Publications by authors named "M R Sher"

Gastro retentive drug delivery systems (GRDDS) have gained immense popularity as they reduce dosing frequency, improve bioavailability, and enhance patient compliance. Herein, a plant-based, controlled swelling, and pH-sensitive GRDDS based on Aloe vera hydrogel and cellulose was developed for the sustained release of levofloxacin (LEVO). The properties of five various floating tablet formulations including dynamic swelling, pH-responsiveness, hardness, friability, drug release, and buoyant time were evaluated.

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Mixed-cation mixed-halide lead perovskites have been shown to be excellent candidates for solar energy conversion. However, understanding the structural phases of these mixed-ion perovskites across a wide range of operating temperatures, including very low temperatures for space applications, is crucial. In this study, we investigated the structure of formamidinium-based Cs FA Pb(Br I ) using low-temperature in situ synchrotron powder X-ray diffraction.

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Article Synopsis
  • Curcumin was encapsulated in a double-layer shell made from nano-sized cellulose and either native starch (MDC) or nano-sized starch (NDC) to enhance stability and mask bitterness.
  • The study assessed encapsulation efficiency, with values of 97.11% for NDC and 90.46% for MDC, and employed FTIR to analyze structural changes in curcumin, indicating reduced intensity of curcumin peaks when encapsulated.
  • The double-walled curcumin capsules were applied to fish fillets coated in starch paste, revealing a visible color change over 7 days in refrigerated storage, effectively signaling spoilage to consumers without needing to open the package.
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Brain tumors pose significant global health concerns due to their high mortality rates and limited treatment options. These tumors, arising from abnormal cell growth within the brain, exhibits various sizes and shapes, making their manual detection from magnetic resonance imaging (MRI) scans a subjective and challenging task for healthcare professionals, hence necessitating automated solutions. This study investigates the potential of deep learning, specifically the DenseNet architecture, to automate brain tumor classification, aiming to enhance accuracy and generalizability for clinical applications.

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Background: Chronic cough, a cough lasting >8 weeks, includes refractory chronic cough (RCC) and unexplained chronic cough (UCC). Patient-reported outcome (PRO) measures are needed to better understand chronic cough impacts that matter most to patients. The 19-item Leicester Cough Questionnaire (LCQ), an existing PRO measure of chronic cough, assesses impacts of cough across physical, psychological, and social domains.

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