Evaluating the Use of Dexamethasone in Diabetic Patients Undergoing Total Joint Arthroplasty: A Systematic Review and Meta-analysis.

Background: The American Association of Hip and Knee Surgeons (AAHKS) strongly recommends the use of dexamethasone in patients undergoing total joint arthroplasty (TJA) due to its therapeutic effects. However, use in diabetic patients is controversial due to safety. Therefore, the objective of this study was to determine safety: (1) calculating the post-operative glucose levels; (2) finding the ideal dexamethasone dosing regimen; and (3) reporting complications of dexamethasone administration in diabetic patients undergoing TJA.

Ameliorated delivery of amphotericin B to macrophages using chondroitin sulfate surface-modified liposome nanoparticles.

Background: The neglected tropical disease leishmaniasis has significant adverse effects from current treatments and limited therapeutic options are currently available.

Objective: The aim of this study was to develop a surface-modified nano-liposomal drug delivery system, anchored with chondroitin sulfate (CS), to effectively transport Amphotericin B (AmB) to macrophages.

Methods: Conventional liposome formulations (CL-F) and CS-coated surface-modified liposome formulations (CS-SML-F) were formulated by the thin film hydration method and characterized for particle size, polydispersity index (PDI), zeta potential, and entrapment efficiency with long-term stability.

Transformation of Digital Health: Advancing Telerehabilitation with Smartwatch Technology.

The emergence of innovative electronic devices has revolutionized the role of medicine, specifically telemedicine and telerehabilitation. A smartwatch is similar in shape to a traditional wristwatch with a built-in, networked computer with an array of sensors. The use of smartwatches has provided healthcare workers with new opportunities for monitoring and managing health.

The emerging role of cardiopulmonary exercise testing and cardiac rehabilitation in dilated cardiomyopathy: A mini review.

Cardiovascular mortality is a major health burden worldwide and the number of patients with cardiac diseases is increasing. Dilated cardiomyopathy (DCM) is the most frequent cause for patient visits in cardiac care units and emergency departments. It is commonly misdiagnosed as ischaemic cardiac disease.

Correlating physico-chemical properties of analytes with Hansen solubility parameters of solvents using machine learning algorithm for predicting suitable extraction solvent.

Artificial neural networks (ANNs) are biologically inspired algorithms designed to simulate the way in which the human brain processes information. In sample preparation for bioanalysis, liquid-liquid extraction (LLE) represents an important step with the extraction solvent selection is the key laborious step. In the current work, a robust and reliable ANNs model for LLE solvent prediction was generated which could predict the suitable solvent for analyte extraction.