A short-term statin treatment changes the contractile properties of fast-twitch skeletal muscles

Background : Cumulative evidence indicates that statins induce myotoxicity. However, the lack of understanding of how statins affect skeletal muscles at the structural, functional, and physiological levels hampers proper healthcare management. The purpose of the present study was to investigate the early after-effects of lovastatin on the slow-twitch soleus (Sol) and fast-twitch extensor digitorum longus (EDL) muscles. Methods : Adult C57BL/6 mice were orally administrated with placebo or lovastatin [50 mg/kg/d] for 28 days. At the end of the treatment, the isometric ex vivo contractile properties of the Sol and EDL muscles were measured. Subtetanic and tetanic contractions were assessed and contraction kinetics were recorded. The muscles were then frozen for immunohistochemical analyses. Data were analyzed by two-way ANOVA followed by an a posteriori Tukey’s test. Results : The short-term lovastatin treatment did not induce muscle mass loss, muscle fiber atrophy, or creatine kinase (CK) release. It had no functional impact on slow-twitch Sol muscles. However, subtetanic stimulations at 10 Hz provoked greater force production in fast-twitch EDL muscles. The treatment also decreased the maximal rate of force development (dP/dT) of twitch contractions and prolonged the half relaxation time (1/2RT) of tetanic contractions of EDL muscles. Conclusions : An early short-term statin treatment induced subtle but significant changes in some parameters of the contractile profile of EDL muscles, providing new insights into the selective initiation of statin-induced myopathy in fast-twitch muscles

An approach to design smart grids and their IT system by cosimulation

International audienceSmart grids are the oncoming generation of power grids, which rely on information and communication technologies to tackle decentralized and intermittent energy sources such as wind farms and photovoltaic plants. They integrate electronics, software information processing and telecommunications technical domains. Therefore the design of smart grids is complex because of the various technical domains and modeling tools at stake. In this article, we present an approach to their design, which relies on model driven engineering, executable models and FMI based cosimulation. This approach is illustrated on the use case of an insular power grid and allows to study the impact of power production decision

A Patch-Based Method for Repetitive and Transient Event Detection in Fluorescence Imaging

Automatic detection and characterization of molecular behavior in large data sets obtained by fast imaging in advanced light microscopy become key issues to decipher the dynamic architectures and their coordination in the living cell. Automatic quantification of the number of sudden and transient events observed in fluorescence microscopy is discussed in this paper. We propose a calibrated method based on the comparison of image patches expected to distinguish sudden appearing/vanishing fluorescent spots from other motion behaviors such as lateral movements. We analyze the performances of two statistical control procedures and compare the proposed approach to a frame difference approach using the same controls on a benchmark of synthetic image sequences. We have then selected a molecular model related to membrane trafficking and considered real image sequences obtained in cells stably expressing an endocytic-recycling trans-membrane protein, the Langerin-YFP, for validation. With this model, we targeted the efficient detection of fast and transient local fluorescence concentration arising in image sequences from a data base provided by two different microscopy modalities, wide field (WF) video microscopy using maximum intensity projection along the axial direction and total internal reflection fluorescence microscopy. Finally, the proposed detection method is briefly used to statistically explore the effect of several perturbations on the rate of transient events detected on the pilot biological model

Physiological role of receptor activator nuclear factor-kB (RANK) in denervation-induced muscle atrophy and dysfunction

The bone remodeling and homeostasis are mainly controlled by the receptor-activator of nuclear factor kB (RANK), its ligand RANKL, and the soluble decoy receptor osteoprotegerin (OPG) pathway. While there is a strong association between osteoporosis and skeletal muscle dysfunction, the functional relevance of a particular biological pathway that synchronously regulates bone and skeletal muscle physiopathology remains elusive. Our recent article published in the American Journal of Physiology (Cell Physiology) showed that RANK is also expressed in fully differentiated C2C12 myotubes and skeletal muscles. We used the Cre-Lox approach to inactivate muscle RANK (RANKmko) and showed that RANK deletion preserves the force of denervated fast-twitch EDL muscles. However, RANK deletion had no positive impact on slow-twitch Sol muscles. In addition, denervating RANKmko EDL muscles induced an increase in the total calcium concentration ([CaT]), which was associated with a surprising decrease in SERCA activity. Interestingly, the levels of STIM-1, which mediates Ca2+ influx following the depletion of SR Ca2+ stores, were markedly higher in denervated RANKmko EDL muscles. We speculated that extracellular Ca2+ influx mediated by STIM-1 may be important for the increase in [CaT] and the gain of force in denervated RANKmko EDL muscles. Overall, these findings showed for the first time that the RANKL/RANK interaction plays a role in denervation-induced muscle atrophy and dysfunction

An extended model of vesicle fusion at the plasma membrane to estimate protein lateral diffusion from TIRF microscopy images.

BACKGROUND: Characterizing membrane dynamics is a key issue to understand cell exchanges with the extra-cellular medium. Total internal reflection fluorescence microscopy (TIRFM) is well suited to focus on the late steps of exocytosis at the plasma membrane. However, it is still a challenging task to quantify (lateral) diffusion and estimate local dynamics of proteins. RESULTS: A new model was introduced to represent the behavior of cargo transmembrane proteins during the vesicle fusion to the plasma membrane at the end of the exocytosis process. Two biophysical parameters, the diffusion coefficient and the release rate parameter, are automatically estimated from TIRFM image sequences, to account for both the lateral diffusion of molecules at the membrane and the continuous release of the proteins from the vesicle to the plasma membrane. Quantitative evaluation on 300 realistic computer-generated image sequences demonstrated the efficiency and accuracy of the method. The application of our method on 16 real TIRFM image sequences additionally revealed differences in the dynamic behavior of Transferrin Receptor (TfR) and Langerin proteins. CONCLUSION: An automated method has been designed to simultaneously estimate the diffusion coefficient and the release rate for each individual vesicle fusion event at the plasma membrane in TIRFM image sequences. It can be exploited for further deciphering cell membrane dynamics

Discriminant random field and patch-based redundancy analysis for image change detection

International audienceTo develop better image change detection algorithms, new models able to capture all the spatio-temporal regularities and geometries seen in an image pair are needed. In con- trast to the usual pixel-wise methods, we propose a patch- based formulation for modeling semi-local interactions and detecting occlusions and other local or regional changes in an image pair. To this end, the image redundancy property is exploited to detect unusual spatio-temporal patterns in the scene. We first define adaptive detectors of changes between two given image patches and combine locally in space and scale such detectors. The resulting score at a given loca- tion is exploited within a discriminant Markov random field (DRF) whose global optimization flags out changes with no optical flow computation. Experimental results on several applications demonstrate that the method performs well at detecting occlusions and meaningful regional changes and is especially robust in the case of low signal-to-noise ratios

Lifetime MAP reconstruction in frequency-domain fluorescence lifetime imaging microscopy

International audienceWe propose a robust statistical framework for reconstructing lifetime map corrupted by vesicle motion in frequency domain FLIM imaging. Instrumental noise is taken into account to improve lifetime estimation. Robust M-estimators and MLestimators allow to jointly estimate motion and lifetime. Performances are demonstrated on simulated and real samples

MAVS polymers smaller than 80 nm induce mitochondrial membrane remodeling and interferon signaling.

Double-stranded RNA (dsRNA) is a potent proinflammatory signature of viral infection and is sensed primarily by RIG-I-like receptors (RLRs). Oligomerization of RLRs following binding to cytosolic dsRNA activates and nucleates self-assembly of the mitochondrial antiviral-signaling protein (MAVS). In the current signaling model, the caspase recruitment domains of MAVS form helical fibrils that self-propagate like prions to promote signaling complex assembly. However, there is no conclusive evidence that MAVS forms fibrils in cells or with the transmembrane anchor present. We show here with super-resolution light microscopy that MAVS activation by dsRNA induces mitochondrial membrane remodeling. Quantitative image analysis at imaging resolutions as high as 32 nm shows that in the cellular context, MAVS signaling complexes and the fibrils within them are smaller than 80 nm. The transmembrane domain of MAVS is required for its membrane remodeling, interferon signaling, and proapoptotic activities. We conclude that membrane tethering of MAVS restrains its polymerization and contributes to mitochondrial remodeling and apoptosis upon dsRNA sensing.Wellcome Trust 101908/Z/13/Z MRC/BBSRC/EPSRC MR/K015680/

The smart grid simulation framework: model-driven engineering applied to cyber-physical systems

International audienceSmart grids are complex systems for which simulation offers a practical way to evaluate and compare multiple solutions before deployment. However, the simulation of a Smart Grid requires the development of heterogeneous models corresponding to electrical, information processing, and telecommunication behaviors. These heterogeneous models must be linked and analyzed together in order to detect the influences on one another and identify emerging behaviors. We apply model-driven engineering to such cyber-physical systems combining physical and digital components and propose SGridSF, the Smart Grid Simulation Framework, which automates tasks in order to ensure consistency between different simulation models. This framework consists mainly of a domain specific language for modeling a cosimulation unit, called CosiML for Cosimulation Modeling Language, a domain specific language for modeling the functional architecture of a Smart Grid, called SGridML for Smart Grid Modeling Language, and a tool implementing different transformation rules to generate the files and scripts for executing a cosimulation. Finally, we illustrate the use of SGridSF on the real use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production. We show the sequencing of automatic generation tasks that minimizes the effort and the risk of error at each iteration of the process