Analytical CPG model driven by limb velocity input generates accurate temporal locomotor dynamics

The ability of vertebrates to generate rhythm within their spinal neural networks is essential for walking, running, and other rhythmic behaviors. The central pattern generator (CPG) network responsible for these behaviors is well-characterized with experimental and theoretical studies, and it can be formulated as a nonlinear dynam- ical system. The underlying mechanism responsible for locomotor behavior can be expressed as the process of leaky integration with resetting states generating appropriate phases for changing body velocity. The low-dimensional input to the CPG model generates the bilateral pattern of swing and stance modulation for each limb and is consistent with the desired limb speed as the input command. To test the minimal configuration of required parameters for this model, we reduced the system of equations representing CPG for a single limb and provided the analytical solution with two complementary methods. The analytical and empirical cycle durations were similar (R2 = 0.99) for the full range of walking speeds. The structure of solution is consistent with the use of limb speed as the input domain for the CPG network. Moreover, the reciprocal interaction between two leaky integration processes representing a CPG for two limbs was sufficient to capture fundamental experimental dynamics associated with the control of heading direction. This analysis provides further support for the embedded velocity or limb speed representation within spinal neural pathways involved in rhythm generation

Automated Assessment of Upper Extremity Movement Impairment due to Stroke

Current diagnosis and treatment of movement impairment post-stroke is based on the subjective assessment of select movements by a trained clinical specialist. However, modern low-cost motion capture technology allows for the development of automated quantitative assessment of motor impairment. Such outcome measures are crucial for advancing post-stroke treatment methods. We sought to develop an automated method of measuring the quality of movement in clinically-relevant terms from low-cost motion capture. Unconstrained movements of upper extremity were performed by people with chronic hemiparesis and recorded by standard and low-cost motion capture systems. Quantitative scores derived from motion capture were compared to qualitative clinical scores produced by trained human raters. A strong linear relationship was found between qualitative scores and quantitative scores derived from both standard and low-cost motion capture. Performance of the automated scoring algorithm was matched by averaged qualitative scores of three human raters. We conclude that low-cost motion capture combined with an automated scoring algorithm is a feasible method to assess objectively upper-arm impairment post stroke. The application of this technology may not only reduce the cost of assessment of post-stroke movement impairment, but also promote the acceptance of objective impairment measures into routine medical practice

Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching

Human reaching movements require complex muscle activations to produce the forces necessary to move the limb in a controlled manner. How gravity and the complex kinetic properties of the limb contribute to the generation of the muscle activation pattern by the central nervous system (CNS) is a long-standing and controversial question in neuroscience. To tackle this issue, muscle activity is often subdivided into static and phasic components. The former corresponds to posture maintenance and transitions between postures. The latter corresponds to active movement production and the compensation for the kinetic properties of the limb. In the present study, we improved the methodology for this subdivision of muscle activity into static and phasic components by relating them to joint torques. Ten healthy subjects pointed in virtual reality to visual targets arranged to create a standard center-out reaching task in three dimensions. Muscle activity and motion capture data were synchronously collected during the movements. The motion capture data were used to calculate postural and dynamic components of active muscle torques using a dynamic model of the arm with 5 degrees of freedom. Principal Component Analysis (PCA) was then applied to muscle activity and the torque components, separately, to reduce the dimensionality of the data. Muscle activity was also reconstructed from gravitational and dynamic torque components. Results show that the postural and dynamic components of muscle torque represent a significant amount of variance in muscle activity. This method could be used to define static and phasic components of muscle activity using muscle torques

Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching

Human reaching movements require complex muscle activations to produce the forces necessary to move the limb in a controlled manner. How gravity and the complex kinetic properties of the limb contribute to the generation of the muscle activation pattern by the central nervous system (CNS) is a long-standing and controversial question in neuroscience. To tackle this issue, muscle activity is often subdivided into static and phasic components. The former corresponds to posture maintenance and transitions between postures. The latter corresponds to active movement production and the compensation for the kinetic properties of the limb. In the present study, we improved the methodology for this subdivision of muscle activity into static and phasic components by relating them to joint torques. Ten healthy subjects pointed in virtual reality to visual targets arranged to create a standard center-out reaching task in three dimensions. Muscle activity and motion capture data were synchronously collected during the movements. The motion capture data were used to calculate postural and dynamic components of active muscle torques using a dynamic model of the arm with 5 degrees of freedom. Principal Component Analysis (PCA) was then applied to muscle activity and the torque components, separately, to reduce the dimensionality of the data. Muscle activity was also reconstructed from gravitational and dynamic torque components. Results show that the postural and dynamic components of muscle torque represent a significant amount of variance in muscle activity. This method could be used to define static and phasic components of muscle activity using muscle torques

MLO Proteins from Tomato (Solanum lycopersicum L.) and Related Species in the Broad Phylogenetic Context

MLO proteins are a family of transmembrane proteins in land plants that play an important role in plant immunity and host–pathogen interactions, as well as a wide range of development processes. Understanding the evolutionary history of MLO proteins is important for understanding plant physiology and health. In the present work, we conducted a phylogenetic analysis on a large set of MLO protein sequences from publicly available databases, specifically emphasising MLOs from the tomato plant and related species. As a result, 4886 protein sequences were identified and used to construct a phylogenetic tree. In comparison to previous findings, we identified nine phylogenetic clades, revealed the internal structure of clades I and II as additional clades and showed the presence of monocotyledon species in all MLO clades. We identified a set of 19 protein motifs that allowed for the identification of particular clades. Sixteen SlMLO proteins from tomato were located in the phylogenetic tree and identified in relation to homologous sequences from other Solanaceae species. The obtained results could be useful for further work on the use of MLO proteins in the study of mildew resistance in Solanaceae and other plant families

Feasibility of Using Low-Cost Motion Capture for Automated Screening of Shoulder Motion Limitation after Breast Cancer Surgery

Objective To determine if a low-cost, automated motion analysis system using Microsoft Kinect could accurately measure shoulder motion and detect motion impairments in women following breast cancer surgery. Design Descriptive study of motion measured via 2 methods. Setting Academic cancer center oncology clinic. Participants 20 women (mean age = 60 yrs) were assessed for active and passive shoulder motions during a routine post-operative clinic visit (mean = 18 days after surgery) following mastectomy (n = 4) or lumpectomy (n = 16) for breast cancer. Interventions Participants performed 3 repetitions of active and passive shoulder motions on the side of the breast surgery. Arm motion was recorded using motion capture by Kinect for Windows sensor and on video. Goniometric values were determined from video recordings, while motion capture data were transformed to joint angles using 2 methods (body angle and projection angle). Main Outcome Measure Correlation of motion capture with goniometry and detection of motion limitation. Results Active shoulder motion measured with low-cost motion capture agreed well with goniometry (r = 0.70–0.80), while passive shoulder motion measurements did not correlate well. Using motion capture, it was possible to reliably identify participants whose range of shoulder motion was reduced by 40% or more. Conclusions Low-cost, automated motion analysis may be acceptable to screen for moderate to severe motion impairments in active shoulder motion. Automatic detection of motion limitation may allow quick screening to be performed in an oncologist\u27s office and trigger timely referrals for rehabilitation

Screening a collection of local and foreign varieties of Solanum lycopersicum L. in Kazakhstan for genetic markers of resistance against three tomato viruses

The tomato is one of the most important vegetable crops. The successful development of tomato cultures in Kazakhstan depends on the implementation of intensive agricultural methods, including breeding and selecting for new tomato varieties resistant to plant pathogens. Common tomato viruses, although not detected in our country to date, may potentially have a deleterious impact on agriculture if allowed to spread. The implementation of tomato breeding programs based on molecular markers of resistance is therefore an important preventive measure for protecting the agriculture and food safety of Kazakhstan. In the present work, we used nine molecular markers associated with resistance to three tomato viruses, i.e., tomato mosaic virus (ToMV), tomato spot wilt virus (TSWV), and tomato yellow leaf curl virus (TYLCV), to test the local breeding collection for the presence of genetic resistance factors. Two tomato varieties, ‘Zhiraf’ (Russia) and ‘Sunnik’ (Armenia), were revealed to possess the resistant allele marker PrRuG86-151 against ToMV; three hybrid forms had the same allele in the heterozygous state. One hybrid, based on the ‘Mirsini’ F1 variety from the Netherlands, had resistance to TSWV, which was confirmed by four markers: NCSw003, NCSw007, NCSw011, and NCSw012. Two cultivars, ‘Nicola’ and ‘Malinovyi Slon’ (Russia), and the local hybrid based on ‘Yarkiy Rumyanets’ had two to three resistant alleles of markers based on locus Tm-3 of resistance to TYLCV. The obtained results have demonstrated that the collection of tomato varieties involved in breeding programs in Kazakhstan lacks well-known genetic resistance factors to the considered tomato viruses. Thus, the prospective breeding programs require introduction of known resistant genetic resources to establish resistance to viruses using marker-assisted selection.Peer reviewe

Replication data for: Automated Assessment of Upper Extremity Movement Impairment Due To Stroke

This is replication data for the following manuscript: E.V. Olesh, S. Yakovenko, and V. Gritsenko (2014) Automated Assessment of Upper Extremity Movement Impairment Due To Stroke. PLOS ONE. In press. The data comprises joint angles in time captured from people with stroke performing several arm movements that are part of clinical tests of arm function

Replication Data for: Feasibility of Using Low-Cost Motion Capture for Automated Screening of Shoulder Motion Limitation after Breast Cancer Surgery

This document describes shared data that is the basis for the following manuscript: V. Gritsenko, E. Dailey, N. Kyle, M. Taylor, S. Whittacre, and A. K. Swisher (2015) Feasibility of Using Low-Cost Motion Capture for Automated Screening of Shoulder. PLOS ONE. In press. The data consists of shoulder joint angles of people recovering from surgery performing several arm movements designed to test active and passive range of motion at the shoulder. The data values are maximal angles calculated from motion capture by the Kinect sensor (Microsoft) and manual goniometry