Characterization of Spinal Sensorimotor Network Using Transcutaneous Spinal Stimulation during Voluntary Movement Preparation and Performance

Transcutaneous electrical spinal stimulation (TSS) can be used to selectively activate motor pools based on their anatomical arrangements in the lumbosacral enlargement. These spatial patterns of spinal motor activation may have important clinical implications, especially when there is a need to target specific muscle groups. However, our understanding of the net effects and interplay between the motor pools projecting to agonist and antagonist muscles during the preparation and performance of voluntary movements is still limited. The present study was designed to systematically investigate and differentiate the multi-segmental convergence of supraspinal inputs on the lumbosacral neural network before and during the execution of voluntary leg movements in neurologically intact participants. During the experiments, participants (N = 13) performed isometric (1) knee flexion and (2) extension, as well as (3) plantarflexion and (4) dorsiflexion. TSS consisting of a pair pulse with 50 ms interstimulus interval was delivered over the T12-L1 vertebrae during the muscle contractions, as well as within 50 to 250 ms following the auditory or tactile stimuli, to characterize the temporal profiles of net spinal motor output during movement preparation. Facilitation of evoked motor potentials in the ipsilateral agonists and contralateral antagonists emerged as early as 50 ms following the cue and increased prior to movement onset. These results suggest that the descending drive modulates the activity of the inter-neuronal circuitry within spinal sensorimotor networks in specific, functionally relevant spatiotemporal patterns, which has a direct implication for the characterization of the state of those networks in individuals with neurological conditions.

Using Sensorized Gloves and Dimensional Reduction for Hand Function Assessment of Patients with Osteoarthritis

Sensorized gloves allow the measurement of all hand kinematics that are essential for daily functionality. However, they are scarcely used by clinicians, mainly because of the difficulty of analyzing all joint angles simultaneously. This study aims to render this analysis easier in order to enable the applicability of the early detection of hand osteoarthritis (HOA) and the identification of indicators of dysfunction. Dimensional reduction was used to compare kinematics (16 angles) of HOA patients and healthy subjects while performing the tasks of the Sollerman hand function test (SHFT). Five synergies were identified by using principal component (PC) analyses, patients using less fingers arch, higher palm arching, and a more independent thumb abduction. The healthy PCs, explaining 70% of patients’ data variance, were used to transform the set of angles of both samples into five reduced variables (RVs): fingers arch, hand closure, thumb-index pinch, forced thumb opposition, and palmar arching. Significant differences between samples were identified in the ranges of movement of most of the RVs and in the median values of hand closure and thumb opposition. A discriminant function for the detection of HOA, based in RVs, is provided, with a success rate of detection higher than that of the SHFT. The temporal profiles of the RVs in two tasks were also compared, showing their potentiality as dysfunction indicators. Finally, reducing the number of sensors to only one sensor per synergy was explored through a linear regression, resulting in a mean error of 7.0°.

Convolution model for COVID-19 rate predictions and health effort levels computation for Saudi Arabia, France, and Canada

Many published infection prediction models, such as the extended SEIR (E-SEIR) model, are used as a study and report tool to aid health authorities to manage the epidemic plans successfully. These models face many challenges, mainly the reliability of the infection rate predictions related to the initial boundary conditions, formulation complexity, lengthy computations, and the limited result scope. We attribute these challenges to the absence of a solution framework that encapsulates the interacted activities that manage: the infection growth process, the infection spread process and the health effort process. In response to these challenges, we formulated such a framework first as the basis of our new convolution prediction model (CPM). CPM links through convolution integration, three temporal profile levels: input (infected and active cases), transformational (health efforts), and output functions (recovered, quarantine, and death cases). COVID-19 data defines the input and output temporal profiles; hence it is possible to deduce the cumulative efforts temporal response (CETR) function for the health effort level. The new CETR function determines the health effort level over a period. Also, CETR plays a role in predicting the evolution of the underlying infection and active cases profiles without a system of differential equations. This work covers three countries: Saudi Arabia, France, and Canada.

Stimulus-induced narrow-band gamma oscillations in humans can be recorded using open-hardware low-cost EEG amplifier

Stimulus-induced narrow-band gamma oscillations (30-70 Hz) in human electro - encephalograph (EEG) have been linked to attentional and memory mechanisms and are abnormal in mental health conditions such as autism, schizophrenia and Alzheimer's Disease. This suggests that gamma oscillations could be valuable both as a research tool and an inexpensive, non-invasive biomarker for disease evaluation. However, since the absolute power in EEG decreases rapidly with increasing frequency following a "1/f" power law, and the gamma band includes line noise frequency, these oscillations are highly susceptible to instrument noise. Previous studies that recorded stimulus-induced gamma oscillations used expensive research-grade EEG amplifiers to address this issue. While low-cost EEG amplifiers have become popular in Brain Computer Interface applications that mainly rely on low-frequency oscillations (<30 Hz) or steady-state-visually-evoked-potentials, whether they can also be used to measure stimulus-induced gamma oscillations is unknown. We recorded EEG signals using a low-cost, open-source amplifier (OpenBCI) and a traditional, research-grade amplifier (Brain Products GmbH) in male (N = 6) and female (N = 5) subjects (22-29 years) while they viewed full-screen static gratings that are known to induce gamma oscillations. OpenBCI recordings showed gamma response in almost all the subjects who showed a gamma response in Brain Products recordings, and the spectral and temporal profiles of these responses in alpha (8-13 Hz) and gamma bands were highly correlated between OpenBCI and Brain Products recordings. These results suggest that low-cost amplifiers can potentially be used in stimulus induced gamma response detection, making its research, and application in medicine more accessible.

Temporal Associations of the SARS-CoV-2 NP Antigen and Anti-Spike Total Ig Levels with Laboratory Parameters in a Greek Cohort of Hospitalized COVID-19 Patients

Background. The direct effect of SARS-CoV-2 on the lungs results in increased hospitalization rates of patients with pneumonia. Severe COVID-19 patients often develop ARDS which is associated with poor prognosis. Assessing risk factors for COVID-19 severity is indispensable for implementing and evaluating therapeutic interventions. We investigated the temporal associations between the SARS-CoV-2 antigen (Ag), total Immunoglobulin (Ig) levels, and several laboratory parameters in hospitalized patients with varying degrees of COVID-19 severity. Methods. The SARS-CoV-2 nucleocapsid protein (NP) and total Ig Spike (S) protein-specific antibodies were determined for each patient with lateral flow assays through repeated sampling every two days. Hematological and biochemical parameters were evaluated at the same time points. Results. 40 Greek COVID-19 patients (31 males, 9 females) with a median age of 59.50 ± 16.21 years were enrolled in the study. The median time from symptom onset to hospitalization was 8.0 ± 4.19 days. A significant negative correlation was observed between the SARS-CoV-2 Ag and total Ig levels. The temporal correlation patterns of the SARS-CoV-2 NP Ag and anti-S total Ig levels with laboratory markers varied among patients with differing degrees of COVID-19 severity. Severe-critical cases had lower SARS-CoV-2 Ag and increased total Ig levels as compared to mild-moderate cases. Conclusions. Distinct temporal profiles of the SARS-CoV-2 NP Ag and anti-S total Ig levels may distinguish different groups of COVID-19 severity.

The Role of Microglia in Modulating Neuroinflammation after Spinal Cord Injury

The pathobiology of traumatic and nontraumatic spinal cord injury (SCI), including degenerative myelopathy, is influenced by neuroinflammation. The neuroinflammatory response is initiated by a multitude of injury signals emanating from necrotic and apoptotic cells at the lesion site, recruiting local and infiltrating immune cells that modulate inflammatory cascades to aid in the protection of the lesion site and encourage regenerative processes. While peripheral immune cells are involved, microglia, the resident immune cells of the central nervous system (CNS), are known to play a central role in modulating this response. Microglia are armed with numerous cell surface receptors that interact with neurons, astrocytes, infiltrating monocytes, and endothelial cells to facilitate a dynamic, multi-faceted injury response. While their origin and essential nature are understood, their mechanisms of action and spatial and temporal profiles warrant extensive additional research. In this review, we describe the role of microglia and the cellular network in SCI, discuss tools for their investigation, outline their spatiotemporal profile, and propose translationally-relevant therapeutic targets to modulate neuroinflammation in the setting of SCI.

Viscoelastic Thermovibrational Flow Driven by Sinusoidal and Pulse (Square) Waves

The present study aims to probe the role of an influential factor heretofore scarcely considered in earlier studies in the field of thermovibrational convection, that is, the specific time-varying shape of the forcing used to produce fluid motion under the effect of an imposed temperature gradient. Towards this end, two different temporal profiles of acceleration are considered: a classical (sinusoidal) and a pulse (square) wave. Their effects are analyzed in conjunction with the ability of a specific category of fluids to accumulate and release elastic energy, i.e., that of Chilcott–Rallison finitely extensible nonlinear elastic (FENE-CR) liquids. Through solution of the related governing equations in time-dependent, three-dimensional, and nonlinear form for a representative set of parameters (generalized Prandtl number Prg=8, normalized frequency Ω=25, solvent-to-total viscosity ratio ξ=0.5, elasticity number ϑ=0.1, and vibrational Rayleigh number Raω=4000), it is shown that while the system responds to a sinusoidal acceleration in a way that is reminiscent of modulated Rayleigh–Bénard (RB) convection in a Newtonian fluid (i.e., producing a superlattice), with a pulse wave acceleration, the flow displays a peculiar breaking-roll mode of convection that is in between classical (un-modulated) RB in viscoelastic fluids and purely thermovibrational flows. Besides these differences, these cases share important properties, namely, a temporal subharmonic response and the tendency to produce spatially standing waves.