Musculoskeletal adaptations to strength training in frail elderly: a matter of quantity or quality?

BACKGROUND: The improvement in muscle strength generally exceeds the increase in muscle size following strength training in frail elderly, highlighting the complex aetiology of strength deficit in aging. The aim of this study was to investigate the effect of heavy-load strength training on a broad number of factors related to specific strength in frail elderly. METHODS: Thirty-four frail elderly men (n = 18) and women (n = 16) aged 67 to 98 (86 ± 7 years) were randomized to either a group performing strength training twice a week for 10 weeks (ST) or a non-exercising control group (CON). Knee extensor muscle strength was tested as one-repetition maximum (1RM) and isometric maximal voluntary contraction (MVC) torque. Muscle activation was assessed by the interpolated twitch technique, and muscle density [mean Hounsfield units (HU)] and intermuscular adipose tissue (IMAT) by computed tomography scans of the quadriceps femoris. Muscle biopsies from the vastus lateralis were obtained to investigate changes in intramyocellular lipids and single-fibre specific tension. RESULTS: In ST, knee extension 1RM and MVC improved by 17 and 7%, respectively. Muscle cross-sectional area of the quadriceps femoris increased by 7%, accompanied by a 4% increase of muscle density. No changes in IMAT, voluntary activation level, single-fibre specific tension, or lipid content were observed. CONCLUSIONS: In contrast to several previous reports, the improvements in isometric muscle strength and muscle area were in good agreement in the present study. The training-induced increase in muscle density was not due to changes in skeletal muscle lipid content. Instead, the increase in muscle density may reflect increased packing of contractile material or simply an increased ratio of muscle tissue relative to IMAT.

What Is Required for Neuronal Calcium Waves? A Numerical Parameter Study.

Neuronal calcium signals propagating by simple diffusion and reaction with mobile and stationary buffers are limited to cellular microdomains. The distance intracellular calcium signals can travel may be significantly increased by means of calcium-induced calcium release from internal calcium stores, notably the endoplasmic reticulum. The organelle, which can be thought of as a cell-within-a-cell, is able to sequester large amounts of cytosolic calcium ions via SERCA pumps and selectively release them into the cytosol through ryanodine receptor channels leading to the formation of calcium waves. In this study, we set out to investigate the basic properties of such dendritic calcium waves and how they depend on the three parameters dendrite radius, ER radius and ryanodine receptor density in the endoplasmic membrane. We demonstrate that there are stable and abortive regimes for calcium waves, depending on the above morphological and physiological parameters. In stable regimes, calcium waves can travel across long dendritic distances, similar to electrical action potentials. We further observe that abortive regimes exist, which could be relevant for spike-timing dependent plasticity, as travel distances and wave velocities vary with changing intracellular architecture. For some of these regimes, analytic functions could be derived that fit the simulation data. In parameter spaces, that are non-trivially influenced by the three-dimensional calcium concentration profile, we were not able to derive such a functional description, demonstrating the mathematical requirement to model and simulate biochemical signaling in three-dimensional space.

Spine-to-Dendrite Calcium Modeling Discloses Relevance for Precise Positioning of Ryanodine Receptor-Containing Spine Endoplasmic Reticulum.

The endoplasmic reticulum (ER) forms a complex endomembrane network that reaches into the cellular compartments of a neuron, including dendritic spines. Recent work discloses that the spine ER is a dynamic structure that enters and leaves spines. While evidence exists that ER Ca2+ release is involved in synaptic plasticity, the role of spine ER morphology remains unknown. Combining a new 3D spine generator with 3D Ca2+ modeling, we addressed the relevance of ER positioning on spine-to-dendrite Ca2+ signaling. Our simulations, which account for Ca2+ exchange on the plasma membrane and ER, show that spine ER needs to be present in distinct morphological conformations in order to overcome a barrier between the spine and dendritic shaft. We demonstrate that RyR-carrying spine ER promotes spine-to-dendrite Ca2+ signals in a position-dependent manner. Our simulations indicate that RyR-carrying ER can initiate time-delayed Ca2+ reverberation, depending on the precise position of the spine ER. Upon spine growth, structural reorganization of the ER restores spine-to-dendrite Ca2+ communication, while maintaining aspects of Ca2+ homeostasis in the spine head. Our work emphasizes the relevance of precise positioning of RyR-containing spine ER in regulating the strength and timing of spine Ca2+ signaling, which could play an important role in tuning spine-to-dendrite Ca2+ communication and homeostasis.

Generating Neuron Geometries for Detailed Three-Dimensional Simulations Using AnaMorph.

Generating realistic and complex computational domains for numerical simulations is often a challenging task. In neuroscientific research, more and more one-dimensional morphology data is becoming publicly available through databases. This data, however, only contains point and diameter information not suitable for detailed three-dimensional simulations. In this paper, we present a novel framework, AnaMorph, that automatically generates water-tight surface meshes from one-dimensional point-diameter files. These surface triangulations can be used to simulate the electrical and biochemical behavior of the underlying cell. In addition to morphology generation, AnaMorph also performs quality control of the semi-automatically reconstructed cells coming from anatomical reconstructions. This toolset allows an extension from the classical dimension-reduced modeling and simulation of cellular processes to a full three-dimensional and morphology-including method, leading to novel structure-function interplay studies in the medical field. The developed numerical methods can further be employed in other areas where complex geometries are an essential component of numerical simulations.

Anatomically Detailed and Large-Scale Simulations Studying Synapse Loss and Synchrony Using NeuroBox.

The morphology of neurons and networks plays an important role in processing electrical and biochemical signals. Based on neuronal reconstructions, which are becoming abundantly available through databases such as NeuroMorpho.org, numerical simulations of Hodgkin-Huxley-type equations, coupled to biochemical models, can be performed in order to systematically investigate the influence of cellular morphology and the connectivity pattern in networks on the underlying function. Development in the area of synthetic neural network generation and morphology reconstruction from microscopy data has brought forth the software tool NeuGen. Coupling this morphology data (either from databases, synthetic, or reconstruction) to the simulation platform UG 4 (which harbors a neuroscientific portfolio) and VRL-Studio, has brought forth the extendible toolbox NeuroBox. NeuroBox allows users to perform numerical simulations on hybrid-dimensional morphology representations. The code basis is designed in a modular way, such that e.g., new channel or synapse types can be added to the library. Workflows can be specified through scripts or through the VRL-Studio graphical workflow representation. Third-party tools, such as ImageJ, can be added to NeuroBox workflows. In this paper, NeuroBox is used to study the electrical and biochemical effects of synapse loss vs. synchrony in neurons, to investigate large morphology data sets within detailed biophysical simulations, and used to demonstrate the capability of utilizing high-performance computing infrastructure for large scale network simulations. Using new synapse distribution methods and Finite Volume based numerical solvers for compartment-type models, our results demonstrate how an increase in synaptic synchronization can compensate synapse loss at the electrical and calcium level, and how detailed neuronal morphology can be integrated in large-scale network simulations.