The development of more predictive and biologically relevant in vitro assays is predicated on the advancement of versatile cell culture systems which facilitate the functional assessment of the seeded cells. To that end, microscale cantilever technology offers a platform with which to measure the contractile functionality of a range of cell types, including skeletal, cardiac and smooth muscle cells, through assessment of contraction induced substrate bending. Application of multiplexed cantilever arrays provides the means to develop moderate to high-throughput protocols for assessing drug efficacy and toxicity, disease phenotype and progression, as well as neuromuscular and other cell-cell interactions. This manuscript provides the details for fabricating reliable cantilever arrays for this purpose, and the methods required to successfully culture cells on these surfaces. Further description is provided on the steps necessary to perform functional analysis of contractile cell types maintained on such arrays using a novel laser and photo-detector system. The representative data provided highlights the precision and reproducible nature of the analysis of contractile function possible using this system, as well as the wide range of studies to which such technology can be applied. Successful widespread adoption of this system could provide investigators with the means to perform rapid, low cost functional studies in vitro, leading to more accurate predictions of tissue performance, disease development and response to novel therapeutic treatment.
This special issue presents neuroscience from an interdisciplinary perspective. Each research paper in this publication contributes to a singular endeavor: the integration of cognition and computation on biological grounds. ''Pointing at Boundaries'' refers to computing with biological substrates, including alternative ways of modeling action potentials, multi-scale computation, ionic dynamic patterns, and mechanisms of information integration.The topics raised in Pointing at Boundaries contribute to earlier computing research such as biological mathematics and cellular automata [1] and the bio-inspired in silico computing proposed by Wooley et al. [12]. Biological substrates might further inform computer research. Several aspects of biological substrates appear in this special issue: astroglial cells in brain cognitive computing, ionic interactions, cortical mini-columns, and statistical neocortical dynamics models. These biological phenomena reframe earlier computational protocols while suggesting research on biophysical grounds for consciousness research.A biological approach to cognitive computation is based upon structures containing both a substrate (as ionic solutions) and mechanisms (as membrane ion channels) that induce the formation of patterns upon the substrate and manipulate an organism's biological substrate. The papers in this special issue contribute to a hypothesis: a biological substrate and its mechanisms act as a diaphragm to better mark differences, according to a topology with highly configurable neighborhoods. Research into this hypothesis might be as suggestive as the configurability of crystalline symmetry groups capturing spatial neighborhoods in the form of diffraction patterns. In this regard, this publication represents groundwork towards uncovering the theoretical and experimental basis to develop biological substrates and mechanisms as the ionic permeation of membranes. By investigating the biophysical aspects of consciousness, future biophysical computational research might investigate with a variety of physical signal types (chemical, mechanical, and electromagnetic) through the sensory pathways found in the 26 vertebrate cranial nerves or the 12 human cranial nerves [7]. SynopsisIn this issue, the opening paper by Dorian Aur contributes to the conceptualization of brain electrodynamics underlying the formation of action potentials and reveals multiple computational levels in neurons. This paper raises foundational questions and objections to existing standards in neural activity research. Aur applies to computational neuroscience Wegner's [11] interactive computation paradigm. Consequently, Aur formulates a continuous
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