Effect of the soft tissue artifact on marker measurements and on the calculation of the helical axis of the knee during a squat movement: A study on the CAMS-Knee dataset.

BACKGROUND: Marker-based motion capture recordings of human body segments are often affected by soft tissue artifact (STA). The undesired and uncontrolled motion of the skin may introduce errors in the estimation of motion and position of body segments and, consequently, in the calculation of the relative functional quantities. METHODS: This study exploited a recently published dataset consisting of six adult subjects that underwent a total knee arthroplasty. The subject performed squat tasks while the motion was concurrently recorded by passive markers attached to the skin of the lower limbs, an optoelectronic system, and a fluoroscope. The STA of shank and thigh was decomposed in local deformation and rigid motion. Additionally, we studied how the instantaneous helical axis (IHA) calculation is affected by STA. FINDINGS: The cluster most affected by STA rigid motion was the thigh. The largest estimated effects were about 7 deg. and about 20 mm. The largest effect of local deformation was about 25 mm, and it was observed on the thigh cluster. INTERPRETATION: The STA made the estimation of the IHA unreliable for both position and direction. The choice of the reference configuration influenced the results of the STA analysis.

An optimal method for calculating an average screw axis for a joint, with improved sensitivity to noise and providing an analysis of the dispersion of the instantaneous axes.

The instantaneous (ISA) and average (ASA) screw axes are techniques commonly adopted in motion analysis to functionally locate the rotation axis and center of rotation of a joint. Several approaches for calculating such axes were proposed in literature and the main limitations were identified as the need for using a threshold on angular displacements or velocities for handling the cases where the ISA is ill-defined and the need for a method for reliably estimating the center or rotation in limit cases, such as a purely rotational motion in the three-dimensional space. Furthermore, in many applications, such as in biomechanics, it is useful to statistically estimate the dispersion or variation of the ISA with respect to the ASA. In this paper we propose a novel method for estimating an ASA. Our method represents an improvement over previous methods as it: (i) exploits an optimization procedure based on the instantaneous differential kinematics (screw twist); (ii) removes the need for a threshold by introducing a weighting based on the norm of angular velocity; (iii) handles the singular cases where the position of the ASA is ill-defined by proposing a regularization term in the optimization. In addition, we proposed a method for estimating the uncertainty in the ASA calculation. The same quantities serve as a measure of the dispersion of the ISAs with respect to the ASA. The method was tested on real data and surrogate data: (i) a human gait analysis trial representing the motion of a knee, (ii) the experimental recording of the free swing motion of a mechanical hinge and (iii) synthetically generated motion data of a purely rotational (cylindrical) motion. The results showed that the new method had a lower sensitivity to noise, was able to reasonably handle the singular cases and provide a detailed analysis of ISA dispersion.

A Novel Procedure for Knee Flexion Angle Estimation Based on Functionally Defined Coordinate Systems and Independent of the Marker Landmarks.

Knee angles are kinematic quantities that are commonly presented in gait analysis reports. They are typically calculated as the relative angles between the anatomical coordinate systems rigidly attached to the femur and the tibia. To give these angles a biomechanical meaning, the coordinate systems must be defined with respect to some anatomical landmarks. For example, if one axis of the joint coordinate systems is directed along the knee flexion/extension axis, then the relative angle assumes the meaning of flexion/extension angle. Defining accurate anatomical coordinate systems is not an easy task, because it requires skills in marker placement, landmark identification and definition of a biomechanical model. In this paper, we present a novel method to (i) functionally define two coordinate systems attached to femur and tibia and (ii) functionally calculate the knee angle based on the relative differential kinematics between the previously defined coordinate systems. As the main limitation, this method is unable to provide an absolute measurement of the knee flexion/extension angle; however, it is able to accurately capture and display the relative angular motion of the knee. We show that our method produced consistent results even when the measured coordinate systems were randomly modified, removing any anatomical referencing. The proposed method has the advantage of being independent/invariant of the choice of the original coordinate systems of the femur and tibia, removing the need for accurate marker placement. Some major consequences are that (i) the markers may be placed on optimal landmarks, for example, minimizing the soft tissue artifacts or improving the subject's comfort, and (ii) there is no need for anatomical calibration when technical marker clusters/triads are used.

Effect of the soft tissue artifact on marker measurements and on the calculation of the helical axis of the knee during a gait cycle: A study on the CAMS-Knee data set.

The soft tissue artifact (STA) is a phenomenon occurring when the motion of bones or anatomical segments is measured by means of skin markers: the biological tissues between the markers and the bone produce a relative motion bone-markers that leads to inaccuracies in the estimation of rigid body poses or kinematics. The aim of this study was to quantify the STA by exploiting a recently published gait analysis dataset. The dataset was composed of six adult subjects with a total knee arthroplasty who underwent gait analysis trials. The motion of the knee was concurrently recorded by means of (i) fluoroscopy imaging and (ii) an optoelectronic system and redundant markers attached to the thigh and shank. The STA was studied by comparing the results calculated on the marker sets with the results obtained from the fluoroscopy data. The stance and swing phases were considered separately. Rigid STA motion and local STA deformation were studied separately. In addition to previous studies, the instantaneous helical axis (IHA) of the knee was calculated and the effect of the STA on its calculation was assessed. The largest rigid-motion STA effect was observed on the thigh cluster (~10 deg. and ~ 18 mm). The shank cluster was mainly affected during the swing phase (~7 deg. and ~ 17 mm). The local STA deformation affected differently the markers. The largest effect was ~16 mm and the lowest was ~4 mm. The estimation of the IHA was not reliable when based only on markers, having an estimation error of ~17 deg. and ~ 25 mm. A high variability of results across subjects was observed.

Gait Trajectory and Event Prediction from State Estimation for Exoskeletons During Gait.

A real-time method is proposed to obtain a single, consistent probabilistic model to predict future joint angles, velocities, accelerations and jerks, together with the timing for the initial contact, foot flat, heel off and toe off events. In a training phase, a probabilistic principal component model is learned from normal walking, which is used in the online phase for state estimation and prediction. This is validated for normal walking and walking with an exoskeleton. Without exoskeleton, both joint trajectories and gait events are predicted without bias. With exoskeleton, the trajectory prediction is unbiased, but event prediction is slightly biased with a maximum of 33 ms for the toe off event. Performance is compared with predictions based on only the population mean. Without exoskeleton, estimation errors are 5 to 30% lower with our method. With exoskeleton, trajectory prediction errors are up to 20% lower, but gait event prediction errors only improve for foot flat (30%) and are worse for other events (30%-50%). The ability to predict future joint trajectories and gait events offers opportunities to design exoskeleton controllers which anticipate these trajectories and events, allowing better tracking control and smoother, accurately timed transitions between different control modes.

Estimating the Instantaneous Screw Axis and the Screw Axis Invariant Descriptor of Motion by Means of Inertial Sensors: An Experimental Study with a Mechanical Hinge Joint and Comparison to the Optoelectronic System.

The motion of a rigid body can be represented by the instantaneous screw axis (ISA, also known as the helical axis). Recently, an invariant representation of motion based on the ISA, namely, the screw axis invariant descriptor (SAID), was proposed in the literature. The SAID consists of six scalar features that are independent from the coordinate system chosen to represent the motion. This method proved its usefulness in robotics; however, a high sensitivity to noise was observed. This paper aims to explore the performance of inertial sensors for the estimation of the ISA and the SAID for a simple experimental setup based on a hinge joint. The free swing motion of the mechanical hinge was concurrently recorded by a marker-based optoelectronic system (OS) and two magnetic inertial measurement units (MIMUs). The ISA estimated by the MIMU was more precise, while the OS was more accurate. The mean angular error was ≈2.2° for the OS and was ≈4.4° for the MIMU, while the mean standard deviation was ≈2.3° for the OS and was ≈0.2° for the MIMU. The SAID features based on angular velocity were better estimated by the MIMU, while the features based on translational velocity were better estimated by the OS. Therefore, a combination of both measurements systems is recommended to accurately estimate the complete SAID.

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements.

Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground reaction forces and moments (GRFM). Measuring GRFM is however only possible in a controlled environment. This paper introduces a probabilistic method based on probabilistic principal component analysis to estimate the joint torques for healthy gait without measured GRFM. A gait dataset of 23 subjects was obtained containing kinematics, measured GRFM and joint torques from inverse dynamics in order to obtain a probabilistic model. This model was then used to estimate the joint torques of other subjects without measured GRFM. Only kinematics, a skeletal model and timing of gait events are needed. Estimation only takes 0.28 ms per time instant. Using cross-validation, the resulting root mean square estimation errors for the lower-limb joint torques are found to be approximately 0.1 Nm/kg, which is 6-18% of the range of the ground truth joint torques. Estimated joint torque and GRFM errors are up to two times smaller than model-based state-of-the-art methods. Model-free artificial neural networks can achieve lower errors than our method, but are less repeatable, do not contain uncertainty information on the estimates and are difficult to use in situations which are not in the learning set. In contrast, our method performs well in a new situation where the walking speed is higher than in the learning dataset. The method can for example be used to estimate the kinetics during overground walking without force plates, during treadmill walking without (separate) force plates and during ambulatory measurements.

Inverse dynamic estimates of muscle recruitment and joint contact forces are more realistic when minimizing muscle activity rather than metabolic energy or contact forces.

BACKGROUND: Assessment of contact forces is essential for a better understanding of mechanical factors affecting progression of osteoarthritis. Since contact forces cannot be measured non-invasively, computer simulations are often used to assess joint loading. Contact forces are to a large extent determined by muscle forces. These muscle forces are computed using optimization techniques that solve the muscle redundancy problem by assuming that muscles are coordinated in a way that optimizes performance (e.g., minimizes muscle activity or metabolic energy). However, it is unclear which of the many proposed performance criteria best describes muscle coordination. RESEARCH QUESTION: Which performance criterion best describes muscle recruitment patterns and knee contact forces recorded using electromyography (EMG) and load cell instrumented prostheses?. METHODS: We solved the muscle redundancy problem based on six different groups of performance criteria: muscle activations, volume-scaled activations, forces, stresses, metabolic energy, and joint contact forces. Computed muscle excitations and knee contact forces during over-ground walking were validated against recorded EMG signals and measured contact forces for four subjects with instrumented knee prostheses in the "Grand Challenge Competition to Predict in Vivo Knee Loads" dataset. RESULTS: Performance criteria based on either stress or muscle activation (either unscaled or scaled by muscle volume), both to a power of 3 or 4, resulted in the best agreement between measured and simulated values. These performance criteria outperformed all other criteria in terms of agreement between simulated muscle excitations and EMG, whereas good agreement between measured and predicted contact forces was also observed for minimization of contact forces and metabolic energy. SIGNIFICANCE: Given the large differences in accuracy obtained with different performance criteria (e.g., root mean square errors of contact forces differed up to 0.45 body weight), the results of our study are important to improve the validity of in silico assessment of joint loading.

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements.

BACKGROUND: Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. METHODS: The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. RESULTS: Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. CONCLUSIONS: This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.

Subject-Exoskeleton Contact Model Calibration Leads to Accurate Interaction Force Predictions.

Knowledge of human-exoskeleton interaction forces is crucial to assess user comfort and effectiveness of the interaction. The subject-exoskeleton collaborative movement and its interaction forces can be predicted in silico using computational modeling techniques. We developed an optimal control framework that consisted of three phases. First, the foot-ground (Phase A) and the subject-exoskeleton (Phase B) contact models were calibrated using three experimental sit-to-stand trials. Then, the collaborative movement and the subject-exoskeleton interaction forces, of six different sit-to-stand trials were predicted (Phase C). The results show that the contact models were able to reproduce experimental kinematics of calibration trials (mean root mean square differences - RMSD - coordinates ≤ 1.1° and velocities ≤ 6.8°/s), ground reaction forces (mean RMSD≤ 22.9 N), as well as the interaction forces at the pelvis, thigh, and shank (mean RMSD ≤ 5.4 N). Phase C could predict the collaborative movements of prediction trials (mean RMSD coordinates ≤ 3.5° and velocities ≤ 15.0°/s), and their subject-exoskeleton interaction forces (mean RMSD ≤ 13.1° N). In conclusion, this optimal control framework could be used while designing exoskeletons to have in silico knowledge of new optimal movements and their interaction forces.

Crystallographic and thermodynamic characterization of phenylaminopyridine bisphosphonates binding to human farnesyl pyrophosphate synthase.

Human farnesyl pyrophosphate synthase (hFPPS) catalyzes the production of the 15-carbon isoprenoid farnesyl pyrophosphate. The enzyme is a key regulator of the mevalonate pathway and a well-established drug target. Notably, it was elucidated as the molecular target of nitrogen-containing bisphosphonates, a class of drugs that have been widely successful against bone resorption disorders. More recently, research has focused on the anticancer effects of these inhibitors. In order to achieve increased non-skeletal tissue exposure, we created phenylaminopyridine bisphosphonates (PNP-BPs) that have bulky hydrophobic side chains through a structure-based approach. Some of these compounds have proven to be more potent than the current clinical drugs in a number of antiproliferation assays using multiple myeloma cell lines. In the present work, we characterized the binding of our most potent PNP-BPs to the target enzyme, hFPPS. Co-crystal structures demonstrate that the molecular interactions designed to elicit tighter binding are indeed established. We carried out thermodynamic studies as well; the newly introduced protein-ligand interactions are clearly reflected in the enthalpy of binding measured, which is more favorable for the new PNP-BPs than for the lead compound. These studies also indicate that the affinity of the PNP-BPs to hFPPS is comparable to that of the current drug risedronate. Risedronate forms additional polar interactions via its hydroxyl functional group and thus exhibits more favorable binding enthalpy; however, the entropy of binding is more favorable for the PNP-BPs, owing to the greater desolvation effects resulting from their large hydrophobic side chains. These results therefore confirm the overall validity of our drug design strategy. With a distinctly different molecular scaffold, the PNP-BPs described in this report represent an interesting new group of future drug candidates. Further investigation should follow to characterize the tissue distribution profile and assess the potential clinical benefits of these compounds.

Real-Time Gait Event Detection Based on Kinematic Data Coupled to a Biomechanical Model.

Real-time detection of multiple stance events, more specifically initial contact (IC), foot flat (FF), heel off (HO), and toe off (TO), could greatly benefit neurorobotic (NR) and neuroprosthetic (NP) control. Three real-time threshold-based algorithms have been developed, detecting the aforementioned events based on kinematic data in combination with a biomechanical model. Data from seven subjects walking at three speeds on an instrumented treadmill were used to validate the presented algorithms, accumulating to a total of 558 steps. The reference for the gait events was obtained using marker and force plate data. All algorithms had excellent precision and no false positives were observed. Timing delays of the presented algorithms were similar to current state-of-the-art algorithms for the detection of IC and TO, whereas smaller delays were achieved for the detection of FF. Our results indicate that, based on their high precision and low delays, these algorithms can be used for the control of an NR/NP, with the exception of the HO event. Kinematic data is used in most NR/NP control schemes and is thus available at no additional cost, resulting in a minimal computational burden. The presented methods can also be applied for screening pathological gait or gait analysis in general in/outside of the laboratory.

Targeting Bacillosamine Biosynthesis in Bacterial Pathogens: Development of Inhibitors to a Bacterial Amino-Sugar Acetyltransferase from Campylobacter jejuni.

The glycoproteins of selected microbial pathogens often include highly modified carbohydrates such as 2,4-diacetamidobacillosamine (diNAcBac). These glycoconjugates are involved in host-cell interactions and may be associated with the virulence of medically significant Gram-negative bacteria. In light of genetic studies demonstrating the attenuated virulence of bacterial strains in which modified carbohydrate biosynthesis enzymes have been knocked out, we are developing small molecule inhibitors of selected enzymes as tools to evaluate whether such compounds modulate virulence. We performed fragment-based and high-throughput screens against an amino-sugar acetyltransferase enzyme, PglD, involved in biosynthesis of UDP-diNAcBac in Campylobacter jejuni. Herein we report optimization of the hits into potent small molecule inhibitors (IC50 < 300 nM). Biophysical characterization shows that the best inhibitors are competitive with acetyl coenzyme A and an X-ray cocrystal structure reveals that binding is biased toward occupation of the adenine subpocket of the AcCoA binding site by an aromatic ring.

Mechanical effort predicts the selection of ankle over hip strategies in nonstepping postural responses.

Experimental studies have shown that a continuum of ankle and hip strategies is used to restore posture following an external perturbation. Postural responses can be modeled by feedback control with feedback gains that optimize a specific objective. On the one hand, feedback gains that minimize effort have been used to predict muscle activity during perturbed standing. On the other hand, hip and ankle strategies have been predicted by minimizing postural instability and deviation from upright posture. It remains unclear, however, whether and how effort minimization influences the selection of a specific postural response. We hypothesize that the relative importance of minimizing mechanical work vs. postural instability influences the strategy used to restore upright posture. This hypothesis was investigated based on experiments and predictive simulations of the postural response following a backward support surface translation. Peak hip flexion angle was significantly correlated with three experimentally determined measures of effort, i.e., mechanical work, mean muscle activity and metabolic energy. Furthermore, a continuum of ankle and hip strategies was predicted in simulation when changing the relative importance of minimizing mechanical work and postural instability, with increased weighting of mechanical work resulting in an ankle strategy. In conclusion, the combination of experimental measurements and predictive simulations of the postural response to a backward support surface translation showed that the trade-off between effort and postural instability minimization can explain the selection of a specific postural response in the continuum of potential ankle and hip strategies.

Control of a hybrid robotic system for computer-assisted interventions in dynamic environments.

PURPOSE: Minimally invasive surgery is becoming the standard treatment of care for a variety of procedures. Surgeons need to display a high level of proficiency to overcome the challenges imposed by the minimal access. Especially when operating on a dynamic organ, it becomes very difficult to align instruments reliably and precisely. In this paper, a hybrid rigid/continuum robotic system and a dedicated robotic control approach are proposed to assist the surgeon performing complex surgical gestures in a dynamic environment. METHODS: The proposed robotic system consists of a rigid robot arm on top of which a continuum robot is mounted in series. The continuum robot is locally actuated with McKibben muscles. A control scheme based on quadratic programming framework is adopted. It is shown that the framework allows enforcing a set of constraints on the pose of the tip, as well as of the instrument shaft, which is commanded to slide in and out through the entry point. RESULTS: Through simulation and experiments, it is shown how the robot tool tip is able to follow sinusoidal trajectories of 0.37 and 2 Hz, while maintaining the instrument shaft pivoting along the entry point. The positioning and tracking accuracy of such system are shown to lie below 4.7 mm in position and [Formula: see text] in angle. CONCLUSION: The results suggest a good potential for applying the proposed technology to assist the surgeon during complex robot-assisted interventions. It is also illustrated that even when using flexible hence relatively safe end-effectors, it is possible to reach acceptable tracking behaviour at relatively high frequencies.

Sensitivity of predicted muscle forces during gait to anatomical variability in musculotendon geometry.

Scaled generic musculoskeletal models are commonly used to drive dynamic simulations of motions. It is however, acknowledged that not accounting for variability in musculoskeletal geometry and musculotendon parameters may confound the simulation results, even when analysing control subjects. This study documents the three-dimensional anatomical variability of musculotendon origins and insertions of 33 lower limb muscles determined based on magnetic resonance imaging in six subjects. This anatomical variability was compared to the musculotendon point location in a generic musculoskeletal model. Furthermore, the sensitivity of muscle forces during gait, calculated using static optimization, to perturbations of the musculotendon point location was analyzed with a generic model. More specific, a probabilistic approach was used: for each analyzed musculotendon point, the three-dimensional location was re-sampled with a uniform Latin hypercube method within the anatomical variability and the static optimization problem was then re-solved for all perturbations. We found that musculotendon point locations in the generic model showed only variable correspondences with the anatomical variability. The anatomical variability of musculotendon point location did affect the calculated muscle forces: muscles most sensitive to perturbations within the anatomical variability are iliacus and psoas. Perturbation of the gluteus medius anterior, iliacus and psoas induces the largest concomitant changes in muscle forces of the unperturbed muscles. Therefore, when creating subject-specific musculoskeletal models, these attachment points should be defined accurately. In addition, the size of the anatomical variability of the musculotendon point location was not related to the sensitivity of the calculated muscle forces.

Probing the molecular and structural elements of ligands binding to the active site versus an allosteric pocket of the human farnesyl pyrophosphate synthase.

In order to explore the interactions of bisphosphonate ligands with the active site and an allosteric pocket of the human farnesyl pyrophosphate synthase (hFPPS), substituted indole and azabenzimidazole bisphosphonates were designed as chameleon ligands. NMR and crystallographic studies revealed that these compounds can occupy both sub-pockets of the active site cavity, as well as the allosteric pocket of hFPPS in the presence of the enzyme's Mg(2+) ion cofactor. These results are consistent with the previously proposed hypothesis that the allosteric pocket of hFPPS, located near the active site, plays a feed-back regulatory role for this enzyme.

The effect of muscle weakness on the capability gap during gross motor function: a simulation study supporting design criteria for exoskeletons of the lower limb.

BACKGROUND: Enabling persons with functional weaknesses to perform activities of daily living (ADL) is one of the main challenges for the aging society. Powered orthoses, or exoskeletons, have the potential to support ADL while promoting active participation of the user. For this purpose, assistive devices should be designed and controlled to deliver assistance as needed (AAN). This means that the level of assistance should bridge the capability gap, i.e. the gap between the capabilities of the subjects and the task requirements. However, currently the actuators of exoskeletons are mainly designed using inverse dynamics (ID) based calculations of joint moments. The goal of the present study is to calculate the capability gap for the lower limb during ADL when muscle weakness is present, which is needed for appropriate selection of actuators to be integrated in exoskeletons. METHODS: A musculoskeletal model (MM) is used to calculate the joint kinematics, joint kinetics and muscle forces of eight healthy subjects during ADL (gait, sit-to-stand, stand-to-sit, stair ascent, stair descent). Muscle weakness was imposed to the MM by a stepwise decrease in maximal isometric force imposed to all muscles. Muscle forces were calculated using static optimization. In order to compensate for muscle weakness, ideal moment actuators that represent the motors of an exoskeleton in the simulation were added to deliver AAN required to perform the task. RESULTS: The ID approach overestimates the required assistance since it relies solely on the demands of the task, whereas the AAN approach incorporates the capabilities of the subject. Furthermore, the ID approach delivers continuous support whereas the AAN approach targets the period where a capability gap occurs. The level of muscle weakness for which the external demands imposed by ADL can no longer be met by active muscle force production, is respectively 40%, 70%, 80% and 30%. CONCLUSIONS: The present workflow allows estimating the AAN during ADL for different levels of muscle weakness, which can be used in the mechatronic design and control of powered exoskeletons. The AAN approach is a more physiological approach than the ID approach, since the MM accounts for the subject-specific capabilities of the user.

Multistage screening reveals chameleon ligands of the human farnesyl pyrophosphate synthase: implications to drug discovery for neurodegenerative diseases.

Human farnesyl pyrophosphate synthase (hFPPS) is the gate-keeper of mammalian isoprenoids and the key target of bisphosphonate drugs. Bisphosphonates suffer from poor "drug-like" properties and are mainly effective in treating skeletal diseases. Recent investigations have implicated hFPPS in various nonskeletal diseases, including Alzheimer's disease (AD). Analysis of single nucleotide polymorphisms in the hFPPS gene and mRNA levels in autopsy-confirmed AD subjects was undertaken, and a genetic link between hFPPS and phosphorylated tau (P-Tau) levels in the human brain was identified. Elevated P-Tau levels are strongly implicated in AD progression. The development of nonbisphosphonate inhibitors can provide molecular tools for validating hFPPS as a therapeutic target for tauopathy-associated neurodegeneration. A multistage screening protocol led to the identification of a new monophosphonate chemotype that bind in an allosteric pocket of hFPPS. Optimization of these compounds could lead to human therapeutics that block tau metabolism and arrest the progression of neurodegeneration.

Altering length and velocity feedback during a neuro-musculoskeletal simulation of normal gait contributes to hemiparetic gait characteristics.

BACKGROUND: Spasticity is an important complication after stroke, especially in the anti-gravity muscles, i.e. lower limb extensors. However the contribution of hyperexcitable muscle spindle reflex loops to gait impairments after stroke is often disputed. In this study a neuro-musculoskeletal model was developed to investigate the contribution of an increased length and velocity feedback and altered reflex modulation patterns to hemiparetic gait deficits. METHODS: A musculoskeletal model was extended with a muscle spindle model providing real-time length and velocity feedback of gastrocnemius, soleus, vasti and rectus femoris during a forward dynamic simulation (neural control model). By using a healthy subject's base muscle excitations, in combination with increased feedback gains and altered reflex modulation patterns, the effect on kinematics was simulated. A foot-ground contact model was added to account for the interaction effect between the changed kinematics and the ground. The qualitative effect i.e. the directional effect and the specific gait phases where the effect is present, on the joint kinematics was then compared with hemiparetic gait deviations reported in the literature. RESULTS: Our results show that increased feedback in combination with altered reflex modulation patterns of soleus, vasti and rectus femoris muscle can contribute to excessive ankle plantarflexion/inadequate dorsiflexion, knee hyperextension/inadequate flexion and increased hip extension/inadequate flexion during dedicated gait cycle phases. Increased feedback of gastrocnemius can also contribute to excessive plantarflexion/inadequate dorsiflexion, however in combination with excessive knee and hip flexion. Increased length/velocity feedback can therefore contribute to two types of gait deviations, which are both in accordance with previously reported gait deviations in hemiparetic patients. Furthermore altered modulation patterns, in particular the reduced suppression of the muscle spindle feedback during swing, can contribute largely to an increased plantarflexion and knee extension during the swing phase and consequently to hampered toe clearance. CONCLUSIONS: Our results support the idea that hyperexcitability of length and velocity feedback pathways, especially in combination with altered reflex modulation patterns, can contribute to deviations in hemiparetic gait. Surprisingly, our results showed only subtle temporal differences between length and velocity feedback. Therefore, we cannot attribute the effects seen in kinematics to one specific type of feedback.