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Biology subjects

Bordes, C.

Publications and source records attributed to Bordes, C..

2 recordsLinked to original sources

Polymeric nanoparticles delivery of AMPK activator 991 prevents its toxicity and improves muscle homeostasis in Duchenne Muscular Dystrophy

Muscular dystrophies, such as Duchenne muscular dystrophy (DMD), are caused by permanent muscle injuries leading to chronic inflammation. In that context, macrophages harbor an altered inflammatory profile that contributes to fibrosis through the secretion of the profibrotic cytokine TGF{beta}1. We previously showed that AMP-activated protein kinase (AMPK) activation reduces TGF{beta}1 secretion by macrophages and improves muscle homeostasis and muscle force in a mouse model of DMD. This makes AMPK an attractive therapeutic target for treating chronic inflammation and fibrosis in DMD. However, potent direct AMPK activators like compound 991 show strong adverse effects in vivo, preventing their direct use. Here, we encapsulated 991 into biodegradable polymeric poly(lactic-co-glycolic) acid (PLGA) nanoparticles for in vivo delivery, in an attempt to overcome toxicity issues. We show that 991-loaded PLGA nanoparticles retained drug activity on fibrotic macrophages in vitro, by reducing their secretion of TGF{beta}1. In the D2-mdx pre-clinical DMD mouse model, intravenously injected PLGA nanoparticles reached gastrocnemius and diaphragm muscles, which are the most affected muscles in this model. Chronic intravenous injections of 991-loaded PLGA nanoparticles decreased inflammation in both muscles, which was associated with fibrosis reduction and increase in myofiber size and muscle mass in the gastrocnemius. No impact on blood cell counts and liver enzymes was observed. These results demonstrate that nanomedicine is an efficient strategy to deliver AMPK activators in vivo to target inflammation and improve the dystrophic muscle phenotype.

pathology↗

A dynamic inflammation model for neutrophil and monocyte responses in sepsis, trauma and surgery patient clusters.

Time series clustering is applied to inflammation and neutrophil cell development markers, CD16 and CD10, in sepsis, trauma and surgery patients and a dynamical model with an inflammation function, F, is used to represent their evolution over a two month period. Five patient clusters are identified, characterised and evaluated against medical assessment scores and the literature. A dynamical model for neutrophil and monocyte cell counts and maturity has been constructed based on mass balances and cell kinetics in both blood and bone marrow. Cell proliferation and flow rates, as well as expression of monocyte HLA-DR, depend on concentrations of pro- and anti- inflammatory cytokines, IL6 and IL10, via F. A good fit with the data is obtained for each cluster and the estimated parameters correlate to illness severity. The model is a potential tool for simulation of immunomodulatory therapies.

bioengineering↗