Suspended Silicon Microphotodiodes for Electrochemical and Biological Applications

Local electric stimulation of tissues and cells has gained importance as therapeutic alternative in the treatment of many diseases. These alternatives aim to deliver a less invasively stimuli in liquid media, making imperative the development of versatile micro‐ and nanoscale solutions for wireless actuation. Here, a simple microfabrication process to produce suspended silicon microphotodiodes that can be activated by visible light to generate local photocurrents in their surrounding medium is presented. Electrical characterization using electrical probes confirms their diode behavior. To demonstrate their electrochemical performance, an indirect test is implemented in solution through photoelectrochemical reactions controlled by a white‐LED lamp. Furthermore, their effects on biological systems are observed in vitro using mouse primary neurons in which the suspended microphotodiodes are activated periodically with white‐LED lamp, bringing out observable morphological changes in neuronal processes. The results demonstrate a simplified and cost‐effective wireless tool for photovoltaic current generation in liquid media at the microscale.     

A Leaky‐Integrate‐and‐Fire Neuron Analog Realized with a Mott Insulator

During the last half century, the tremendous development of computers based on von Neumann architecture has led to the revolution of the information technology. However, von Neumann computers are outperformed by the mammal brain in numerous data‐processing applications such as pattern recognition and data mining. Neuromorphic engineering aims to mimic brain‐like behavior through the implementation of artificial neural networks based on the combination of a large number of artificial neurons massively interconnected by an even larger number of artificial synapses. In order to effectively implement artificial neural networks directly in hardware, it is mandatory to develop artificial neurons and synapses. A promising advance has been made in recent years with the introduction of the components called memristors that might implement synaptic functions. In contrast, the advances in artificial neurons have consisted in the implementation of silicon‐based circuits. However, so far, a single‐component artificial neuron that will bring an improvement comparable to what memristors have brought to synapses is still missing. Here, a simple two‐terminal device is introduced, which can implement the basic functions leaky integrate and fire of spiking neurons. Remarkably, it has been found that it is realized by the behavior of strongly correlated narrow‐gap Mott insulators subject to electric pulsing.     

Lithium Enhances the GABAergic Synaptic Activities on the Hypothalamic Preoptic Area (hPOA) Neurons

Lithium (Li⁺) salt is widely used as a therapeutic agent for treating neurological and psychiatric disorders. Despite its therapeutic effects on neurological and psychiatric disorders, it can also disturb the neuroendocrine axis in patients under lithium therapy. The hypothalamic area contains GABAergic and glutamatergic neurons and their receptors, which regulate various hypothalamic functions such as the release of neurohormones, control circadian activities. At the neuronal level, several neurotransmitter systems are modulated by lithium exposure. However, the effect of Li⁺ on hypothalamic neuron excitability and the precise action mechanism involved in such an effect have not been fully understood yet. Therefore, Li⁺ action on hypothalamic neurons was investigated using a whole-cell patch-clamp technique. In hypothalamic neurons, Li⁺ increased the GABAergic synaptic activities via action potential independent presynaptic mechanisms. Next, concentration-dependent replacement of Na⁺ by Li⁺ in artificial cerebrospinal fluid increased frequencies of GABAergic miniature inhibitory postsynaptic currents without altering their amplitudes. Li⁺ perfusion induced inward currents in the majority of hypothalamic neurons independent of amino-acids receptor activation. These results suggests that Li⁺ treatment can directly affect the hypothalamic region of the brain and regulate the release of various neurohormones involved in synchronizing the neuroendocrine axis.     

DNA Targeting Sequence Improves Magnetic Nanoparticle-Based Plasmid DNA Transfection Efficiency in Model Neurons

Efficient non-viral plasmid DNA transfection of most stem cells, progenitor cells and primary cell lines currently presents an obstacle for many applications within gene therapy research. From a standpoint of efficiency and cell viability, magnetic nanoparticle-based DNA transfection is a promising gene vectoring technique because it has demonstrated rapid and improved transfection outcomes when compared to alternative non-viral methods. Recently, our research group introduced oscillating magnet arrays that resulted in further improvements to this novel plasmid DNA (pDNA) vectoring technology. Continued improvements to nanomagnetic transfection techniques have focused primarily on magnetic nanoparticle (MNP) functionalization and transfection parameter optimization: cell confluence, growth media, serum starvation, magnet oscillation parameters, etc. Noting that none of these parameters can assist in the nuclear translocation of delivered pDNA following MNP-pDNA complex dissociation in the cell’s cytoplasm, inclusion of a cassette feature for pDNA nuclear translocation is theoretically justified. In this study incorporation of a DNA targeting sequence (DTS) feature in the transfecting plasmid improved transfection efficiency in model neurons, presumably from increased nuclear translocation. This observation became most apparent when comparing the response of the dividing SH-SY5Y precursor cell to the non-dividing and differentiated SH-SY5Y neuroblastoma cells.     

PEI/EVAL blend membranes for granule neuronal cell culture

Recently we developed a novel type of membrane, based on polyethylene vinyl alcohol (EVAL), for biomedical applications. To improve the physical and biological performance of this membrane, polyethylenimine (PEI) that has been widely used as a gene transfer vector was chosen to blend with EVAL in this study. The properties and in vitro neuronal interaction of the blend membranes were investigated. Scanning electron microscopic observations show that the membranes exhibited increasingly smoother surface morphologies as the PEI content increased. Differential scanning calorimetric analysis demonstrated that EVAL was compatible with PEI at the microscopic level and the crystallinity of EVAL membrane was reduced by amorphous PEI. The surface nitrogen to carbon ratios, surface positive charges, surface hydrophilicity and surface protein adsorption were found to increase with increasing PEI content in the blend membranes as evidenced by the evidences from electron spectroscopy for chemical analysis as well as measurements of zeta potential, water contact angle, and serum protein adsorption respectively. From the morphology and viability of neurons cultured on the surfaces, it was observed that the neurons adhered, spread, grew and differentiated more onto the moderately hydrophilic PEI-containing membranes than onto the unmodified and hydrophobic EVAL. These PEI/EVAL blend membranes, which displayed high compatibility, thermal stability, moderate hydrophilicity, improved serum protein adsorption and enhanced neuronal interaction, may offer the potential to improve the healing and axonal regeneration of injured neuronal tissues.     

A Set of Neural Tools for Human-Computer Interactions: Application to the Handwritten Character Recognition, and Visual Speech Recognition Problems

This paper presents a new technique of data coding and an associated set of homogenous processing tools for the development of Human Computer Interactions (HCI). The proposed technique facilitates the fusion of different sensorial modalities and simplifies the implementations. The coding takes into account the spatio-temporal nature of the signals to be processed in the framework of a sparse representation of data. Neural networks adapted to such a representation of data are proposed to perform the recognition tasks. Their development is illustrated by two examples: one of on-line handwritten character recognition; and the other of visual speech recognition.     

Peptides Derived from Growth Factors to Treat Alzheimer’s Disease

Alzheimer’s disease (AD) is a devastating neurodegenerative disease characterized by progressive neuron losses in memory-related brain structures. The classical features of AD are a dysregulation of the cholinergic system, the accumulation of amyloid plaques, and neurofibrillary tangles. Unfortunately, current treatments are unable to cure or even delay the progression of the disease. Therefore, new therapeutic strategies have emerged, such as the exogenous administration of neurotrophic factors (e.g., NGF and BDNF) that are deficient or dysregulated in AD. However, their low capacity to cross the blood–brain barrier and their exorbitant cost currently limit their use. To overcome these limitations, short peptides mimicking the binding receptor sites of these growth factors have been developed. Such peptides can target selective signaling pathways involved in neuron survival, differentiation, and/or maintenance. This review focuses on growth factors and their derived peptides as potential treatment for AD. It describes (1) the physiological functions of growth factors in the brain, their neuronal signaling pathways, and alteration in AD; (2) the strategies to develop peptides derived from growth factor and their capacity to mimic the role of native proteins; and (3) new advancements and potential in using these molecules as therapeutic treatments for AD, as well as their limitations.