Influence of muscle soft tissue and lower limbs on the vibration behavior of the entire spine inside the seated human body: A finite element study.

The objective of the study is to investigate the vibration behavior of the entire spine inside the human body and the influence of muscle soft tissue and lower limbs on spinal response under vertical whole-body vibration. This study conducted modal and random response analyses to simulate the modal displacements and stress of all intervertebral discs in the vertical principal mode in the skeleton, upper, and whole body. Additionally, the acceleration response of intervertebral discs under vertical random excitation was investigated. The results revealed that removing muscle soft tissue and lower limbs significantly changed the resonant frequency, modal displacement, and stress. Particularly, there was a rapid increase in vertical displacement of the lumbar spine in the skeleton model. The reason for that was due to the lack of soft tissue to provide stability, leading to significant lumbar spine bending. Under random excitation, the fore-aft acceleration of intervertebral discs in the skeleton model was considerably larger than that in the whole body, especially in the lumbar spine where it can reach up to four times higher. Conversely, the vertical response of the intervertebral discs inside the human body model was 1.4-2.4 times larger than that of the skeleton model. Muscle soft tissue contributes to the strength of the spine, reducing fore-aft response. The muscle soft tissue in the gluteal region, connected below the spine, can lower the vertical natural frequency and attenuate spinal impact. Although the lower limbs enhance spinal stability, stimulation from the feet can superimpose vibrational responses in the spine.

Synaptic architecture of leg and wing premotor control networks in Drosophila.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles1. MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours2-6. Here we use connectomics7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

Connectomic reconstruction of a female Drosophila ventral nerve cord.

A deep understanding of how the brain controls behaviour requires mapping neural circuits down to the muscles that they control. Here, we apply automated tools to segment neurons and identify synapses in an electron microscopy dataset of an adult female Drosophila melanogaster ventral nerve cord (VNC)1, which functions like the vertebrate spinal cord to sense and control the body. We find that the fly VNC contains roughly 45 million synapses and 14,600 neuronal cell bodies. To interpret the output of the connectome, we mapped the muscle targets of leg and wing motor neurons using genetic driver lines2 and X-ray holographic nanotomography3. With this motor neuron atlas, we identified neural circuits that coordinate leg and wing movements during take-off. We provide the reconstruction of VNC circuits, the motor neuron atlas and tools for programmatic and interactive access as resources to support experimental and theoretical studies of how the nervous system controls behaviour.

Full Hill-type muscle model of the I1/I3 retractor muscle complex in Aplysia californica.

The coordination of complex behavior requires knowledge of both neural dynamics and the mechanics of the periphery. The feeding system of Aplysia californica is an excellent model for investigating questions in soft body systems' neuromechanics because of its experimental tractability. Prior work has attempted to elucidate the mechanical properties of the periphery by using a Hill-type muscle model to characterize the force generation capabilities of the key protractor muscle responsible for moving Aplysia's grasper anteriorly, the I2 muscle. However, the I1/I3 muscle, which is the main driver of retractions of Aplysia's grasper, has not been characterized. Because of the importance of the musculature's properties in generating functional behavior, understanding the properties of muscles like the I1/I3 complex may help to create more realistic simulations of the feeding behavior of Aplysia, which can aid in greater understanding of the neuromechanics of soft-bodied systems. To bridge this gap, in this work, the I1/I3 muscle complex was characterized using force-frequency, length-tension, and force-velocity experiments and showed that a Hill-type model can accurately predict its force-generation properties. Furthermore, the muscle's peak isometric force and stiffness were found to exceed those of the I2 muscle, and these results were analyzed in the context of prior studies on the I1/I3 complex's kinematics in vivo.

A fluorescently-tagged tick kinin neuropeptide triggers peristalsis and labels tick midgut muscles.

Ticks are blood-feeding arthropods that require heme for their successful reproduction. During feeding they also acquire pathogens that are subsequently transmitted to humans, wildlife and/or livestock. Understanding the regulation of tick midgut is important for blood meal digestion, heme and nutrient absorption processes and for aspects of pathogen biology in the host. We previously demonstrated the activity of tick kinins on the cognate G protein-coupled receptor. Herein we uncovered the physiological role of the kinin receptor in the tick midgut. A fluorescently-labeled kinin peptide with the endogenous kinin 8 sequence (TMR-RK8), identical in the ticks Rhipicephalus microplus and R. sanguineus, activated and labeled the recombinant R. microplus receptor expressed in CHO-K1 cells. When applied to the live midgut the TMR-RK8 labeled the kinin receptor in muscles while the labeled peptide with the scrambled-sequence of kinin 8 (TMR-Scrambled) did not. The unlabeled kinin 8 peptide competed TMR-RK8, decreasing confocal microscopy signal intensity, indicating TMR-RK8 specificity to muscles. TMR-RK8 was active, inducing significant midgut peristalsis that was video-recorded and evaluated with video tracking software. The TMR-Scrambled peptide used as a negative control did not elicit peristalsis. The myotropic function of kinins in eliciting tick midgut peristalsis was established.

Gluconeogenesis in frogs during cooling and dehydration exposure: new insights into tissue plasticity of the gluconeogenic pathway dependent on abiotic factors.

Anurans undergo significant physiological changes when exposed to environmental stressors such as low temperatures and humidity. Energy metabolism and substrate management play a crucial role in their survival success. Therefore, understanding the role of the gluconeogenic pathway and demonstrating its existence in amphibians is essential. In this study, we exposed the subtropical frog Boana pulchella to cooling (-2.5°C for 24 h) and dehydration conditions (40% of body water loss), followed by recovery (24 h), and assessed gluconeogenesis activity from alanine, lactate, glycerol and glutamine in the liver, muscle and kidney. We report for the first time that gluconeogenesis activity by 14C-alanine and 14C-lactate conversion to glucose occurs in the muscle tissue of frogs, and this tissue activity is influenced by environmental conditions. Against the control group, liver gluconeogenesis from 14C-lactate and 14C-glycerol was lower during cooling and recovery (P<0.01), and gluconeogenesis from 14C-glutamine in the kidneys was also lower during cooling (P<0.05). In dehydration exposure, gluconeogenesis from 14C-lactate in the liver was lower during recovery, and that from 14C-alanine in the muscle was lower during dehydration (P<0.05). Moreover, we observed that gluconeogenesis activity and substrate preference respond differently to cold and dehydration. These findings highlight tissue-specific plasticity dependent on the nature of the encountered stressor, offering valuable insights for future studies exploring this plasticity, elucidating the importance of the gluconeogenic pathway and characterizing it in anuran physiology.

The sex of organ geometry.

Organs have a distinctive yet often overlooked spatial arrangement in the body1-5. We propose that there is a logic to the shape of an organ and its proximity to its neighbours. Here, by using volumetric scans of many Drosophila melanogaster flies, we develop methods to quantify three-dimensional features of organ shape, position and interindividual variability. We find that both the shapes of organs and their relative arrangement are consistent yet differ between the sexes, and identify unexpected interorgan adjacencies and left-right organ asymmetries. Focusing on the intestine, which traverses the entire body, we investigate how sex differences in three-dimensional organ geometry arise. The configuration of the adult intestine is only partially determined by physical constraints imposed by adjacent organs; its sex-specific shape is actively maintained by mechanochemical crosstalk between gut muscles and vascular-like trachea. Indeed, sex-biased expression of a muscle-derived fibroblast growth factor-like ligand renders trachea sexually dimorphic. In turn, tracheal branches hold gut loops together into a male or female shape, with physiological consequences. Interorgan geometry represents a previously unrecognized level of biological complexity which might enable or confine communication across organs and could help explain sex or species differences in organ function.

Note on hydrostatic skeletons: muscles operating within a pressurized environment.

Muscles and muscle fibers are volume-constant constructs that deform when contracted and develop internal pressures. However, muscles embedded in hydrostatic skeletons are also exposed to external pressures generated by their activity. For two examples, the pressure generation in spiders and in annelids, we used simplified biomechanical models to demonstrate that high intracellular pressures diminishing the resulting tensile stress of the muscle fibers are avoided in the hydrostatic skeleton. The findings are relevant for a better understanding of the design and functionality of biological hydrostatic skeletons.

Scaling of buccal mass growth and muscle activation determine the duration of feeding behaviours in the marine mollusc Aplysia californica.

The mechanical forces experienced during movement and the time constants of muscle activation are important determinants of the durations of behaviours, which may both be affected by size-dependent scaling. The mechanics of slow movements in small animals are dominated by elastic forces and are thus quasistatic (i.e. always near mechanical equilibrium). Muscular forces producing movement and elastic forces resisting movement should scale identically (proportional to mass2/3), leaving the scaling of the time constant of muscle activation to play a critical role in determining behavioural duration. We tested this hypothesis by measuring the duration of feeding behaviours in the marine mollusc Aplysia californica whose body sizes spanned three orders of magnitude. The duration of muscle activation was determined by measuring the time it took for muscles to produce maximum force as A. californica attempted to feed on tethered inedible seaweed, which provided an in vivo approximation of an isometric contraction. The timing of muscle activation scaled with mass0.3. The total duration of biting behaviours scaled identically, with mass0.3, indicating a lack of additional mechanical effects. The duration of swallowing behaviour, however, exhibited a shallower scaling of mass0.17. We suggest that this was due to the allometric growth of the anterior retractor muscle during development, as measured by micro-computed tomography (micro-CT) scans of buccal masses. Consequently, larger A. californica did not need to activate their muscles as fully to produce equivalent forces. These results indicate that muscle activation may be an important determinant of the scaling of behavioural durations in quasistatic systems.

Estimation of lower back muscle force in a lifting task using wearable IMUs.

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

Machine learning reveals the control mechanics of an insect wing hinge.

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs1, but are novel structures that are attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings2. The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the three-dimensional motion of the wings with high-speed cameras. Using machine learning, we created a convolutional neural network3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation incorporating our hinge model generates flight manoeuvres that are remarkably similar to those of free-flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Muscle and joint mechanics during maximum force biting following total temporomandibular joint replacement surgery.

Total temporomandibular joint replacement (TMJR) surgery is the established treatment for severe temporomandibular joint disorders. While TMJR surgery is known to increase mouth-opening capacity, reduce pain and improve quality of life, little is known about post-surgical jaw function during activities of daily living such as biting and chewing. The aim of this study was to use subject-specific 3D bite force measurements to evaluate the magnitude and direction of joint loading in unilateral total TMJR patients and compare these data to those in healthy control subjects. An optoelectronic tracking system was used to measure jaw kinematics while biting a rubber sample for 5 unilateral total TMJR patients and 8 controls. Finite element simulations driven by the measured kinematics were employed to calculate the resultant bite force generated when compressing the rubber between teeth during biting tasks. Subject-specific musculoskeletal models were subsequently used to calculate muscle and TMJ loading. Unilateral total TMJR patients generated a bite force of 249.6 ± 24.4 N and 164.2 ± 62.3 N when biting on the contralateral and ipsilateral molars, respectively. In contrast, controls generated a bite force of 317.1 ± 206.6 N. Unilateral total TMJR patients biting on the contralateral molars had a significantly higher lateral TMJ force direction (median difference: 63.6°, p = 0.028) and a significantly lower ratio of working TMJ force to bite force (median difference: 0.17, p = 0.049) than controls. Results of this study may guide TMJ prosthesis design and evaluation of dental implants.

Steering Muscle-Based Bio-Syncretic Robot Through Bionic Optimized Biped Mechanical Design.

Bio-syncretic robots consisting of artificial structures and living muscle cells have attracted much attention owing to their potential advantages, such as high drive efficiency, miniaturization, and compatibility. Motion controllability, as an important factor related to the main performance of bio-syncretic robots, has been explored in numerous studies. However, most of the existing bio-syncretic robots still face challenges related to the further development of steerable kinematic dexterity. In this study, a bionic optimized biped fully soft bio-syncretic robot actuated by two muscle tissues and steered with a direction-controllable electric field generated by external circularly distributed multiple electrodes has been developed. The developed bio-syncretic robot could realize wirelessly steerable motion and effective transportation of microparticle cargo on artificial polystyrene and biological pork tripe surfaces. This study may provide an effective strategy for the development of bio-syncretic robots and other related studies, such as nonliving soft robot design and muscle tissue engineering.

Prediction of trunk muscle activation and spinal forces in adolescent idiopathic scoliosis during simulated trunk motion: A musculoskeletal modelling study.

Due to lack of reference validation data, the common strategy in characterizing adolescent idiopathic scoliosis (AIS) by musculoskeletal modelling approach consists in adapting structure and parameters of validated body models of adult individuals with physiological alignments. Until now, only static postures have been replicated and investigated in AIS subjects. When aiming to simulate trunk motion, two critical factors need consideration: how distributing movement along the vertebral motion levels (lumbar spine rhythm), and if neglecting or accounting for the contribution of the stiffness of the motion segments (disc stiffness). The present study investigates the effect of three different lumbar spine rhythms and absence/presence of disc stiffness on trunk muscle imbalance in the lumbar region and on intervertebral lateral shear at different levels of the thoracolumbar/lumbar scoliotic curve, during simulated trunk motions in the three anatomical planes (flexion/extension, lateral bending, and axial rotation). A spine model with articulated ribcage previously developed in AnyBody software and adapted to replicate the spinal alignment in AIS subjects is employed. An existing dataset of 100 subjects with mild and moderate scoliosis is exploited. The results pointed out the significant impact of lumbar spine rhythm configuration and disc stiffness on changes in the evaluated outputs, as well as a relationship with scoliosis severity. Unfortunately, no optimal settings can be identified due to lack of reference validation data. According to that, extreme caution is recommended when aiming to adapt models of adult individuals with physiological alignments to adolescent subjects with scoliotic deformity.

Effective On-Line Performance Modulation and Efficient Continuous Preparation of Ultra-Long Twisted and Coiled Polymer Artificial Muscles for Engineering Applications.

Artificial muscle is a kind of thread-like actuator that can produce contractile strain, generate force, and output mechanical work under external stimulations to imitate the functions and achieve the performances of biological muscles. It can be used to actuate various bionic soft robots and has broad application prospects. The electrically controlled twisted and coiled polymer (TCP) artificial muscles, with the advantages of high power density, large stroke and low driving voltage, while also being electrolyte free, are the most practical. However, the relationship between the muscle performances and its preparation parameters is not very clear yet, and the complete procedure of designing and preparing TCP muscles according to actual needs has not been established. Besides, current preparation approaches are very time-consuming and cannot make ultra-long TCP muscles. These problems greatly limit wide applications of TCP artificial muscles. In this study, we studied and built the relationship between the actuating performances of TCP muscles and their preparation parameters, so that suitable TCP muscles can be easily designed and prepared according to actual requirements. Moreover, an efficient preparation method integrating one-step annealing technique has been developed to realize on-line performance modulation and continuous fabrication of ultra-long TCP muscles. By graphically assembling long muscles on heat-resist films, we designed and produced a series of fancy soft robots (butterfly, flower, starfish), which can perform various bionic movements and complete specific tasks. This work has achieved efficient on-demand preparation and large-scale assembly of ultra-long TCP muscles, laying solid foundations for their engineering applications in soft robot field.

A Physics-Informed Low-Shot Adversarial Learning for sEMG-Based Estimation of Muscle Force and Joint Kinematics.

Muscle force and joint kinematics estimation from surface electromyography (sEMG) are essential for real-time biomechanical analysis of the dynamic interplay among neural muscle stimulation, muscle dynamics, and kinetics. Recent advances in deep neural networks (DNNs) have shown the potential to improve biomechanical analysis in a fully automated and reproducible manner. However, the small sample nature and physical interpretability of biomechanical analysis limit the applications of DNNs. This paper presents a novel physics-informed low-shot adversarial learning method for sEMG-based estimation of muscle force and joint kinematics. This method seamlessly integrates Lagrange's equation of motion and inverse dynamic muscle model into the generative adversarial network (GAN) framework for structured feature decoding and extrapolated estimation from the small sample data. Specifically, Lagrange's equation of motion is introduced into the generative model to restrain the structured decoding of the high-level features following the laws of physics. A physics-informed policy gradient is designed to improve the adversarial learning efficiency by rewarding the consistent physical representation of the extrapolated estimations and the physical references. Experimental validations are conducted on two scenarios (i.e. the walking trials and wrist motion trials). Results indicate that the estimations of the muscle forces and joint kinematics are unbiased compared to the physics-based inverse dynamics, which outperforms the selected benchmark methods, including physics-informed convolution neural network (PI-CNN), vallina generative adversarial network (GAN), and multi-layer extreme learning machine (ML-ELM).