Neural and non-neural related properties in the spastic wrist flexors: An optimization study.

Quantifying neural and non-neural contributions to increased joint resistance in spasticity is essential for a better understanding of its pathophysiological mechanisms and evaluating different intervention strategies. However, direct measurement of spasticity-related manifestations, e.g., motoneuron and biophysical properties in humans, is extremely challenging. In this vein, we developed a forward neuromusculoskeletal model that accounts for dynamics of muscle spindles, motoneuron pools, muscle activation and musculotendon of wrist flexors and relies on the joint angle and resistant torque as the only input measurement variables. By modeling the stretch reflex pathway, neural and non-neural related properties of the spastic wrist flexors were estimated during the wrist extension test. Joint angle and resistant torque were collected from 17 persons with chronic stroke and healthy controls using NeuroFlexor, a motorized force measurement device during the passive wrist extension test. The model was optimized by tuning the passive and stretch reflex-related parameters to fit the measured torque in each participant. We found that persons with moderate and severe spasticity had significantly higher stiffness than controls. Among subgroups of stroke survivors, the increased neural component was mainly due to a lower muscle spindle rate at 50% of the motoneuron recruitment. The motoneuron pool threshold was highly correlated to the motoneuron pool gain in all subgroups. The model can describe the overall resistant behavior of the wrist joint during the test. Compared to controls, increased resistance was predominantly due to higher elasticity and neural components. We concluded that in combination with the NeuroFlexor measurement, the proposed neuromusculoskeletal model and optimization scheme served as suitable tools for investigating potential parameter changes along the stretch-reflex pathway in persons with spasticity.

Antineutrophil cytoplasmic antibodies induce decreased CD62L expression and enhanced metabolic activity in monocytes.

Monocyte in vitro activation by antimyeloperoxidase (anti-MPO)- and antiproteinase-3 (anti-PR3)-positive sera, corresponding immunoglobulin G (IgG) fractions and monoclonal antibodies against MPO and PR3 was evaluated. The expression of adhesion molecules, l-selectin (CD62L) and CR3 (CD11b), involved in leucocyte endothelial adhesion, and metabolic activity, measured as the production of hydrogen peroxide, were analysed. Decreased expression of CD62L was demonstrated in monocytes after incubation with antineutrophil cytoplasmic antibody (ANCA)-positive sera. This finding was not accompanied by changes in CD11b expression. Metabolic activity was increased in monocytes after incubation with ANCA-positive IgG fractions as well as after incubation with monoclonal anti-MPO and anti-PR3. These findings support the concept that the pathophysiological effect of ANCA is partly mediated through the action on crucial events in monocyte activation, such as CD62L downregulation and oxygen radical production.

Precision grip force dynamics: a system identification approach.

A linear model of the dynamics of the human precision grip is presented. The transfer function is identified as representing the peripheral motor subsystem, from the motoneuron pool to the final production of a grip force between the tip of the index finger and the thumb. The transfer function captures the limiting isometric muscle dynamics that, e.g., cortical motor areas have to act through. When identifying the transfer function we introduce a novel technique, common subsystem identification. This characterizes a specific subsystem in a complex biomechanical system. This technique requires data from two functionally different experiments that both involve the subsystem of interest. Two transfer functions, one for each experiment, are then estimated using a linear black box technique. The common mathematical factors, represented by poles and zeros, are used to form a new transfer function. It is concluded that this transfer function represents the common biological subsystem involved in both experiments. Here, we use one active and one reactive isometric grip force experiment to capture the subsystem of interest, i.e., the motoneuron pool, motor units, muscles, tendons and fingertip tissue. The characteristics of the dynamics are in agreement with previously published experiments on human neuro-muscular systems. The model, H(s) = 280/(s2 + 22s + 280), is well suited for the representation of a force producing end-effector in simulations including a control system with sensory feedback.

Cortical activity in precision- versus power-grip tasks: an fMRI study.

Most manual grips can be divided in precision and power grips on the basis of phylogenetic and functional considerations. We used functional magnetic resonance imaging to compare human brain activity during force production by the right hand when subjects used a precision grip and a power grip. During the precision-grip task, subjects applied fine grip forces between the tips of the index finger and the thumb. During the power-grip task, subjects squeezed a cylindrical object using all digits in a palmar opposition grasp. The activity recorded in the primary sensory and motor cortex contralateral to the operating hand was higher when the power grip was applied than when subjects applied force with a precision grip. In contrast, the activity in the ipsilateral ventral premotor area, the rostral cingulate motor area, and at several locations in the posterior parietal and prefrontal cortices was stronger while making the precision grip than during the power grip. The power grip was associated predominately with contralateral left-sided activity, whereas the precision-grip task involved extensive activations in both hemispheres. Thus our findings indicate that in addition to the primary motor cortex, premotor and parietal areas are important for control of fingertip forces during precision grip. Moreover, the ipsilateral hemisphere appears to be strongly engaged in the control of precision-grip tasks performed with the right hand.