Publications by authors named "M K Khan"

Rice (Oryza sativa ) is a crucial staple crop worldwide, providing nutrition to more than half of the global population. Nonetheless, the sustainability of grain production is increasingly jeopardized by both biotic and abiotic stressors exacerbated by climate change, which increases the crop's rvulnerability to pests and diseases. Genome-editing by clustered regularly interspaced short palindromic repeats and CRISPR-associated Protein 9 (CRISPR-Cas9) presents a potential solution for enhancing rice productivity and resilience under climatic stress.

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Background: Tauopathies are a group of neurological disorders including Alzheimer's disease that involve progressive neurodegeneration, behavioral deficits, and aberrant tau accumulation. While the molecular mechanisms that regulate the progression of the tauopathy are not fully elucidated, there is evidence to suggest that accumulation of nuclear DNA damage, particularly nuclear DNA double-strand breaks (DNA DSBs), contribute to the progression of neurodegeneration. In our present work, we investigated the relationship between DNA DSB accumulation and neuroinflammation in the brains of AD patients and a mouse model of tauopathy.

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Background: Among primary liver tumors, hepatocellular carcinoma (HCC) is considered the most common hepatic tumor. Liver transplantation is one of the curative treatment options for HCC. However, the risk of HCC recurrence after liver transplantation varies and is influenced by various factors.

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The study has investigated the implications of three estimation methods, namely L-moments, Maximum Likelihood, and Maximum Product of Spacing (MPS), for fitting the four-parameter Kappa Distribution (KAPD) in extreme value analysis using Monte Carlo simulations. The accuracy of the estimates has been evaluated using root mean square error (RMSE) and bias. The paper also includes an analysis of the effect of the estimation method on the estimated quantiles considering a real-life example of annual maximum peak flows and the Generalized Normal Distribution as the error distribution.

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Extracellular vesicles (EVs) are associated with intercellular communications, immune responses, viral pathogenicity, cardiovascular diseases, neurological disorders, and cancer progression. EVs deliver proteins, metabolites, and nucleic acids into recipient cells to effectively alter their physiological and biological response. During their transportation from the donor to the recipient cell EVs face differential ionic concentrations, which can be detrimental to their integrity and impact their cargo content.

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