A central tenet of skeletal muscle biology is the existence of an inverse relationship between the oxidative fibre capacity and its size. However, robustness of this relationship is unknown. We show that superimposition of Estrogen-related receptor gamma (Errγ) on the myostatin (Mtn) mouse null background (Mtn-/-/ErrγTg/+) results in hypertrophic muscle with a high oxidative capacity thus violating the inverse relationship between fibre size and oxidative capacity. We also examined the canonical view that oxidative muscle phenotype positively correlate with Satellite cell number, the resident stem cells of skeletal muscle. Surprisingly, hypertrophic fibres from Mtn-/-/ErrγTg/+ mouse showed satellite cell deficit which unexpectedly did not affect muscle regeneration. These observations 1) challenge the concept of a constraint between fibre size and oxidative capacity and 2) indicate the important role of the microcirculation in the regenerative capacity of a muscle even when satellite cell numbers are reduced.DOI: http://dx.doi.org/10.7554/eLife.16940.001
Mathematical models for excitable cells are commonly based on cable theory, which considers a homogenized domain and spatially constant ionic concentrations. Although such models provide valuable insight, the effect of altered ion concentrations or detailed cell morphology on the electrical potentials cannot be captured. In this paper, we discuss an alternative approach to detailed modelling of electrodiffusion in neural tissue. The mathematical model describes the distribution and evolution of ion concentrations in a geometrically-explicit representation of the intra-and extracellular domains. As a combination of the electroneutral Kirchhoff-Nernst-Planck (KNP) model and the Extracellular-Membrane-Intracellular (EMI) framework, we refer to this model as the KNP-EMI model. Here, we introduce and numerically evaluate a new, finite element-based numerical scheme for the KNP-EMI model, capable of efficiently and flexibly handling geometries of arbitrary dimension and arbitrary polynomial degree. Moreover, we compare the electrical potentials predicted by the KNP-EMI and EMI models. Finally, we study ephaptic coupling induced in an unmyelinated axon bundle and demonstrate how the KNP-EMI framework can give new insights in this setting.
Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.
Aim: Cachexia is a severe wasting disorder involving loss of body-and muscle mass reducing survival and quality of life in cancer patients. We aim at determining if cachexia is a mere perturbation of the protein balance or if the condition also involves a degenerative loss of myonuclei within the fibre syncytia or loss of whole muscle fibres. Methods: We induced cachexia by xenografting PC3 prostate cancer cells in nu/nu mice. Six weeks later, we counted myonuclei by in vivo microscopic imaging of single live fibres in the extensor digitorum longus muscle (EDL), and the EDL, soleus and tibialis anterior muscles were also harvested for ex vivo histology. Results: The mice lost on average 15% of the whole-body wt. The muscle wet weight of the glycolytic, fast EDL was reduced by 14%, the tibialis anterior by 17%, and the slow, oxidative soleus by 6%. The fibre cross-sectional area in the EDL was reduced by 21% with no loss of myonuclei or any significant reduction in the number of muscle fibres. TUNEL-positive nuclei or fibres with embryonic myosin were rare both in cachectic and control muscles, and haematoxylin-eosin staining revealed no clear signs of muscle pathology. Conclusion: The data suggest that the cachexia induced by xenografted prostate tumours induces a pronounced atrophy not accompanied by a loss of myonuclei or a loss of muscle fibres. Thus, stem cell related treatment might be redundant, and the quest for treatment options should rather focus on intervening with intracellular pathways regulating muscle fibre size. K E Y W O R D Satrophy, cachexia, cancer, myonuclei, skeletal muscle
Significance: The cerebral metabolic rate of oxygen (CMRO 2) is an important indicator of brain function and pathology. Knowledge about its magnitude is also required for proper interpretation of the blood oxygenation level-dependent (BOLD) signal measured with functional MRI. Despite the need for estimating CMRO 2 , no gold standard exists. Traditionally, the estimation of CMRO 2 has been pursued with somewhat indirect approaches combining several different types of measurements with mathematical modeling of the underlying physiological processes. The recent ability to measure the level of oxygen (pO 2) in cortex with two-photon resolution in in vivo conditions has provided a more direct way for estimating CMRO 2 , but has so far only been used to estimate the average CMRO 2 close to cortical penetrating arterioles in rats. Aim: The aim of this study was to propose a method to provide spatial maps of CMRO 2 based on two-photon pO 2 measurements. Approach: The method has two key steps. First, the pO 2 maps are spatially smoothed to reduce the effects of noise in the measurements. Next, the Laplace operator (a double spatial derivative) in two spatial dimensions is applied on the smoothed pO 2 maps to obtain spatially resolved CMRO 2 estimates. Result: The smoothing introduces a bias, and a balance must be found where the effects of the noise are sufficiently reduced without introducing too much bias. In this model-based study, we explored this balance using synthetic model-based data, that is, data where the spatial maps of CMRO 2 were preset and thus known. The corresponding pO 2 maps were found by solving the Poisson equation, which relates CMRO 2 and pO 2. MATLAB code for using the method is provided. Conclusion: Through this model-based study, we propose a method for estimating CMRO 2 with high spatial resolution based on measurements of pO 2 in cerebral cortex.
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