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Advancements in Wound Bed Preparation of Chronic Wounds.

Surg Technol Int

January 2025

Dr. Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida.

Chronic wounds are notoriously challenging to heal as they are often halted in their normal healing process. The concept of TIME (Tissue, Inflammation/Infection, Moisture imbalance, Epithelial edge advancement) has been widely utilized in clinical practice to prepare wound beds and promote healing, particularly in longstanding wounds. Traditional methods of wound bed preparation are often inadequate in healing chronic wounds or they may not be tolerated by patients.

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Background And Hypothesis: Convergent evidence shows the presence of brain metabolic abnormalities in psychotic disorders. This study examined brain reductive stress and energy metabolism in people with psychotic disorders with impaired or average range cognition. We hypothesized that global cognitive impairment would be associated with greater brain metabolic dysregulation.

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Enzymatic asymmetric synthesis of l-phenylglycine by amino acid dehydrogenases has potential for industrial applications; however, this is hindered by their low catalytic efficiency toward high-concentration substrates. We identified and characterized a novel leucine dehydrogenase (LeuDH) with a high catalytic efficiency for benzoylformic acid via directed metagenomic approaches. Further, we obtained a triple-point mutant LeuDH-EER (D332E/G333E/L334R) with improved stability and catalytic efficiency through the rational design of distal loop 13.

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Unlabelled: Caliciviruses are significant agricultural and human pathogens that are poorly understood due to the dearth of molecular tools, including reporter systems. We report the development of a stable, faithful, and robust luciferase-based reporter system for a model calicivirus, murine norovirus (MNoV). Genetic insertion of a HiBiT tag, an 11 amino acid fragment of nanolucifersase, at the junction of the nonstructural proteins NS4 and NS5 yields infectious virus.

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The accurate quantification of glycemic index (GI) remains crucial for diabetes management, yet current methodologies are constrained by resource intensiveness and methodological limitations. digestion models face challenges in replicating the dynamic conditions of the human gastrointestinal tract, such as enzyme variability and multi-time point analysis, leading to suboptimal predictive accuracy. This review proposes an integrated technological framework combining non-enzymatic electrochemical sensing with artificial intelligence to revolutionize GI assessment.

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