Physiological electric fields induce directional migration of mammalian cranial neural crest cells

Advances in Material-Assisted Electromagnetic Neural Stimulation

Bioelectricity plays a crucial role in organisms, being closely connected to neural activity and physiological processes. Disruptions in the nervous system can lead to chaotic ionic currents at the injured site, causing disturbances in the local cellular microenvironment, impairing biological pathways, and resulting in a loss of neural functions. Electromagnetic stimulation has the ability to generate internal currents, which can be utilized to counter tissue damage and aid in the restoration of movement in paralyzed limbs. By incorporating implanted materials, electromagnetic stimulation can be targeted more accurately, thereby significantly improving the effectiveness and safety of such interventions. Currently, there have been significant advancements in the development of numerous promising electromagnetic stimulation strategies with diverse materials. This review provides a comprehensive summary of the fundamental theories, neural stimulation modulating materials, material application strategies, and pre-clinical therapeutic effects associated with electromagnetic stimulation for neural repair. It offers a thorough analysis of current techniques that employ materials to enhance electromagnetic stimulation, as well as potential therapeutic strategies for future applications.

Harnessing the Stem Cell Niche in Regenerative Medicine: Innovative Avenue to Combat Neurodegenerative Diseases

Regenerative medicine harnesses the body's innate capacity for self-repair to restore malfunctioning tissues and organs. Stem cell therapies represent a key regenerative strategy, but to effectively harness their potential necessitates a nuanced understanding of the stem cell niche. This specialized microenvironment regulates critical stem cell behaviors including quiescence, activation, differentiation, and homing. Emerging research reveals that dysfunction within endogenous neural stem cell niches contributes to neurodegenerative pathologies and impedes regeneration. Strategies such as modifying signaling pathways, or epigenetic interventions to restore niche homeostasis and signaling, hold promise for revitalizing neurogenesis and neural repair in diseases like Alzheimer's and Parkinson's. Comparative studies of highly regenerative species provide evolutionary clues into niche-mediated renewal mechanisms. Leveraging endogenous bioelectric cues and crosstalk between gut, brain, and vascular niches further illuminates promising therapeutic opportunities. Emerging techniques like single-cell transcriptomics, organoids, microfluidics, artificial intelligence, in silico modeling, and transdifferentiation will continue to unravel niche complexity. By providing a comprehensive synthesis integrating diverse views on niche components, developmental transitions, and dynamics, this review unveils new layers of complexity integral to niche behavior and function, which unveil novel prospects to modulate niche function and provide revolutionary treatments for neurodegenerative diseases.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, and are suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and the noise/background associated with the immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, Denoising Convolutional Neural Network (DnCNN), to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8 mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3, 7, 10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly, we found a positive correlation (R2 = 0.926) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, which have been suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and noise/background associated with the Immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, DnCNN, to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3,7,10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly we found a positive correlation (R 2  = 0.933) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Voltage-gated sodium channels: from roles and mechanisms in the metastatic cell behavior to clinical potential as therapeutic targets

During the second half of the last century, the prevalent knowledge recognized the voltage-gated sodium channels (VGSCs) as the proteins responsible for the generation and propagation of action potentials in excitable cells. However, over the last 25 years, new non-canonical roles of VGSCs in cancer hallmarks have been uncovered. Their dysregulated expression and activity have been associated with aggressive features and cancer progression towards metastatic stages, suggesting the potential use of VGSCs as cancer markers and prognostic factors. Recent work has elicited essential information about the signalling pathways modulated by these channels: coupling membrane activity to transcriptional regulation pathways, intracellular and extracellular pH regulation, invadopodia maturation, and proteolytic activity. In a promising scenario, the inhibition of VGSCs with FDA-approved drugs as well as with new synthetic compounds, reduces cancer cell invasion in vitro and cancer progression in vivo. The purpose of this review is to present an update regarding recent advances and ongoing efforts to have a better understanding of molecular and cellular mechanisms on the involvement of both pore-forming α and auxiliary β subunits of VGSCs in the metastatic processes, with the aim at proposing VGSCs as new oncological markers and targets for anticancer treatments.

Quantifying innervation facilitated by deep learning in wound healing

The peripheral nerves (PNs) innervate the dermis and epidermis, which have been suggested to play an important role in wound healing. Several methods to quantify skin innervation during wound healing have been reported. Those usually require multiple observers, are complex and labor-intensive, and noise/background associated with the Immunohistochemistry (IHC) images could cause quantification errors/user bias. In this study, we employed the state-of-the-art deep neural network, DnCNN, to perform pre-processing and effectively reduce the noise in the IHC images. Additionally, we utilized an automated image analysis tool, assisted by Matlab, to accurately determine the extent of skin innervation during various stages of wound healing. The 8mm wound is generated using a circular biopsy punch in the wild-type mouse. Skin samples were collected on days 3,7,10 and 15, and sections from paraffin-embedded tissues were stained against pan-neuronal marker- protein-gene-product 9.5 (PGP 9.5) antibody. On day 3 and day 7, negligible nerve fibers were present throughout the wound with few only on the lateral boundaries of the wound. On day 10, a slight increase in nerve fiber density appeared, which significantly increased on day 15. Importantly we found a positive correlation (R- 2 = 0.933) between nerve fiber density and re-epithelization, suggesting an association between re-innervation and re-epithelization. These results established a quantitative time course of re-innervation in wound healing, and the automated image analysis method offers a novel and useful tool to facilitate the quantification of innervation in the skin and other tissues.

Morphoceuticals: perspectives for discovery of drugs targeting anatomical control mechanisms in regenerative medicine, cancer and aging

Morphoceuticals are a new class of interventions that target the setpoints of anatomical homeostasis for efficient, modular control of growth and form. Here, we focus on a subclass: electroceuticals, which specifically target the cellular bioelectrical interface. Cellular collectives in all tissues form bioelectrical networks via ion channels and gap junctions that process morphogenetic information, controlling gene expression and allowing cell networks to adaptively and dynamically control growth and pattern formation. Recent progress in understanding this physiological control system, including predictive computational models, suggests that targeting bioelectrical interfaces can control embryogenesis and maintain shape against injury, senescence and tumorigenesis. We propose a roadmap for drug discovery focused on manipulating endogenous bioelectric signaling for regenerative medicine, cancer suppression and antiaging therapeutics. Teaser: By taking advantage of the native problem-solving competencies of cells and tissues, a new kind of top-down approach to biomedicine becomes possible. Bioelectricity offers an especially tractable interface for interventions targeting the software of life for regenerative medicine applications.

A machine learning based model accurately predicts cellular response to electric fields in multiple cell types

Many cell types migrate in response to naturally generated electric fields. Furthermore, it has been suggested that the external application of an electric field may be used to intervene in and optimize natural processes such as wound healing. Precise cell guidance suitable for such optimization may rely on predictive models of cell migration, which do not generalize. Here, we present a machine learning model that can forecast directedness of cell migration given a timeseries of previous directedness and electric field values. This model is trained using time series galvanotaxis data of mammalian cranial neural crest cells obtained through time-lapse microscopy of cells cultured at 37 °C in a galvanotaxis chamber at ambient pressure. Next, we show that our modeling approach can be used for a variety of cell types and experimental conditions with very limited training data using transfer learning methods. We adapt the model to predict cell behavior for keratocytes (room temperature, ~ 18–20 °C) and keratinocytes (37 °C) under similar experimental conditions with a small dataset (~ 2–5 cells). Finally, this model can be used to perform in silico studies by simulating cell migration lines under time-varying and unseen electric fields. We demonstrate this by simulating feedback control on cell migration using a proportional–integral–derivative (PID) controller. This data-driven approach provides predictive models of cell migration that may be suitable for designing electric field based cellular control mechanisms for applications in precision medicine such as wound healing.

Direct Current Electric Field Coordinates the Migration of BV2 Microglia via ERK/GSK3β/Cofilin Signaling Pathway

Direct current electric field (DCEF) steers the migration of various neural cells. Microglia, as macrophage of the central nervous system (CNS), however, have not been reported to engage in electrotaxis. Here, we applied electric fields to an in vitro environment and found directional migration of BV2 microglia toward the cathode, in a DCEF strength-dependent manner. Transcriptome analysis then revealed significant changes in the mitogen-activated protein kinase cascades. In terms of mechanism, DCEF coordinated microglia movement by regulating the ERK/GSK3β/cofilin signaling pathway, and PMA (protein kinase C activator) reversed cell migration through intervention of the ERK/GSK3β/cofilin axis. Meanwhile, LiCl (GSK3β inhibitor) showed similar functions to PMA in the electrotaxis of microglia. Furthermore, pharmacological and genetic suppression of GSK3β or cofilin also modulated microglia directional migration under DCEF. Collectively, we discovered the electrotaxis of BV2 microglia and the essential role of the ERK/GSK3β/cofilin axis in regulating cell migration via modulation of F-actin redistribution. This research highlights new insight toward mediating BV2 directional migration and provides potential direction for novel therapeutic strategies of CNS diseases.