: The cardiovascular (CVS) adverse events were extracted for three broad headings (SOCs) - cardiac disorders, vascular disorders, and investigations. Descriptive statistics were reported in the form of percentage and frequency, and the disproportionality analysis was conducted.

    RESULTS: For the cardiovascular system, 4863 adverse events (AEs) were reported from BNT162b2 Pfizer, 1222 AstraZeneca, Moderna, and other COVID-19 vaccines. Common adverse events observed with vaccines under study were tachycardia (16.41%), flushing (12.17%), hypertension (5.82%), hypotension (3.60%) and peripheral coldness (2.41%). Based on disproportionality analysis (IC025 values), acute myocardial infarction, cardiac arrest, and circulatory collapse were linked to the vaccines in the age group >75 years. Hypertension, severe hypertension, supraventricular tachycardia, sinus tachycardia, and palpitations were associated across all age groups and either gender. Amongst the investigations, abnormal ECG findings raised C-reactive protein, elevated D dimer, and troponin were reported in specific age groups or gender or all subjects.

    CONCLUSION: Although cardiovascular events have been reported with the COVID-19 vaccines, the causality is yet to be established because such CVS AEs are also usually associated with the general public even without intervention. Hence, people should be administered these vaccines, and sustained monitoring of these AEs should be done.

  3. Varshney P, Sharma V, Yadav D, Kumar Y, Singh A, Kagithala NR, et al.
    Curr Drug Metab, 2023;24(12):787-802.
    PMID: 38141188 DOI: 10.2174/0113892002266408231207150547
    BACKGROUND: Cancer drug resistance remains a difficult barrier to effective treatment, necessitating a thorough understanding of its multi-layered mechanism.

    OBJECTIVE: This study aims to comprehensively explore the diverse mechanisms of cancer drug resistance, assess the evolution of resistance detection methods, and identify strategies for overcoming this challenge. The evolution of resistance detection methods and identification strategies for overcoming the challenge.

    METHODS: A comprehensive literature review was conducted to analyze intrinsic and acquired drug resistance mechanisms, including altered drug efflux, reduced uptake, inactivation, target mutations, signaling pathway changes, apoptotic defects, and cellular plasticity. The evolution of mutation detection techniques, encompassing clinical predictions, experimental approaches, and computational methods, was investigated. Strategies to enhance drug efficacy, modify pharmacokinetics, optimizoptimizee binding modes, and explore alternate protein folding states were examined.

    RESULTS: The study comprehensively overviews the intricate mechanisms contributing to cancer drug resistance. It outlines the progression of mutation detection methods and underscores the importance of interdisciplinary approaches. Strategies to overcome drug resistance challenges, such as modulating ATP-binding cassette transporters and developing multidrug resistance inhibitors, are discussed. The study underscores the critical need for continued research to enhance cancer treatment efficacy.

    CONCLUSION: This study provides valuable insights into the complexity of cancer drug resistance mechanisms, highlights evolving detection methods, and offers potential strategies to enhance treatment outcomes.

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