Perspectives for computational modeling of cell replacement for neurological disorders

Cell Therapy and Functional Recovery of Stroke

Stroke is the most common cause of disability. Brain repair mechanisms are often insufficient to allow a full recovery. Stroke damage involve all brain cell type and extracellular matrix which represent the crucial "glio-neurovascular niche" useful for brain plasticity. Regenerative medicine including cell therapies hold great promise to decrease post-stroke disability of many patients, by promoting both neuroprotection and neural repair through direct effects on brain lesion and/or systemic effects such as immunomodulation. Mechanisms of action vary according to each grafted cell type: "peripheral" stem cells, such as mesenchymal stem cells (MSC), can provide paracrine trophic support, and neural stem/progenitor cells (NSC) or neurons can act as direct cells' replacements. Optimal time window, route, and doses are still debated, and may depend on the chosen medicinal product and its expected mechanism such as neuroprotection, delayed brain repair, systemic effects, or graft survival and integration in host network. MSC, mononuclear cells (MNC), umbilical cord stem cells and NSC are the most investigated. Innovative approaches are implemented concerning combinatorial approaches with growth factors and biomaterials such as injectable hydrogels which could protect a cell graft and/or deliver drugs into the post-stroke cavity at chronic stages. Through main publications of the last two decades, we provide in this review concepts and suggestions to improve future translational researches and larger clinical trials of cell therapy in stroke.

The brain's unique take on algorithms

The current gap between computing algorithms and neuromorphic hardware to emulate brains is an outstanding bottleneck in developing neural computing technologies. Aimone and Parekh discuss the possibility of bridging this gap using theoretical computing frameworks from a neuroscience perspective.

Mechanisms of Hierarchical Cortical Maturation

Cortical information processing is structurally and functionally organized into hierarchical pathways, with primary sensory cortical regions providing modality specific information and associative cortical regions playing a more integrative role. Historically, there has been debate as to whether primary cortical regions mature earlier than associative cortical regions, or whether both primary and associative cortical regions mature simultaneously. Identifying whether primary and associative cortical regions mature hierarchically or simultaneously will not only deepen our understanding of the mechanisms that regulate brain maturation, but it will also provide fundamental insight into aspects of adolescent behavior, learning, neurodevelopmental disorders and computational models of neural processing. This mini-review article summarizes the current evidence supporting the sequential and hierarchical nature of cortical maturation, and then proposes a new cellular model underlying this process. Finally, unresolved issues associated with hierarchical cortical maturation are also addressed.

Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling - regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity.

Functional Properties of Human Stem Cell-Derived Neurons in Health and Disease

Stem cell-derived neurons from various source materials present unique model systems to examine the fundamental properties of central nervous system (CNS) development as well as the molecular underpinnings of disease phenotypes. In order to more accurately assess potential therapies for neurological disorders, multiple strategies have been employed in recent years to produce neuronal populations that accurately represent in vivo regional and transmitter phenotypes. These include new technologies such as direct conversion of somatic cell types into neurons and glia which may accelerate maturation and retain genetic hallmarks of aging. In addition, novel forms of genetic manipulations have brought human stem cells nearly on par with those of rodent with respect to gene targeting. For neurons of the CNS, the ultimate phenotypic characterization lies with their ability to recapitulate functional properties such as passive and active membrane characteristics, synaptic activity, and plasticity. These features critically depend on the coordinated expression and localization of hundreds of ion channels and receptors, as well as scaffolding and signaling molecules. In this review I will highlight the current state of knowledge regarding functional properties of human stem cell-derived neurons, with a primary focus on pluripotent stem cells. While significant advances have been made, critical hurdles must be overcome in order for this technology to support progression toward clinical applications.

The synergistic effects of heat shock protein 70 and ginsenoside Rg1 against tert-butyl hydroperoxide damage model in vitro

Neural stem cells (NSCs) transplanted is one of the hottest research to treat Alzheimer's disease (AD), but cholinergic neurons from stem cells were also susceptible to cell death which Heat shock protein 70 (HSP70) was affirmed to reverse. Related to cognitive impairment, cholinergic nervous cells should be investigated and ginsenoside Rg1 (G-Rg1) was considered to increase them. We chose tert-butyl hydroperoxide (t-BHP) damage model to study in vitro. Functional properties of our recombination plasmid pEGFP-C2-HSP70 were affirmed by SH-SY5Y cells. To opposite the transitory appearance of HSP70, NSCs used as the vectors of HSP70 gene overexpressed HSP70 for at least 7 days in vitro. After transfection for 3 days, G-Rg1 pretreatment for 4 hours, and coculture for 3 days, the expression of acetylcholinesterase (ChAT), synaptophysin, and the ratio of NeuN and GFAP were assessed by western blot; Morphological properties were detected by 3D reconstruction and immunofluorescence. ChAT was markedly improved in the groups contained G-Rg1. In coculture system, the ratio of neurons/astrocytes and the filaments of neurons were increased; apoptosis cells were decreased, compared to monotherapy (P < 0.05). In conclusion, we demonstrated that, as a safe cotreatment affirmed in vitro, overexpression of HSP70 in NSCs plus G-Rg1 promoted nervous cells regeneration from chronic oxidative damage.