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The BNT162b2 mRNA vaccine is highly effective against SARS-CoV-2. However, apprehension exists that variants of concern (VOCs) may evade vaccine protection, due to evidence of reduced neutralization of the VOCs B.1.1.7 and B.1.351 by vaccine sera in laboratory assays. We performed a matched cohort study to examine the distribution of VOCs in infections of BNT162b2 mRNA vaccinees from Clalit Health Services (Israel) using viral genomic sequencing, and hypothesized that if vaccine effectiveness against a VOC is reduced, its proportion among breakthrough cases would be higher than in unvaccinated controls. Analyzing 813 viral genome sequences from nasopharyngeal swabs, we showed that vaccinees who tested positive at least 7 days after the second dose were disproportionally infected with B.1.351, compared with controls. Those who tested positive between 2 weeks after the first dose and 6 days after the second dose were disproportionally infected by B.1.1.7. These findings suggest reduced vaccine effectiveness against both VOCs within particular time windows. Our results emphasize the importance of rigorously tracking viral variants, and of increasing vaccination to prevent the spread of VOCs. At early time points after vaccination with a single dose or two doses of the BNT162b2 mRNA COVID-19 vaccine, breakthrough SARS-CoV-2 infections can be disproportionately caused by the B.1.1.7 or B.1.351 variants of concern, underlining the need to ensure rapid and complete vaccination.

The overall goal of this study was to develop a computational framework to quantify hip, knee, and ankle joint forces during exoskeletal-assisted walking (EAW) in the ReWalk P6.0, an FDA-approved lower-extremity exoskeleton. The first objective was to quantify hip, knee, and ankle joint forces during unassisted walking and compare the results to existing in vivo and simulation data. The second objective was to compute hip, knee, and ankle joint forces from four different approaches to simulate human-robot interactions during EAW. We recorded the three-dimensional motion of one able-bodied participant during unassisted walking and EAW, with simultaneous measurements of (i) marker trajectories, (ii) ground reaction forces, (iii) electromyography, and (iv) exoskeleton encoder data. We developed a subject-specific virtual simulator in OpenSim to reproduce unassisted walking and EAW. Next, we utilized OpenSim’s extension, OpenSim Moco, to determine the joint reaction forces at the hips, knees, and ankles during unassisted walking and EAW. The computed peak hip, knee, and ankle joint compressive forces during unassisted walking were 3.42–3.82 body weight (BW), 3.10–3.48 BW, and 4.97–5.83 BW, respectively; these joint forces were comparable to prior in vivo and simulation results. The four approaches to simulate human-robot interactions during EAW resulted in peak compressive forces ranging from 2.98–4.66 BW, 2.82–5.83 BW, and 3.39–3.79 BW at the hip, knee, and ankle joints, respectively. This computational framework provides a low-risk and cost-effective technique to quantify the loading of the long bones and assess fracture risk during EAW in patients with severe bone loss in the lower extremities.

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread. In this study, Adi Stern and colleagues use full genome sequences of SARS-CoV-2 to look at the rate of infections in Israel. They report that social distancing had a significant effect on minimising the rate of transmission, and find evidence for transmission heterogeneity (superspreading events).

•IF optimization for DBS MRI with a two-channel transmit system.•Induced current on the DBS electrode was minimized while overall B1+ was preserved.•Streamlined IF workflow applied in three DBS patients (1 bilateral, 2 unilateral).•Reduction of RF artifact and heating using IF mode compared to standard CP mode. MRI of patients with deep brain stimulation (DBS) implants presents a significant safety risk due to RF heating. A current measurement that utilizes an inherent imaging artifact was previously used to mitigate induced current along a single electrode using a two transmit-channel system. This study extends it to bilateral DBS configurations and demonstrates a streamlined implant-friendly (IF) optimization in both unilateral and bilateral patients. The bilateral IF mode was optimized to reduce RF-induced currents on both electrodes while maximizing the overall B1 and was validated in an anthropomorphic head phantom. An imaging workflow to determine electrode-specific and bilateral IF modes were demonstrated in three DBS patients (one bilateral, two unilateral). Image quality and artifact reduction of the circularly-polarized (CP) and IF modes were compared using 2D-TSE. Phantom study confirmed the heating reduction capabilities of the IF optimization. In both phantom and patient studies, RF artifact reduction was observed. In the unilateral DBS case, IF optimization completely mitigated the induced current, while in the bilateral case, current was reduced up to 74 % compared to CP excitation. The total active scan time for the pre-scan imaging was <6 min. All measurements in the pre-scan protocol were performed directly on the MRI console, with minimal external hardware. This study demonstrates a practical workflow for real-time current analysis and IF mode optimization in patients with DBS implants, effectively reducing RF-induced heating and artifacts while maintaining imaging performance.

Physical therapy is crucial for rehabilitating hand function after spinal cord injury (SCI), but it is time- and effort-intensive. New approaches that foster engagement and accelerate motor learning are needed. This study examined whether augmented sensory feedback (ASF) delivered through virtual reality (VR) can improve motor performance and neural activation in persons with SCI. Experimental study. VR compatibility was integrated with a custom-developed smart glove system that informs users when secure object grasp was achieved during training of functional grasp tasks. Six participants with incomplete cervical-level SCI performed a grasp-and-place task under three training conditions: no ASF, glove-based ASF, and VR-based ASF. Training trial-blocks provided multimodal (visual and audio) ASF cues about secure grasp at progressively reduced delays to induce a sense of agency through conditioned perceptions of intentional binding. Compared with no ASF, VR-based ASF significantly improved performance (p < 0.05) for metrics of reduced motion path length (51.5%) and shorter trial completion times (−44.6%). VR training also correspondingly produced the greatest increases in electroencephalography activity. Findings should be interpreted cautiously, given the small sample size and single-session design. Still, results from this study suggest VR-enhanced ASF can positively support motor learning and neuroplasticity after SCI through greater cognitive-level engagement. NCT04577573. •Physical therapy for hand function after neurotraumas is time- and effort-intensive.•Sensory-driven cues about performance can accelerate gains in motor learning.•Persons with spinal cord injury benefit from receiving training cues in virtual reality.•Virtual reality enhances neuromotor training to improve hand function performance.

Key Points Adult mammalian CNS regeneration is limited by a combination of intrinsic and extrinsic inhibitory barriers. This differs from the extraordinary ability to form short- and long-distance connections and complex circuits during nervous system development. Various signalling molecules guide developing neuronal branches. Many of these molecules persist in adults, but in different quantitative and qualitative distributions. The immature nervous system is refined by experience-dependent plasticity, resulting in the pruning of unnecessary connections and strengthening of useful ones. Mechanisms responsible for consolidating these refinements largely prevent further plastic changes, and secondarily inhibit regenerative responses in the context of injury. Local network circuits termed central pattern generators (CPGs) regulate semi-automatic behaviours such as ambulation. CPG plasticity and adaptation depend on sensory feedback and voluntary input. Intrinsic barriers to CNS regeneration include an unfavourable intracellular second messenger milieu as well as the inability to use regeneration-associated genes. Extrinsic barriers to CNS regeneration include inhibitory molecules produced by oligodendrocytes, astrocytes and inflammatory cells. The altered distribution of growth and guidance factors in the adult relative to the developing nervous systems represents another extrinsic barrier to effective regeneration. Advances using stem cells, neurotrophins and antagonists of extracellular inhibitors have resulted in a limited degree of CNS regeneration so far. Better approaches are required to recapitulate the precision of developmental growth, guidance and plasticity mechanisms. One strategy to mimic the developmental milieu requires better understanding of the changes in distribution of key guidance molecules during and after development. Rehabilitation approaches that maximize sensory feedback to CPGs will optimize the adaptation to loss of descending voluntary input. During development, precisely coordinated processes allow the formation of complex neural circuitry, but after CNS injury in adult mammals, functional circuits fail to reform. Recent work indicates that the recapitulation of developmental processes will be advantageous for successful functional recovery. The precise wiring of the adult mammalian CNS originates during a period of stunning growth, guidance and plasticity that occurs during and shortly after development. When injured in adults, this intricate system fails to regenerate. Even when the obstacles to regeneration are cleared, growing adult CNS fibres usually remain misdirected and fail to reform functional connections. Here, we attempt to fill an important niche related to the topics of nervous system development and regeneration. We specifically contrast the difficulties faced by growing fibres within the adult context to the precise circuit-forming capabilities of developing fibres. In addition to focusing on methods to stimulate growth in the adult, we also expand on approaches to recapitulate development itself.

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90° (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

•Connectomics can help treatment planning in epilepsy and neuro-oncology.•Tractography can help motor thalamus targeting and has potential with other targets.•Combined with other modalities, connectomics can help elucidate pathophysiology.•Lack of standards in image acquisition and processing limit widespread utilization.•Improved acquisition and process automation can increase reliability of these tools. Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.

Deep brain stimulation (DBS) requires accurate localization of the anatomical target structure, and the precise placement of the DBS electrode within it. Ultra-high field 7 Tesla (T) MR images can be utilized to create patient-specific anatomical 3D models of the subthalamic nuclei (STN) to enhance pre-surgical DBS targeting as well as post-surgical visualization of the DBS lead position and orientation. We validated the accuracy of the 7T imaging-based patient-specific model of the STN and measured the variability of the location and dimensions across movement disorder patients. 72 patients who underwent DBS surgery were scanned preoperatively on 7T MRI. Segmentations and 3D volume rendering of the STN were generated for all patients. For 21 STN-DBS cases, microelectrode recording (MER) was used to validate the segmentation. For 12 cases, we computed the correlation between the overlap of the STN and volume of tissue activated (VTA) and the monopolar review for a further validation of the model's accuracy and its clinical relevancy. We successfully reconstructed and visualized the STN in all patients. Significant variability was found across individuals regarding the location of the STN center of mass as well as its volume, length, depth and width. Significant correlations were found between MER and the 7T imaging-based model of the STN (r = 0.86) and VTA-STN overlap and the monopolar review outcome (r = 0.61). The results suggest that an accurate visualization and localization of a patient-specific 3D model of the STN can be generated based on 7T MRI. The imaging-based 7T MRI STN model was validated using MER and patient's clinical outcomes. The significant variability observed in the STN location and shape based on a large number of patients emphasizes the importance of an accurate direct visualization of the STN for DBS targeting. An accurate STN localization can facilitate postoperative stimulation parameters for optimized patient outcome.

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports. Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation. Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution. Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings. Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.