Action potential alterations induced by single F11 neuronal cell loading

In Vitro Models for Peripheral Nerve Regeneration

Peripheral nerve injury (PNI) resulting in lesions is highly prevalent clinically, but current therapeutic approaches fail to provide satisfactory outcomes in many patients. While peripheral nerves have intrinsic regenerative capacity, the regenerative capabilities of peripheral nerves are often insufficient to restore full functionality. This highlights an unmet need for developing more effective strategies to repair damaged peripheral nerves and improve regenerative success. Consequently, researchers are actively exploring a variety of therapeutic strategies, encompassing the local delivery of trophic factors or bioactive molecules, the design of advanced biomaterials that interact with regenerating axons, and augmentation with nerve guidance conduits or complex prostheses. However, clinical translation of these technologies remains limited, emphasizing the need for continued research on peripheral nerve regeneration modalities that can enhance functional restoration. Experimental models that accurately recapitulate key aspects of peripheral nerve injury and repair biology can accelerate therapeutic development by enabling systematic testing of new techniques. Advancing regenerative therapies for PNI requires bridging the gap between basic science discoveries and clinical application. This review discusses different in vitro models of peripheral nerve injury and repair, including their advantages, limitations, and potential applications.

Short-term plasticity as 'energetic memory' of ion channel components of action potential

Information transfer in the nervous system is traditionally understood by the transmission of action potentials along neuronal dendrites, with ion channels in the membrane as the basic unit operator for their creation and propagation. We present here a new model for the multiphysics behaviour of ion channels and the action potential dynamics in nervous and other signal-transmitting systems. This model is based on the long-term suppression of an action potential as a response to mechanical input. While other models focus on electrical aspects of the action potential, an increasing body of experiments highlights its electro-mechanical nature and points in particular towards an alteration of the action potential when subjected to a mechanical input. Here, we propose a new phenomenological framework able to capture the mechanical aspect of ion channel dynamics and the resulting effect on the overall electrophysiology of the membrane. The model is introduced here through a set of coupled differential equations that describe the system while agreeing with the general findings of the experiments that support an electro-mechanical model. It also confirms that transient quasi-static mechanical loads reversibly affect the amplitude and rate of change of neuronal action potentials, which are smaller and slower under indentation loading conditions. Changes after the loading release are also reversible, albeit on a different time scale.

Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks

A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.

Synapses without tension fail to fire in an in vitro network of hippocampal neurons

Neurons in the brain communicate with each other at their synapses. It has long been understood that this communication occurs through biochemical processes. Here, we reveal that mechanical tension in neurons is essential for communication. Using in vitro rat hippocampal neurons, we find that 1) neurons become tout/tensed after forming synapses resulting in a contractile neural network, and 2) without this contractility, neurons fail to fire. To measure time evolution of network contractility in 3D (not 2D) extracellular matrix, we developed an ultrasensitive force sensor with 1 nN resolution. We employed Multi-Electrode Array and iGluSnFR, a glutamate sensor, to quantify neuronal firing at the network and at the single synapse scale, respectively. When neuron contractility is relaxed, both techniques show significantly reduced firing. Firing resumes when contractility is restored. This finding highlights the essential contribution of neural contractility in fundamental brain functions and has implications for our understanding of neural physiology.

Cations Control Lipid Bilayer Memcapacitance Associated with Long-Term Potentiation

Phospholipid bilayers can be described as capacitors whose capacitance per unit area (specific capacitance, Cm) is determined by their thickness and dielectric constant─independent of applied voltage. It is also widely assumed that the Cm of membranes can be treated as a "biological constant". Recently, using droplet interface bilayers (DIBs), it was shown that zwitterionic phosphatidylcholine (PC) lipid bilayers can act as voltage-dependent, nonlinear memory capacitors, or memcapacitors. When exposed to an electrical "training" stimulation protocol, capacitive energy storage in lipid membranes was enhanced in the form of long-term potentiation (LTP), which enables biological learning and long-term memory. LTP was the result of membrane restructuring and the progressive asymmetric distribution of ions across the lipid bilayer during training, which is analogous, for example, to exponential capacitive energy harvesting from self-powered nanogenerators. Here, we describe how LTP could be produced from a membrane that is continuously pumped into a nonequilibrium steady state, altering its dielectric properties. During this time, the membrane undergoes static and dynamic changes that are fed back to the system's potential energy, ultimately resulting in a membrane whose modified molecular structure supports long-term memory storage and LTP. We also show that LTP is very sensitive to different salts (KCl, NaCl, LiCl, and TmCl3), with LiCl and TmCl3 having the most profound effect in depressing LTP, relative to KCl. This effect is related to how the different cations interact with the bilayer zwitterionic PC lipid headgroups primarily through electric-field-induced changes to the statistically averaged orientations of water dipoles at the bilayer headgroup interface.

Development of a mammalian neurosensory full-thickness skin equivalent and its application to screen sensitizing stimuli

Human skin equivalents (HSEs) are an increasingly popular research tool due to limitations associated with animal testing for dermatological research. They recapitulate many aspects of skin structure and function, however, many only contain two basic cell types to model dermal and epidermal compartments, which limits their application. We describe advances in the field skin tissue modeling to produce a construct containing sensory-like neurons that is responsive to known noxious stimuli. Through incorporation of mammalian sensory-like neurons, we were able to recapitulate aspects of the neuroinflammatory response including secretion of substance P and a range of pro-inflammatory cytokines in response to a well-characterized neurosensitizing agent: capsaicin. We observed that neuronal cell bodies reside in the upper dermal compartment with neurites extending toward the keratinocytes of the stratum basale where they exist in close proximity to one another. These data suggest that we are able to model aspects of the neuroinflammatory response that occurs during exposure to dermatological stimuli including therapeutics and cosmetics. We propose that this skin construct can be considered a platform technology with a wide range of applications including screening of actives, therapeutics, modeling of inflammatory skin diseases, and fundamental approaches to probe underlying cell and molecular mechanisms.

Modelling transcranial ultrasound neuromodulation: an energy-based multiscale framework

Several animal and human studies have now established the potential of low intensity, low frequency transcranial ultrasound (TUS) for non-invasive neuromodulation. Paradoxically, the underlying mechanisms through which TUS neuromodulation operates are still unclear, and a consensus on the identification of optimal sonication parameters still remains elusive. One emerging hypothesis based on thermodynamical considerations attributes the acoustic-induced nerve activity alterations to the mechanical energy and/or entropy conversions occurring during TUS action. Here, we propose a multiscale modelling framework to examine the energy states of neuromodulation under TUS. First, macroscopic tissue-level acoustic simulations of the sonication of a whole monkey brain are conducted under different sonication protocols. For each one of them, mechanical loading conditions of the received waves in the anterior cingulate cortex region are recorded and exported into a microscopic cell-level 3D viscoelastic finite element model of neuronal axon embedded extracellular medium. Pulse-averaged elastically stored and viscously dissipated energy rate densities during axon deformation are finally computed under different sonication incident angles and are mapped against distinct combinations of sonication parameters of the TUS. The proposed multiscale framework allows for the analysis of vibrational patterns of the axons and its comparison against the spectrograms of stimulating ultrasound. The results are in agreement with literature data on neuromodulation, demonstrating the potential of this framework to identify optimised acoustic parameters in TUS neuromodulation. The proposed approach is finally discussed in the context of multiphysics energetic considerations, argued here to be a promising avenue towards a scalable framework for TUS in silico predictions. STATEMENT OF SIGNIFICANCE: Low-intensity transcranial ultrasound (TUS) is poised to become a leading neuromodulation technique for the treatment of neurological disorders. Paradoxically, how it operates at the cellular scale remains unknown, hampering progress in personalised treatment. To this end, models of the multiphysics of neurons able to upscale results to the organ scale are required. We propose here to achieve this by considering an axon submitted to an ultrasound wave extracted from a simulation at the organ scale. Doing so, information pertaining to both stored and dissipated axonal energies can be extracted for a given head/brain morphology. This two-scale multiphysics energetic approach is a promising scalable framework for in silico predictions in the context of personalised TUS treatment.

Voltage-Driven Alterations to Neuron Viscoelasticity

Background

The consideration of neurons as coupled mechanical-electrophysiological systems is supported by a growing body of experimental evidence, including observations that cell membranes mechanically deform during the propagation of an action potential. However, the short-term (seconds to minutes) influence of membrane voltage on the mechanical properties of a neuron at the single-cell level remains unknown.

Materials and Methods

Here, we use microscale dynamic mechanical analysis to demonstrate that changes in membrane potential induce changes in the mechanical properties of individual neurons. We simultaneously measured the membrane potential and mechanical properties of individual neurons through a multiphysics single-cell setup. Membrane voltage of a single neuron was measured through whole-cell patch clamp. The mechanical properties of the same neuron were measured through a nanoindenter, which applied a dynamic indentation to the neuron at different frequencies.

Results

Neuronal storage and loss moduli were lower for positive voltages than negative voltages.

Conclusion

The observed effects of membrane voltage on neuron mechanics could be due to piezoelectric or flexoelectric effects and altered ion distributions under the applied voltage. Such effects could change cell mechanics by changing the intermolecular interactions between ions and the various biomolecules within the membrane and cytoskeleton.

The thermodynamic theory of action potential propagation: a sound basis for unification of the physics of nerve impulses

The thermodynamic theory of action potential propagation challenges the conventional understanding of the nerve signal as an exclusively electrical phenomenon. Often misunderstood as to its basic tenets and predictions, the thermodynamic theory is virtually ignored in mainstream neuroscience. Addressing a broad audience of neuroscientists, we here attempt to stimulate interest in the theory. We do this by providing a concise overview of its background, discussion of its intimate connection to Albert Einstein's treatment of the thermodynamics of interfaces and outlining its potential contribution to the building of a physical brain theory firmly grounded in first principles and the biophysical reality of individual nerve cells. As such, the paper does not attempt to advocate the superiority of the thermodynamic theory over any other approach to model the nerve impulse, but is meant as an open invitation to the neuroscience community to experimentally test the assumptions and predictions of the theory on their validity.

On the Coupling between Mechanical Properties and Electrostatics in Biological Membranes

Cell membrane structure is proposed as a lipid matrix with embedded proteins, and thus, their emerging mechanical and electrostatic properties are commanded by lipid behavior and their interconnection with the included and absorbed proteins, cytoskeleton, extracellular matrix and ionic media. Structures formed by lipids are soft, dynamic and viscoelastic, and their properties depend on the lipid composition and on the general conditions, such as temperature, pH, ionic strength and electrostatic potentials. The dielectric constant of the apolar region of the lipid bilayer contrasts with that of the polar region, which also differs from the aqueous milieu, and these changes happen in the nanometer scale. Besides, an important percentage of the lipids are anionic, and the rest are dipoles or higher multipoles, and the polar regions are highly hydrated, with these water molecules forming an active part of the membrane. Therefore, electric fields (both, internal and external) affects membrane thickness, density, tension and curvature, and conversely, mechanical deformations modify membrane electrostatics. As a consequence, interfacial electrostatics appears as a highly important parameter, affecting the membrane properties in general and mechanical features in particular. In this review we focus on the electromechanical behavior of lipid and cell membranes, the physicochemical origin and the biological implications, with emphasis in signal propagation in nerve cells.