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Functional Properties of Muscle
Published in Nassir H. Sabah, Neuromuscular Fundamentals, 2020
The relation between stoke volume and end-diastolic volume (Figure 10.19) is essentially the same as the length-tension relation for skeletal muscle (Figure 10.5) but with the axes relabeled in terms of parameters appropriate for the heart. The resting length in the case of cardiac muscle is on the steeper part of the curve, where the active contraction increases rapidly with sarcomere length, rather than near the maximum of curve as in the case of skeletal muscle. In addition, a significant factor in increasing the force of contraction with sarcomere length in the case of cardiac muscle, which makes the curve of Figure 10.19 steeper, is stretch activation (Section 10.3.1). Another factor is that the amount of Ca2+ released into the cytoplasm during excitation-contraction coupling is less than that needed for saturation of troponin C. Hence, the enhanced Ca2+ binding to troponin C that occurs with increasing sarcomere lengths increases the force of contraction with muscle fiber length.
Striated MusclesSkeletal and Cardiac Muscles
Published in Peter Kam, Ian Power, Michael J. Cousins, Philip J. Siddal, Principles of Physiology for the Anaesthetist, 2020
Peter Kam, Ian Power, Michael J. Cousins, Philip J. Siddal
The sequence of events in excitation–contraction coupling in a skeletal muscle is as follows: Depolarization of the T-tubule alters the conformation of the dihydropyridine receptor, a subtype of voltage-gated L-type Ca++ channels. The dihydropyridine receptor is in physical contact with the ryanodine receptor.
Genetically Determined Ventricular Arrhythmias
Published in Andrea Natale, Oussama M. Wazni, Kalyanam Shivkumar, Francis E. Marchlinski, Handbook of Cardiac Electrophysiology, 2020
Houman Khakpour, Jason S. Bradfield
Two variants of CPVT have been described based on their genetic mutation and mode of transmission. CPVT1 has a mutation in the ryanodine 2 receptor gene (RyR2) which leads to delayed afterdepolarization (DAD)-induced extrasystolic activity from defective calcium handling. The resulting transmural dispersion of repolarization provides the substrate for the development of re-entrant tachyarrhythmias.13,76 The RyR2 gene shows autosomal dominant inheritance. CPVT2 is defined by a mutation in the calsequestrin (CASQ2) gene and has an autosomal recessive inheritance. Other unidentified genes are also believed to result in CPVT. The ryanodine receptor is located on the sarcoplasmic reticulum and allows the release of calcium into the cell, thus facilitating excitation contraction coupling in the myocardium. Calsequestrin gene mutations interfere with sarcoplasmic calcium storage.13
Proteomic profiling of fatty acid binding proteins in muscular dystrophy
Published in Expert Review of Proteomics, 2020
Paul Dowling, Stephen Gargan, Margit Zweyer, Dieter Swandulla, Kay Ohlendieck
The systematic application of comparative proteomics, using both two-dimensional gel electrophoresis and/or liquid chromatography for the efficient separation of muscle protein constituents prior to mass spectrometric analysis, has led to the establishment of a comprehensive pathobiochemical signature of X-linked muscular dystrophy [67]. Significant proteome-wide changes were identified for a large variety of muscle proteins involved in excitation-contraction coupling, ion homeostasis, the acto-myosin apparatus and associated sarcomeric components, energy metabolism, the cytoskeletal network, the extracellular matrix and the cellular stress response, as extensively reviewed [68–71]. Representative studies that have identified significant alterations in tissue-associated FABP expression levels due to dystrophin deficiency are listed in Table 3. More comprehensive listings of general biomarker candidates of dystrophinopathy have been recently published [68,71].
Proteomic profiling of giant skeletal muscle proteins
Published in Expert Review of Proteomics, 2019
Sandra Murphy, Paul Dowling, Margit Zweyer, Dieter Swandulla, Kay Ohlendieck
Skeletal muscle proteins with very high molecular masses are especially associated with the scaffolding, stabilizing and signalling elements of the contractile apparatus, the extra-sarcomeric cytoskeletal networks and the excitation-contraction coupling complex [11–14]. This includes titin of apparent 3,904 kDa [15], nebulin of apparent 986 kDa [16] and obscurin of apparent 779 kDa [17] of the sarcomeric units that mediate and stabilize the contraction-relaxation cycle of the acto-myosin apparatus [18], the non-sarcomeric cytoskeletal protein plectin of apparent 506 kDa [19], the membrane cytoskeletal protein dystrophin of apparent 426 kDa that provides the linkage between the actin cytoskeleton and the extracellular matrix [20], and the sarcoplasmic reticulum ryanodine receptor Ca2+-release channel of apparent 565 kDa that plays a key regulatory role in Ca2+-induced fibre contraction [21]. In addition, muscle-associated proteins with a high molecular mass are the scaffolding protein desmoyokin, the basal lamina components laminin and proteoglycans, the fibrillins, fibronectin and collagens of the extracellular matrix, the actin-binding protein filamin, the cytoskeletal proteins talin and spectrin, the metabolic enzyme fatty acid synthase, the sarcolemmal protein dysferlin and a variety of myosin heavy chain isoforms.
Introduction to biological complexity as a missing link in drug discovery
Published in Expert Opinion on Drug Discovery, 2018
Gary A. Gintant, Christopher H. George
The ultimate goal of preclinical assays is to accurately predict a drug’s clinical therapeutic efficacy and safety. As Swinney notes, “the more relevant the system is to physiology, the better it will predict the clinical success” [12]. The use of the term “physiology” here is key; physiology represents the functional coalescence of interlocking biological processes in a network architecture that involves the multi-layering of components (Figures 2 and 3). In this context, the prediction of outcome in response to a given drug treatment or pathological disruption is difficult since the network gives rise to a number of characteristics that define the nonlinear behavior of the linked processes (e.g. entrainment, emergence, resilience, robustness, fragility) [34–42]. It is not practically possible at present to consider and measure all of the variables and connections that contribute to such system nonlinearity. In Figure 2, we use the example of β-AR signaling to illustrate a process where the output (i.e. downstream phosphorylation of multiple proteins) is dependent on multiple network connections. Figure 3 depicts how the release of Ca2+ from the sarcoplasmic reticulum (SR) through intracellular Ca2+ release channels (ryanodine receptors) is enmeshed in the process of excitation–contraction coupling (ECC) [43] which is regulated by the alignment of “horizontal” and “vertical” network elements. We return to the issue of network alignment in Section 4.