Mechanotransduction is a process where cells sense their surroundings and convert the physical forces in their environment into an appropriate response. Calcium plays a crucial role in the translation of such forces to biochemical signals that control various biological processes fundamental in muscle development. The mechanical stimulation of muscle cells may for example result from stretch, electric and magnetic stimulation, shear stress, and altered gravity exposure. The response, mainly involving changes in intracellular calcium concentration then leads to a cascade of events by the activation of downstream signaling pathways. The key calcium-dependent pathways described here include the nuclear factor of activated T cells (NFAT) and mitogen-activated protein kinase (MAPK) activation. The subsequent effects in cellular homeostasis consist of cytoskeletal remodeling, cell cycle progression, growth, differentiation, and apoptosis, all necessary for healthy muscle development, repair, and regeneration. A deregulation from the normal process due to disuse, trauma, or disease can result in a clinical condition such as muscle atrophy, which entails a significant loss of muscle mass. In order to develop therapies against such diseased states, we need to better understand the relevance of calcium signaling and the downstream responses to mechanical forces in skeletal muscle. The purpose of this review is to discuss in detail how diverse mechanical stimuli cause changes in calcium homeostasis by affecting membrane channels and the intracellular stores, which in turn regulate multiple pathways that impart these effects and control the fate of muscle tissue.

/pdf/calcium-s-role-in-mechanotransduction-during-muscle-1ndvz8tyih.pdf

Calcium's Role in Mechanotransduction during Muscle Development

A comprehensive review of spatiotemporal pattern formation in systems driven away from equilibrium is presented, with emphasis on comparisons between theory and quantitative experiments. Examples include patterns in hydrodynamic systems such as thermal convection in pure fluids and binary mixtures, Taylor-Couette flow, parametric-wave instabilities, as well as patterns in solidification fronts, nonlinear optics, oscillatory chemical reactions and excitable biological media. The theoretical starting point is usually a set of deterministic equations of motion, typically in the form of nonlinear partial differential equations. These are sometimes supplemented by stochastic terms representing thermal or instrumental noise, but for macroscopic systems and carefully designed experiments the stochastic forces are often negligible. An aim of theory is to describe solutions of the deterministic equations that are likely to be reached starting from typical initial conditions and to persist at long times. A unified description is developed, based on the linear instabilities of a homogeneous state, which leads naturally to a classification of patterns in terms of the characteristic wave vector q0 and frequency ω0 of the instability. Type Is systems (ω0=0, q0≠0) are stationary in time and periodic in space; type IIIo systems (ω0≠0, q0=0) are periodic in time and uniform in space; and type Io systems (ω0≠0, q0≠0) are periodic in both space and time. Near a continuous (or supercritical) instability, the dynamics may be accurately described via "amplitude equations," whose form is universal for each type of instability. The specifics of each system enter only through the nonuniversal coefficients. Far from the instability threshold a different universal description known as the "phase equation" may be derived, but it is restricted to slow distortions of an ideal pattern. For many systems appropriate starting equations are either not known or too complicated to analyze conveniently. It is thus useful to introduce phenomenological order-parameter models, which lead to the correct amplitude equations near threshold, and which may be solved analytically or numerically in the nonlinear regime away from the instability. The above theoretical methods are useful in analyzing "real pattern effects" such as the influence of external boundaries, or the formation and dynamics of defects in ideal structures. An important element in nonequilibrium systems is the appearance of deterministic chaos. A greal deal is known about systems with a small number of degrees of freedom displaying "temporal chaos," where the structure of the phase space can be analyzed in detail. For spatially extended systems with many degrees of freedom, on the other hand, one is dealing with spatiotemporal chaos and appropriate methods of analysis need to be developed. In addition to the general features of nonequilibrium pattern formation discussed above, detailed reviews of theoretical and experimental work on many specific systems are presented. These include Rayleigh-Benard convection in a pure fluid, convection in binary-fluid mixtures, electrohydrodynamic convection in nematic liquid crystals, Taylor-Couette flow between rotating cylinders, parametric surface waves, patterns in certain open flow systems, oscillatory chemical reactions, static and dynamic patterns in biological media, crystallization fronts, and patterns in nonlinear optics. A concluding section summarizes what has and has not been accomplished, and attempts to assess the prospects for the future.

/pdf/pattern-formation-outside-of-equilibrium-1601b9znum.pdf

Pattern formation outside of equilibrium

This book is the second of two volumes in a series on terrestrial and marine comparisons, focusing on the temporal complement of the earlier spatial analysis of patchiness and pattern (Levin et al. 1993). The issue of the relationships among pattern, scale, and patchiness has been framed forcefully in John Steele’s writings of two decades (e.g., Steele 1978). There is no pattern without an observational frame. In the words of Nietzsche, “There are no facts… only interpretations.”

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.2307/1941447

The Problem of Pattern and Scale in Ecology: The Robert H. MacArthur Award Lecture

In systematic searches for embryonic lethal mutants of Drosophila melanogaster we have identified 15 loci which when mutated alter the segmental pattern of the larva. These loci probably represent the majority of such genes in Drosophila. The phenotypes of the mutant embryos indicate that the process of segmentation involves at least three levels of spatial organization: the entire egg as developmental unit, a repeat unit with the length of two segments, and the individual segment.

Mutations affecting segment number and polarity in Drosophila

1980 Preface * 1999 Preface * 1999 Acknowledgements * Introduction * 1 Circular Logic * 2 Phase Singularities (Screwy Results of Circular Logic) * 3 The Rules of the Ring * 4 Ring Populations * 5 Getting Off the Ring * 6 Attracting Cycles and Isochrons * 7 Measuring the Trajectories of a Circadian Clock * 8 Populations of Attractor Cycle Oscillators * 9 Excitable Kinetics and Excitable Media * 10 The Varieties of Phaseless Experience: In Which the Geometrical Orderliness of Rhythmic Organization Breaks Down in Diverse Ways * 11 The Firefly Machine 12 Energy Metabolism in Cells * 13 The Malonic Acid Reagent ('Sodium Geometrate') * 14 Electrical Rhythmicity and Excitability in Cell Membranes * 15 The Aggregation of Slime Mold Amoebae * 16 Numerical Organizing Centers * 17 Electrical Singular Filaments in the Heart Wall * 18 Pattern Formation in the Fungi * 19 Circadian Rhythms in General * 20 The Circadian Clocks of Insect Eclosion * 21 The Flower of Kalanchoe * 22 The Cell Mitotic Cycle * 23 The Female Cycle * References * Index of Names * Index of Subjects

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/596B270197FE27DE5FABB598B6210622/S0025557200150892a.pdf/div-class-title-span-class-italic-the-geometry-of-biological-time-span-by-a-t-winfree-pp-544-dm68-corrected-second-printing-1990-isbn-3-540-52528-9-springer-div.pdf

The geometry of biological time , by A. T. Winfree. Pp 544. DM68. Corrected Second Printing 1990. ISBN 3-540-52528-9 (Springer)

One of the elementary processes in morphogenesis is the formation of a spatial pattern of tissue structures, starting from almost homogeneous tissue. It will be shown that relatively simple molecular mechanisms based on auto- and cross catalysis can account for a primary pattern of morphogens to determine pattern formation of the tissue. The theory is based on short range activation, long range inhibition, and a distinction between activator and inhibitor concentrations on one hand, and the densities of their sources on the other. While source density is expected to change slowly, e.g. as an effect of cell differentiation, the concentration of activators and inhibitors can change rapidly to establish the primary pattern; this results from auto- and cross catalytic effects on the sources, spreading by diffusion or other mechanisms, and degradation. Employing an approximative equation, a criterium is derived for models, which lead to a striking pattern, starting from an even distribution of morphogens, and assuming a shallow source gradient. The polarity of the pattern depends on the direction of the source gradient, but can be rather independent of other features of source distribution. Models are proposed which explain size regulation (constant proportion of the parts of the pattern irrespective of total size). Depending on the choice of constants, aperiodic patterns, implying a one-to-one correlation between morphogen concentration and position in the tissue, or nearly periodic patterns can be obtained. The theory can be applied not only to multicellular tissues, but also to intracellular differentiation, e.g. of polar cells. The theory permits various molecular interpretations. One of the simplest models involves bimolecular activation and monomolecular inhibition. Source gradients may be substituted by, or added to, sink gradients, e.g. of degrading enzymes. Inhibitors can be substituted by substances required for, and depleted by activation. Sources may be either synthesizing systems or particulate structures releasing activators and inhibitors. Calculations by computer are presented to exemplify the main features of the theory proposed. The theory is applied to quantitative data on hydra — a suitable one-dimensional model for pattern formation — and is shown to account for activation and inhibition of secondary head formation.

/pdf/a-theory-of-biological-pattern-formation-1321dzdm5p.pdf

A theory of biological pattern formation.

The development of higher organisms is controlled by a complex network of biochemical reactions that are under genetic control The aim of the seminar is to demonstrate that it is possible to formulate models in a mathematical precise way that describe essential steps in spite of the appearing complexity of this process Many of these models have found meanwhile direct support by molecular-genetic experiments By computer simulations it will be shown that the models describe precisely the regulatory phenomena as they have been experimentally observed

Models of biological pattern formation

Summary In 1972, we proposed a theory of biological pattern formation in which concentration maxima of pattern forming substances are generated through local selfenhancement in conjunction with long range inhibition. Since then, much evidence in various developmental systems has confirmed the importance of autocatalytic feedback loops combined with inhibitory interaction. Examples are found in the formation of embryonal organizing regions, in segmentation, in the polarization of individual cells, and in gene activation. By computer simulations, we have shown that the theory accounts for much of the regulatory phenomena observed, including signalling to regenerate removed parts. These selfregulatory features contribute to making development robust and error-tolerant. Furthermore, the resulting pattern is, to a large extent, independent of the details provided by initial conditions and inducing signals. BioEssays 22:753‐760, 2000. fl 2000 John Wiley & Sons, Inc.

/pdf/pattern-formation-by-local-self-activation-and-lateral-5gli5h0kf8.pdf

Pattern formation by local self-activation and lateral inhibition.

The reliable development of highly complex organisms is an intriguing and fascinating problem. The genetic material is, as a rule, the same in each cell of an organism. How then do cells, under the influence of their common genes, produce spatial patterns? Simple models are discussed that describe the generation of patterns out of an initially nearly homogeneous state. They are based on nonlinear interactions of at least two chemicals and on their diffusion. The concepts of local autocatalysis and of long-range inhibition play a fundamental role. Numerical simulations show that the models account for many basic biological observations such as the regeneration of a pattern after excision of tissue or the production of regular (or nearly regular) arrays of organs during (or after) completion of growth. Very complex patterns can be generated in a reproducible way by hierarchical coupling of several such elementary reactions. Applications to animal coats and to the generation of polygonally shaped patterns are provided. It is further shown how to generate a strictly periodic pattern of units that themselves exhibit a complex and polar fine structure. This is illustrated by two examples: the assembly of photoreceptor cells in the eye of Drosophila and the positioning of leaves and axillary buds in a growing shoot. In both cases, the substructures have to achieve an internal polarity under the influence of some primary pattern-forming system existing in the fly's eye or in the plant. The fact that similar models can describe essential steps in organisms as distantly related as animals and plants suggests that they reveal some universal mechanisms.

/pdf/biological-pattern-formation-from-basic-mechanisms-to-1q6xpucrm2.pdf

Biological pattern formation: from basic mechanisms to complex structures

A model is proposed for an amplification step in chemotactically sensitive cells or growth cones that accounts for their extraordinary directional sensitivity. It is assumed that cells have an intrinsic pattern forming system that generates the signals for extension of filopods and lamellipods. An external signal such as a graded cue is assumed to impose some directional preference onto the pattern formed. According to the model, a saturating, self-enhancing reaction is coupled with two antagonistic reactions. One antagonist equilibrates rapidly over the whole cell, causing competition between different surface elements of the cell cortex for activation. It will be won by those cortical regions of the cell that are exposed to the highest concentrations of the external graded cues. The second antagonistic reaction is assumed to act more locally and has a longer time constant. It causes a destabilization of peaks after they have formed. While the total activated area on the cell surface is maintained, the disappearance of some hot spots allows the formation of new ones, preferentially at positions specified by the actual external guiding signal. Computer simulations show that the model accounts for the highly dynamic behaviour of chemotactic cells and growth cones. In the absence of external signals, maxima of the internal signals emerge at random positions and disappear after some time. Travelling waves or oscillations in counter phase can emerge on the cell cortex, in agreement with observations reported in the literature. In other ranges of parameters, the model accounts for the generation of a stable cell polarity.

/pdf/orientation-of-chemotactic-cells-and-growth-cones-models-and-1jnaju6ete.pdf

Orientation of chemotactic cells and growth cones: models and mechanisms.

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