Predictive Simulation of Gait at Low Gravity Reveals Skipping as the Preferred Locomotion Strategy

The investigation of gait strategies at low gravity environments gained momentum recently as manned missions to the Moon and to Mars are reconsidered. Although reports by astronauts of the Apollo missions indicate alternative gait strategies might be favored on the Moon, computational simulations and experimental investigations have been almost exclusively limited to the study of either walking or running, the locomotion modes preferred under Earth\u27s gravity. In order to investigate the gait strategies likely to be favored at low gravity a series of predictive, computational simulations of gait are performed using a physiological model of the musculoskeletal system, without assuming any particular type of gait. A computationally efficient optimization strategy is utilized allowing for multiple simulations. The results reveal skipping as more efficient and less fatiguing than walking or running and suggest the existence of a walk–skip rather than a walk–run transition at low gravity. The results are expected to serve as a background to the design of experimental investigations of gait under simulated low gravity

Optimality Principles for Model-Based Prediction of Human Gait

Although humans have a large repertoire of potential movements, gait patterns tend to be stereotypical and appear to be selected according to optimality principles such as minimal energy. When applied to dynamic musculoskeletal models such optimality principles might be used to predict how a patient\u27s gait adapts to mechanical interventions such as prosthetic devices or surgery. In this paper we study the effects of different performance criteria on predicted gait patterns using a 2D musculoskeletal model. The associated optimal control problem for a family of different cost functions was solved utilizing the direct collocation method. It was found that fatigue-like cost functions produced realistic gait, with stance phase knee flexion, as opposed to energy-related cost functions which avoided knee flexion during the stance phase. We conclude that fatigue minimization may be one of the primary optimality principles governing human gait

Concurrent Muscoskeletal Dynamics and Finite Element Analysis Predicts Altered Gait Patterns to Reduce Foot Tissue Loading

Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care

Concurrent Muscoskeletal Dynamics and Finite Element Analysis Predicts Altered Gait Patterns to Reduce Foot Tissue Loading

Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care

Modelo transteórico de mudança de comportamentos na promoção da actividade física nas grávidas

Determinar se o Modelo Transteórico de Mudança de Comportamento (MTMC) é eficaz na promoção da actividade física (AF) nas grávidas. O grupo experimental (GE) participou no projecto “Mães em Movimento” baseado no MTMC. Aplicou-se o Questionário de AF para Gestantes, Escala de Estados de Mudança, Behavioural Regulation in Exercise Questionnaire e Questionário de Conhecimentos. Na 2ª avaliação, no GE, todas as grávidas referiram praticar AF. A motivação intrínseca e os conhecimentos aumentaram. O MTMC revelou-se um modelo eficaz na promoção da AF em grávidas.To determine whether the Transtheoretical Model of Behavior Change (TTM) is effective in promoting physical activity (PA) in pregnant women. The experimental group (EG), participated in the "Moms in Motion" based on the TTM. It was applied the Pregnancy Physical Activity Questionnaire, Stages of Change Questionnaire, Behavioral Regulation in Exercise Questionnaire and Skills Questionnaire. In the 2nd evaluation, in EG, all women reported practicing PA. The intrinsic motivation and knowledge increased. The TTM revealed to be an effective model in promoting PA habits in pregnant women

Fine Mapping the Spatial Distribution and Concentration of Unlabeled Drugs within Tissue Micro-Compartments Using Imaging Mass Spectrometry

Readouts that define the physiological distributions of drugs in tissues are an unmet challenge and at best imprecise, but are needed in order to understand both the pharmacokinetic and pharmacodynamic properties associated with efficacy. Here we demonstrate that it is feasible to follow the in vivo transport of unlabeled drugs within specific organ and tissue compartments on a platform that applies MALDI imaging mass spectrometry to tissue sections characterized with high definition histology. We have tracked and quantified the distribution of an inhaled reference compound, tiotropium, within the lungs of dosed rats, using systematic point by point MS and MS/MS sampling at 200 µm intervals. By comparing drug ion distribution patterns in adjacent tissue sections, we observed that within 15 min following exposure, tiotropium parent MS ions (mass-to-charge; m/z 392.1) and fragmented daughter MS/MS ions (m/z 170.1 and 152.1) were dispersed in a concentration gradient (80 fmol-5 pmol) away from the central airways into the lung parenchyma and pleura. These drug levels agreed well with amounts detected in lung compartments by chemical extraction. Moreover, the simultaneous global definition of molecular ion signatures localized within 2-D tissue space provides accurate assignment of ion identities within histological landmarks, providing context to dynamic biological processes occurring at sites of drug presence. Our results highlight an important emerging technology allowing specific high resolution identification of unlabeled drugs at sites of in vivo uptake and retention

Patients with COVID-19: in the dark-NETs of neutrophils.

SARS-CoV-2 infection poses a major threat to the lungs and multiple other organs, occasionally causing death. Until effective vaccines are developed to curb the pandemic, it is paramount to define the mechanisms and develop protective therapies to prevent organ dysfunction in patients with COVID-19. Individuals that develop severe manifestations have signs of dysregulated innate and adaptive immune responses. Emerging evidence implicates neutrophils and the disbalance between neutrophil extracellular trap (NET) formation and degradation plays a central role in the pathophysiology of inflammation, coagulopathy, organ damage, and immunothrombosis that characterize severe cases of COVID-19. Here, we discuss the evidence supporting a role for NETs in COVID-19 manifestations and present putative mechanisms, by which NETs promote tissue injury and immunothrombosis. We present therapeutic strategies, which have been successful in the treatment of immunο-inflammatory disorders and which target dysregulated NET formation or degradation, as potential approaches that may benefit patients with severe COVID-19

Dynamik und Energieaufwand des Gehens mit Beinprothesen

In Biomechanics musculoskeletal models have been proposed and increasingly used to investigate human walking by means of computational simulations. The skeletal system is often modeled by multibody systems composed of rigid bodies, while the biological actuator is almost exclusively modeled by Hill-type muscle models due to its suitability to computational investigations. The study of normal and pathological walking necessarily involves the consideration of the energetic demand, since it was shown that the energetic demand per unit of distance traveled is the primary performance criterion during walking. These models are used to investigate walking, for instance, by computing moments at the joints required to perform an observed motion using inverse dynamics, by estimating muscle forces from joint moments using optimization techniques, and by generating optimal normal and pathological walking patterns. In spite of the increasing use of computational simulation of gait, the large-scale musculoskeletal models required lead frequently to a prohibitive computational effort, in particular when optimization procedures are involved, preventing its wider use in clinical applications. This dissertation covers part of this wide spectrum of problems in biomechanics focusing on the investigation of normal and pathological walking, in particular prosthetic walking, and on the development of methods that offer alternatives to conventional approaches that either require overwhelming computational effort or deliver unrealistic estimations. In order to investigate the burden caused by lower limb assistive devices experiments are designed to emulate typical deviations of the mechanical properties of the lower limbs caused by prosthetic and orthotic devices. The experiments are performed in a gait analysis laboratory, and the kinematics is reconstructed from markers attached on anatomical landmarks of two subjects. The reconstructed kinematics and measured ground reaction forces are then used to estimate joint moments by inverse dynamics. The results for the kinematics and joint moments for all experiments and subjects are compared and discussed concerning possible contributions to the understanding of prosthetic and orthotic walking. The determination of individual muscle forces has many applications including the assessment of muscle coordination and internal loads on joints and bones, useful for instance, for the design of endoprostheses. Because muscle forces cannot be directly measured without invasive techniques, they are often estimated from joint moments by means of optimization procedures that search for a unique solution among the infinite muscle forces that generate the same joint moments. The conventional method to solve this problem, the static optimization, is computationally efficient but neglects the dynamics involved in muscle force generation and requires the use of an instantaneous cost function, leading often to unrealistic estimations of muscle forces. An alternative is using dynamic optimization associated with a motion tracking, which is, however, computationally very costly. Two alternative approaches are proposed to overcome the limitations of static optimization delivering more realistic estimations of muscle forces while being computationally less expensive than dynamic optimization. One of the great challenges in biomechanics of human walking is the use of the complex, large-scale models of the musculoskeletal system in predictive investigations of pathological gait, for instance, to help on the design of assistive devices, therapies or surgical interventions. The prohibitive computational effort required by dynamic optimization, the conventional approach used to generate optimal walking patterns, prevents a wider use of dynamic simulation of gait for clinical applications. An alternative to avoid the several integrations of the state equations, the major cause for the high computational effort, is the use of inverse dynamics-based methods. Such methods have been used, for instance, in robotics and character animation, but have been poorly explored in biomechanics. Therefore, an inverse dynamics-based approach to simulate human motion that deals with the overdeterminacy of muscle actuation and uses Hill-type muscle models is proposed, too. This approach is applied to generate normal walking patterns, to investigate the gait with a bilateral 2 kg-increase in feet mass, and to predict skeleton motion, muscle coordination and metabolic cost of walking with three different bilateral transtibial prostheses, characterized by their ankle moment versus ankle angle curves. Furthermore, improved parameters describing the prosthetic ankle stiffness curve are determined by incorporating them to the optimization variables.Der menschliche Bewegungsapparat besteht hauptsächlich aus einen Skelett sowie aus Muskeln, die Kräfte auf das Skelett ausüben und damit Bewegungen hervorrufen. Die Muskeln werden durch das zentrale Nervensystem angeregt, so dass bestimmte aktivittsabhängige Kriterien optimiert werden. Während zum Beispiel bei Sprungbewegungen die maximale erreichte Höhe das wichtigste Kriterium darstellt, können bei anderen Aktivitäten die Minimierung von Muskelermüdung oder Schmerz von primärer Bedeutung sein. Experimentelle Hinweise zeigen, dass der Energieaufwand während der Gehbewegung von größer Bedeutung ist. Aus diesem Grund wird bei Untersuchungen der menschlichen Gehbewegung der Energieaufwand häufig berücksichtigt. Funktionsstörungen des neurologischen oder Muskel-Skelett-Systems verursachen Abweichungen der Kinematik, Kinetik und Muskelerregungen von normalen Mustern und führen zu einem erhöhten Energieaufwand. Insbesondere die Abweichungen, die während des Gehens mit Beinprothesen entstehen, werden in dieser Dissertation betrachtet. Der hohe Energieaufwand zeigt die große Belastung, die durch eine Amputation verursacht wird. Das Verständnis dieser Abweichungen und Störungen kann einen wesentlichen Beitrag zur Entwicklung von Prothesen und Orthesen, zur Planung von chirurgischen Interventionen und zur Verbesserung von Therapien leisten. In der Biomechanik, einer Wissenschaft, die durch die Untersuchung von biologischen Systemen mit den Methoden der Mechanik entstanden ist, werden Modelle des menschlichen Bewegungsapparates entwickelt und zunehmend auf die Untersuchung von Gehbewegung mit Hilfe von rechnergestützten Simulationen angewandt. Dabei wird das Skelett-System häufig durch ein Mehrkörpersystem bestehend aus starren Körper modelliert. Die biologischen Aktoren werden durch Modelle nach Hill repräsentiert, die aus einem kontraktilen Element bestehen, welches die aktive Krafterzeugung der Muskelfasern wiedergibt, und Elementen, welche die passive Eigenschaften des Gewebes modellieren. Außerdem kann in Verbindung mit Muskelmodellen nach Hill der Energieaufwand bei der Krafterzeugung durch neuerdings entwickelte Modelle abgeschätzt werden. Diese Modelle werden beispielsweise für die Berechnung von Momenten an den Gelenken aus der experimentell erfassten Kinematik, für die Bestimmung von Muskelkräften aus Gelenkmomenten, und für die Bestimmung von normalen und pathologischen Gehbewegungsmustern verwendet. Trotz der zunehmenden Anwendung von Computersimulationen für die Untersuchung der Gehbewegung führt die hohe Ordnung des Muskel-Skelett-Modells in der Regel zu einem enormen Rechenaufwand, insbesondere wenn das Modell für Optimierungsrechnungen herangezogen wird. Dieser Aufwand schränkt eine häufigere Benutzung der Computersimulation für die Untersuchung von pathologischen Gehbewegungen ein, oder erfordert eine so starke Vereinfachung der Modelle, dass unrealistische Ergebnisse entstehen. Vor diesem Hintergrund sind die in dieser Dissertation enthaltenen Arbeiten zu sehen. So werden einerseits alternative Methoden zur Berechnung der Kinematik, der Kinetik, der Muskelansteuerung sowie des Energieaufwands der menschlichen Bewegung entwickelt, die im Vergleich zu den herkömmlichen Methoden eine bessere Abbildung der natürlichen Gehbewegungen des Menschen bei geringerem Rechenaufwand bieten. Andererseits leistet diese Dissertation einen Beitrag zum Verständnis der pathologischen Gehbewegung und zur Entwicklung von Beinorthesen und -prothesen