Spinal cord stimulation: fiber diameters in the dorsal columns modeled from clinical data

Computer simulations of clinical data were performed to estimate the diameter distribution of A¿ß nerve fibers in the human dorsal columns, activated by spinal cord stimulation. Qualitatively, the calculated distribution was in accordance with experimental data. Due to mismatches in impedance and limited resolution of the CT scans more patient data is needed to reliably predict the quantitative diameter distributio

Analysis of current density and related parameters in spinal cord stimulation

A volume conductor model of the spinal cord and surrounding anatomical structures is used to calculate current (and current density) charge per pulse, and maximum charge density per pulse at the contact surface of the electrode in the dorsal epidural space, in the dorsal columns of the spinal cord and in the dorsal roots. The effects of various contact configurations (mono-, bi-, and tripole), contact area and spacing, pulsewidth and distance between contacts and spinal cord on these electrical parameters were investigated under conditions similar to those in clinical spinal cord stimulation. At the threshold stimulus of a large dorsal column fiber, current density and charge density per pulse at the contact surface were found to be highest (1.9·105 ¿A/cm2 and 39.1 ¿C/cm2 ·p, respectively) when the contact surface was only 0.7 mm 2. When stimulating with a pulse of 500 ¿s, highest charge per pulse (0.92 ¿C/p), and the largest charge density per pulse in the dorsal columns (1.59 ¿C/cm2·p) occurred. It is concluded that of all stimulation parameters that can be selected freely, only pulsewidth affects the charge and charge density per pulse in the nervous tissue, whereas both pulsewidth and contact area strongly affect these parameters in the nonnervous tissue neighboring the electrode contact

Effects of electrode configuration and geometry on fiber preference in spinal cord stimulation

In contrast to the widespread assumption that dorsal column fibers are the primary targets of spinal cord stimulation by a dorsal epidural electrode, it appears that dorsal root fibers are recruited as well, and even preferentially under various conditions. This will, however, limit the coverage of the painful body areas with paresthesia, a prerequisite for the management of chronic pain. In order to favor the preferential stimulation of dorsal column fibers, advantage was taken of the different positions and orientations of fibers in the dorsal columns and dorsal roots. Using an SCS computer model, electrode configurations have been designed for the selective stimulation of the human dorsal column

Estimation of fiber diameters in the spinal dorsal columns from clinical data

Lack of human morphometric data regarding the largest nerve fibers in the dorsal columns (DCs) of the spinal cord has lead to the estimation of the diameters of these fibers from clinical data retrieved from patients with a new spinal cord stimulation (SCS) system. These patients indicated the perception threshold of stimulation induced paresthesia in various body segments, while the stimulation amplitude was increased. The fiber diameters were calculated with a computer model, developed to calculate the effects of SCS on spinal nerve fibers. This computer model consists of two parts: (1) a three-dimensional (3-D) volume conductor model of a spinal cord segment in which the potential distribution due to electrical stimulation is calculated and (2) an electrical equivalent cable model of myelinated nerve fiber, which uses the calculated potential field to determine the threshold stimulus needed for activation. It is shown that the largest fibers in the medial DCs are significantly smaller than the largest fibers in the lateral parts. This finding is in accordance with the fiber distribution in cat, derived from the corresponding propagation velocities. Moreover, it is shown that the mediolateral increase in fiber diameter is mainly confined to the lateral parts of the DCs. Implementation of this mediolateral fiber diameter distribution of the DCs in the computer model enables the prediction of the recruitment order of dermatomal paresthesias following increasing electrical stimulation amplitud

Technical phosphoproteomic and bioinformatic tools useful in cancer research

Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools

(Tissue) P Systems with Vesicles of Multisets

We consider tissue P systems working on vesicles of multisets with the very simple operations of insertion, deletion, and substitution of single objects. With the whole multiset being enclosed in a vesicle, sending it to a target cell can be indicated in those simple rules working on the multiset. As derivation modes we consider the sequential mode, where exactly one rule is applied in a derivation step, and the set maximal mode, where in each derivation step a non-extendable set of rules is applied. With the set maximal mode, computational completeness can already be obtained with tissue P systems having a tree structure, whereas tissue P systems even with an arbitrary communication structure are not computationally complete when working in the sequential mode. Adding polarizations (-1, 0, 1 are sufficient) allows for obtaining computational completeness even for tissue P systems working in the sequential mode.Comment: In Proceedings AFL 2017, arXiv:1708.0622

Implementation issues of a high-speed distributed multi-channel ADDA system

ABSTRACT A multi-channel ADDA controller is used in many active noise cancellation and active vibration control problems. Such a controller is able to yield good performance, however it also requires a lot of hardware on a centralized place and a lot of sensitive wiring. A practical work around for this problem would be to use a local single channel controller. However such a controller would reduce the overall system performance and may introduce instability. In this paper a system will be presented that acts as a hybrid form and combines the performance of a local feedback loop with a large multi-channel controller. To reduce the wiring and the influence of disturbances on this wiring a local analog to digital and digital to analog converter will be used. These systems will be interconnected using a high-speed serial communication system. To reduce the sample rate for the overall system, a local decimation and interpolation filter will be implemented. Further performance improvements will be realized by means of a simple local feedback system. The implementation issues concerning such a system are the subject of this paper

Standardized, Modular Parallelization Platform for Microfluidic Large-Scale Integration Cell Culturing Chips

Standardized high-throughput devices for microfluidic cell cultures are necessary to translate discoveries made in academia to applications in pharmaceutical industry. Here we present a platform with integrated pneumatic valves for standardized parallelization of multichamber chips (SPARC). In total, 192 chambers divided over three microfluidic building blocks (MFBBs) can be filled and purged with spatial and temporal independence. The dimensions of both the MFBB and the platform are standardized and thus compatible with common lab equipment. We characterize the valves at different pumping and gate pressures and show that the MFBBs are suitable for culturing human umbilical vein endothelial cells (HUVECs)

Enhanced Visualization of Optimal Cerebral Perfusion Pressure Over Time to Support Clinical Decision Making.

OBJECTIVE: Cerebrovascular reactivity can provide a continuously updated individualized target for management of cerebral perfusion pressure, termed optimal cerebral perfusion pressure. The objective of this project was to find a way of improving the optimal cerebral perfusion pressure methodology by introducing a new visualization method. DATA SOURCES: Four severe traumatic brain injury patients with intracranial pressure monitoring. DATA EXTRACTION: Data were collected and pre-processed using ICM+ software. DATA SYNTHESIS: Sequential optimal cerebral perfusion pressure curves were used to create a color-coded maps of autoregulation - cerebral perfusion pressure relationship evolution over time. CONCLUSIONS: The visualization method addresses some of the main drawbacks of the original methodology and might bring the potential for its clinical application closer.Marcel Aries received an unrestricted grant from the Dutch Society of Intensive Care. Joseph Donnelly is supported by a Woolf Fisher Trust Scholarship. The software for brain monitoring ICM+® (www.neurosurg.cam.ac.uk/imcplus) is licensed by the University of Cambridge (Cambridge Enterprise).This is the author accepted manuscript. It is currently embargoed pending publication by Wolters Kluwer

Architecture and dynamics of the jasmonic acid gene regulatory network

Jasmonic acid (JA) is a critical hormonal regulator of plant growth and defense. To advance our understanding of the architecture and dynamic regulation of the JA gene regulatory network, we performed a high-resolution RNA-seq time series of methyl JA-treated Arabidopsis thaliana at 15 time points over a 16-h period. Computational analysis showed that methyl JA (MeJA) induces a burst of transcriptional activity, generating diverse expression patterns over time that partition into distinct sectors of the JA response targeting specific biological processes. The presence of transcription factor (TF) DNA binding motifs correlated with specific TF activity during temporal MeJA-induced transcriptional reprogramming. Insight into the underlying dynamic transcriptional regulation mechanisms was captured in a chronological model of the JA gene regulatory network. Several TFs, including MYB59 and bHLH27, were uncovered as early network components with a role in pathogen and insect resistance. Analysis of subnetworks surrounding the TFs ORA47, RAP2.6L, MYB59, and ANAC055, using transcriptome profiling of overexpressors and mutants, provided insights into their regulatory role in defined modules of the JA network. Collectively, our work illuminates the complexity of the JA gene regulatory network, pinpoints and validates previously unknown regulators, and provides a valuable resource for functional studies on JA signaling components in plant defense and development