Combination of bacteriophages and vancomycin in a co-delivery hydrogel for localized treatment of fracture-related infections.

Fracture-related infections (FRIs), particularly those caused by methicillin-resistant Staphylococcus aureus (MRSA), are challenging to treat. This study designed and evaluated a hydrogel loaded with a cocktail of bacteriophages and vancomycin (1.2 mg/mL).

Alginate microbeads and hydrogels delivering meropenem and bacteriophages to treat Pseudomonas aeruginosa fracture-related infections.

Bacteriophage (phage) therapy has shown promise in treating fracture-related infection (FRI); however, questions remain regarding phage efficacy against biofilms, phage-antibiotic interaction, administration routes and dosing, and the development of phage resistance. The goal of this study was to develop a dual antibiotic-phage delivery system containing hydrogel and alginate microbeads loaded with a phage cocktail plus meropenem and evaluate efficacy against muti-drug resistant Pseudomonas aeruginosa. Two phages (FJK.

Bacteriophage Therapy for the Prevention and Treatment of Fracture-Related Infection Caused by Staphylococcus aureus: a Preclinical Study.

Although several studies have shown promising clinical outcomes of phage therapy in patients with orthopedic device-related infections, questions remain regarding the optimal application protocol, systemic effects, and the impact of the immune response. This study provides a proof-of-concept of phage therapy in a clinically relevant rabbit model of fracture-related infection (FRI) caused by Staphylococcus aureus. In a prevention setting, phage in saline (without any biomaterial-based carrier) was highly effective in the prevention of FRI, compared to systemic antibiotic prophylaxis alone.

Understanding the Impact of Neural Variations and Random Connections on Inference.

Recent research suggests that neural networks created from dissociated neurons may be used for computing and performing machine learning tasks. To develop a better artificial intelligent system, a hybrid bio-silicon computer is worth exploring, but its performance is still inferior to that of a silicon-based computer. One reason may be that a living neural network has many intrinsic properties, such as random network connectivity, high network sparsity, and large neural and synaptic variability.