One of the complication of diabetes mellitus is chronic wounds. The healing of wounds in diabetic patients is retarded by the elevation in the pro-inflammatory cytokines secretion and free radicles accumulation. Wound management in diabetic patients requires preventing bacterial biofilm development.
View Article and Find Full Text PDFEnviron Monit Assess
March 2025
Heavy metal contamination in industrial-agricultural regions poses global challenges, yet comprehensive risk assessment models addressing both ecological and human health impacts are scarce. This study introduces a novel multi-compartmental risk assessment framework applied to the Saldha River region of Gazipur, Bangladesh, a rapidly industrialising area experiencing significant environmental stress. Here, we analysed eight heavy metals (Cr, Pb, Cu, Fe, Mn, Zn, Ni, and Cd) in soil, wastewater, and plant samples (spinach, wild rice, and nut grass) via atomic absorption spectrophotometry (AAS).
View Article and Find Full Text PDFIntroduction: Acute radiation dermatitis (ARD) is a common side effect experienced during radiation therapy (RT) for cancer. Published clinical trials for ARD use a myriad of assessment tools and outcomes to measure ARD severity, which limits the comparability of clinical trial results. Our study utilized a modified Delphi consensus survey to gather expert opinions on commonly used tools for ARD severity.
View Article and Find Full Text PDFThe study focuses on developing and evaluating 3D biomimetic fibrous scaffolds to enhance osteoblast differentiation and bone tissue regeneration. Utilizing a synergistic approach, biological and chemical factors were compartmentalized within the fibrous scaffolds through co-axial electrospinning. Bioactive glass (BG) was used for osteo-conductivity, and Bone-Conditioned Medium (BCM) for osteoinduction.
View Article and Find Full Text PDFBiomed Phys Eng Express
March 2025
Driver drowsiness significantly contributes to road accidents worldwide, and timely prediction of driver reaction time is crucial for developing effective advanced driver assistance systems. In this paper, we present an EEG-based prediction framework that investigates the impact of different pre-stimulus time windows, frequency band combinations, and channel groups on driver reaction time estimation using data from a 90-minute sustained attention driving task. Our systematic evaluation using a publicly available dataset of 24 drivers reveals that a 2-second pre-stimulus window yields the lowest prediction error.
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