Roadmap on semiconductor-cell biointerfaces.

This roadmap outlines the role semiconductor-based materials play in understanding the complex biophysical dynamics at multiple length scales, as well as the design and implementation of next-generation electronic, optoelectronic, and mechanical devices for biointerfaces. The roadmap emphasizes the advantages of semiconductor building blocks in interfacing, monitoring, and manipulating the activity of biological components, and discusses the possibility of using active semiconductor-cell interfaces for discovering new signaling processes in the biological world

A hybrid piezoelectric and electrostatic energy harvester for scavenging arterial pulsations

Implantable and wearable biomedical devices suffer from a limited lifespan of on-board batteries which results in a requirement to change the battery or the device itself causing additional physical discomfort. In order to overcome this, various energy harvesters have been developed. The human body possesses several types of energy available for scavenging through appropriately designed energy harvesting devices, while cardiovascular system in particular represents a constant reliable source of mechanical energy from vibration. Most conventional energy harvesters exploit only a single phenomenon, such piezo- or triboelectricity, thus producing reduced power density. As an improvement, hybridisation of energy harvesters intends to negate this drawback by simultaneously scavenging energy by multiple harvesters. In the present work, the reverse electrowetting on dielectric (REWOD) phenomenon is combined with the piezoelectric effect in a proof-of-concept hybrid harvester for scavenging biomechanical energy from arterial or other type pulsations. A mathematical model of the harvester was developed, and a computational investigation using CFD, and fluid-structure interaction simulations were carried out using the COMSOL Multiphysics software. The effect of the materials of piezoelectric film and geometrical features of the harvester on parameters such as the displacement, the frequency of pulsations and the energy produced were studied. An experimental setup that could imitate the displacements caused from arterial pulsations was designed and the produced electrical energy characteristics were analysed. A comparison between experimental and computational data was carried out and demonstrated a good agreement. Dependencies between geometrical parameters and electrical output were obtained, recommendation on piezoelectric materials and design solutions were provided

Risk prediction and an injectable collagen material for intervertebral disc degeneration

This research primarily focuses on early prediction and treatment for intervertebral disc degeneration (IVDD). In Phase 1, machine learning algorithms were evaluated to predict the risk of intervertebral disc degeneration in patients. This was done by using factors associated with IVDD and taken from patient medical history. Several classification algorithms were utilized to develop predictive models. Results demonstrated that machine learning algorithms could be used to predict IVDD risk and also the potential for developing an app from these predictive models. Phase 2 focused on the development of a collagen-based, gold nanoparticle material for intervertebral disc regeneration. Gold nanoparticles were conjugated to viscoelastic collagen using a natural crosslinker, genipin. This material was then characterized to evaluate its ability to serve as a treatment for chronic back pain caused by IVDD. Results demonstrated successful attachment of the gold nanoparticles to the collagen using the genipin crosslinker. Overall, the characterization studies of the collagen composite were successful and demonstrated potential for further application in IVDD treatment.Includes bibliographical reference

Interfacing graphene with peripheral neurons: influence of neurite outgrowth and NGF axonal transport

Graphene displays properties that make it appealing for neuroregenerative medicine, yet the potential of large-scale highly-crystalline graphene as a conductive peripheral neural interface has been scarcely investigated. In particular, pristine graphene offers enhanced electrical properties that can be advantageous for nervous system regeneration applications. In this work, we investigate graphene potential as peripheral nerve interface. First, we perform an unprecedented analysis aimed at revealing how the typical polymeric coatings for neural cultures distribute on graphene at the nanometric scale. Second, we examine the impact of graphene on the culture of two established cellular models for peripheral nervous system: PC12 cell line and primary embryonic rat dorsal root ganglion (DRG) neurons, showing a better and faster axonal elongation using graphene. We then observe that the axon elongation in the first days of culture correlates to an altered nerve growth factor (NGF) axonal transport, with a reduced number of retrogradely moving NGF vesicles in favor of stalled vesicles. We thus hypothesize that the axon elongation observed in the first days of culture could be mediated by this pool of NGF vesicles locally retained in the medial/distal parts of axons. Furthermore, we investigate electrophysiological properties and cytoskeletal structure of peripheral neurons. We observe a reduced neural excitability and altered membrane potential together with a reduced inter-microtubular distance on graphene and correlate these electrophysiological and structural reorganizations of axon physiology to the observed vesicle stalling. Finally, the potential of another 2D material as neural interface, tungsten disulfide, is explored