A new methodological approach to characterize selective motor control in children with cerebral palsy.

Introduction: Despite being a primary impairment in individuals with cerebral palsy (CP), selective motor control (SMC) is not routinely measured. Personalized treatment approaches in CP will be unattainable without the ability to precisely characterize the types and degrees of impairments in motor control. The objective of this study is to report the development and feasibility of a new methodological approach measuring muscle activation patterns during single-joint tasks to characterize obligatory muscle co-activation patterns that may underly impaired SMC. Methods: Muscle activation patterns were recorded during sub-maximal voluntary isometric contraction (sub-MVIC) tasks at the hip, knee, and ankle with an interactive feedback game to standardize effort across participants. We calculated indices of co-activation, synergistic movement, mirror movement, and overflow (indices range 0-2, greater scores equal to greater impairment in SMC) for each isolated joint task in 15 children - 8 with typical development (TD) (mean age 4.7 ± 1.0 SD years) and 7 with CP (mean age 5.8 ± 0.7 SD years). Indices were compared with Mann-Whitney tests. The relationships between the indices and gross motor function (GMFM-66) were examined with Pearson's r. Results: Mean indices were higher in the CP vs. the TD group for each of the six tasks, with mean differences ranging from 0.05 (abduction and plantarflexion) to 0.44 (dorsiflexion). There was great inter-subject variability in the CP group such that significant group differences were detected for knee flexion mirroring (p = 0.029), dorsiflexion coactivation (p = 0.021), and dorsiflexion overflow (p = 0.014). Significant negative linear relations to gross motor function were found in all four indices for knee extension (r = -0.56 to -0.75), three of the indices for ankle dorsiflexion (r = -0.68 to -0.78) and in two of the indices for knee flexion (r = -0.66 to -0.67), and ankle plantarflexion (r = -0.53 to -0.60). Discussion: Indices of coactivation, mirror movement, synergy, and overflow during single-joint lower limb tasks may quantify the type and degree of impairment in SMC. Preliminary concurrent validity between several of the indices of SMC and gross motor function was observed. Our findings established the feasibility of a new methodological approach that quantifies muscle activation patterns using electromyography paired with biofeedback during single-joint movement.

Deep learning, 3D ultrastructural analysis reveals quantitative differences in platelet and organelle packing in COVID-19/SARSCoV2 patient-derived platelets.

Platelets contribute to COVID-19 clinical manifestations, of which microclotting in the pulmonary vasculature has been a prominent symptom. To investigate the potential diagnostic contributions of overall platelet morphology and their α-granules and mitochondria to the understanding of platelet hyperactivation and micro-clotting, we undertook a 3D ultrastructural approach. Because differences might be small, we used the high-contrast, high-resolution technique of focused ion beam scanning EM (FIB-SEM) and employed deep learning computational methods to evaluate nearly 600 individual platelets and 30 000 included organelles within three healthy controls and three severely ill COVID-19 patients. Statistical analysis reveals that the α-granule/mitochondrion-to-plateletvolume ratio is significantly greater in COVID-19 patient platelets indicating a denser packing of organelles, and a more compact platelet. The COVID-19 patient platelets were significantly smaller -by 35% in volume - with most of the difference in organelle packing density being due to decreased platelet size. There was little to no 3D ultrastructural evidence for differential activation of the platelets from COVID-19 patients. Though limited by sample size, our studies suggest that factors outside of the platelets themselves are likely responsible for COVID-19 complications. Our studies show how deep learning 3D methodology can become the gold standard for 3D ultrastructural studies of platelets.

COVID-19 patients exhibit a range of symptoms including microclotting. Clotting is a complex process involving both circulating proteins and platelets, a cell within the blood. Increased clotting is suggestive of an increased level of platelet activation. If this were true, we reasoned that parts of the platelet involved in the release of platelet contents during clotting would have lost their content and appear as expanded, empty "ghosts." To test this, we drew blood from severely ill COVID-19 patients and compared the platelets within the blood draws to those from healthy volunteers. All procedures were done under careful attention to biosafety and approved by health authorities. We looked within the platelets for empty ghosts by the high magnification technique of electron microscopy. To count the ghosts, we developed new computer software. In the end, we found little difference between the COVID patient platelets and the healthy donor platelets. The results suggest that circulating proteins outside of the platelet are more important to the strong clotting response. The software developed will be used to analyze other disease states.