Isolation of mineralizing Nestin+ Nkx6.1+ vascular muscular cells from the adult human spinal cord

Background: The adult central nervous system (CNS) contains different populations of immature cells that could possibly be used to repair brain and spinal cord lesions. The diversity and the properties of these cells in the human adult CNS remain to be fully explored. We previously isolated Nestin(+) Sox2(+) neural multipotential cells from the adult human spinal cord using the neurosphere method (i.e. non adherent conditions and defined medium). -- Results: Here we report the isolation and long term propagation of another population of Nestin(+) cells from this tissue using adherent culture conditions and serum. QPCR and immunofluorescence indicated that these cells had mesenchymal features as evidenced by the expression of Snai2 and Twist1 and lack of expression of neural markers such as Sox2, Olig2 or GFAP. Indeed, these cells expressed markers typical of smooth muscle vascular cells such as Calponin, Caldesmone and Acta2 (Smooth muscle actin). These cells could not differentiate into chondrocytes, adipocytes, neuronal and glial cells, however they readily mineralized when placed in osteogenic conditions. Further characterization allowed us to identify the Nkx6.1 transcription factor as a marker for these cells. Nkx6.1 was expressed in vivo by CNS vascular muscular cells located in the parenchyma and the meninges. -- Conclusion: Smooth muscle cells expressing Nestin and Nkx6.1 is the main cell population derived from culturing human spinal cord cells in adherent conditions with serum. Mineralization of these cells in vitro could represent a valuable model for studying calcifications of CNS vessels which are observed in pathological situations or as part of the normal aging. In addition, long term propagation of these cells will allow the study of their interaction with other CNS cells and their implication in scar formation during spinal cord injury.

SEM and EDS Characterisation of Layering TiOx Growth onto the Cutting Tool Surface in Hard Drilling Processes of Ti-Al-V Alloys

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Comparison of laser performances of 5at.% Yb : Gd2xY2(1-x)SiO5 crystals between different cutting directions

We investigate the laser actions of 5at.% Yb:Gd2xY2(1-x)SiO5 (Yb:GYSO; x = 0.1) crystals with different cutting directions, parallel and vertical to the growth axis. Our results show that the cutting direction of the sample plays an astonished role in the laser operation. The sample cut vertically to the growth axis possesses the favourable lasing characteristics. Its output power reaches 3.13W at 1060nm with a slope efficiency of 44.68% when the absorbed pump power is 8.9 W. In contrast, the sample cut parallel reaches only 1.65 W at 1044 nm with a slope elLiciency of 33.76% with absorbed pump power of 7.99 W. The absorption and emission spectra of the two samples are examined and the merit factor M is calculated. Our analysis is in agreement well with the experimental results. The wavelength tuning range of the superior sample covers from 1013.68 nm to 1084.82 nm.

Spinal cord injury therapy through active learning

Therapy employing epidural electrostimulation holds great potential for improving therapy for patients with spinal cord injury (SCI) (Harkema et al., 2011). Further promising results from combined therapies using electrostimulation have also been recently obtained (e.g., van den Brand et al., 2012). The devices being developed to deliver the stimulation are highly flexible, capable of delivering any individual stimulus among a combinatorially large set of stimuli (Gad et al., 2013). While this extreme flexibility is very useful for ensuring that the device can deliver an appropriate stimulus, the challenge of choosing good stimuli is quite substantial, even for expert human experimenters. To develop a fully implantable, autonomous device which can provide useful therapy, it is necessary to design an algorithmic method for choosing the stimulus parameters. Such a method can be used in a clinical setting, by caregivers who are not experts in the neurostimulator's use, and to allow the system to adapt autonomously between visits to the clinic. To create such an algorithm, this dissertation pursues the general class of active learning algorithms that includes Gaussian Process Upper Confidence Bound (GP-UCB, Srinivas et al., 2010), developing the Gaussian Process Batch Upper Confidence Bound (GP-BUCB, Desautels et al., 2012) and Gaussian Process Adaptive Upper Confidence Bound (GP-AUCB) algorithms. This dissertation develops new theoretical bounds for the performance of these and similar algorithms, empirically assesses these algorithms against a number of competitors in simulation, and applies a variant of the GP-BUCB algorithm in closed-loop to control SCI therapy via epidural electrostimulation in four live rats. The algorithm was tasked with maximizing the amplitude of evoked potentials in the rats' left tibialis anterior muscle. These experiments show that the algorithm is capable of directing these experiments sensibly, finding effective stimuli in all four animals. Further, in direct competition with an expert human experimenter, the algorithm produced superior performance in terms of average reward and comparable or superior performance in terms of maximum reward. These results indicate that variants of GP-BUCB may be suitable for autonomously directing SCI therapy.

Microelectrode Implants for Spinal Cord Stimulation in Rats

Paralysis is a debilitating condition afflicting millions of people across the globe, and is particularly deleterious to quality of life when motor function of the legs is severely impaired or completely absent. Fortunately, spinal cord stimulation has shown great potential for improving motor function after spinal cord injury and other pathological conditions. Many animal studies have shown stimulation of the neural networks in the spinal cord can improve motor ability so dramatically that the animals can even stand and step after a complete spinal cord transaction.

This thesis presents work to successfully provide a chronically implantable device for rats that greatly enhances the ability to control the site of spinal cord stimulation. This is achieved through the use of a parylene-C based microelectrode array, which enables a density of stimulation sites unattainable with conventional wire electrodes. While many microelectrode devices have been proposed in the past, the spinal cord is a particularly challenging environment due to the bending and movement it undergoes in a live animal. The developed microelectrode array is the first to have been implanted in vivo while retaining functionality for over a month. In doing so, different neural pathways can be selectively activated to facilitate standing and stepping in spinalized rats using various electrode combinations, and important differences in responses are observed.

An engineering challenge for the usability of any high density electrode array is connecting the numerous electrodes to a stimulation source. This thesis develops several technologies to address this challenge, beginning with a fully passive implant that uses one wire per electrode to connect to an external stimulation source. The number of wires passing through the body and the skin proved to be a hazard for the health of the animal, so a multiplexed implant was devised in which active electronics reduce the number of wires. Finally, a fully wireless implant was developed. As these implants are tested in vivo, encapsulation is of critical importance to retain functionality in a chronic experiment, especially for the active implants, and it was achieved without the use of costly ceramic or metallic hermetic packaging. Active implants were built that retained functionality 8 weeks after implantation, and achieved stepping in spinalized rats after just 8-10 days, which is far sooner than wire-based electrical stimulation has achieved in prior work.