Microstructural analysis of skeletal muscle force generation during aging.

Human aging results in a progressive decline in the active force generation capability of skeletal muscle. While many factors related to the changes of morphological and structural properties in muscle fibers and the extracellular matrix (ECM) have been considered as possible reasons for causing age-related force reduction, it is still not fully understood why the decrease in force generation under eccentric contraction (lengthening) is much less than that under concentric contraction (shortening). Biomechanically, it was observed that connective tissues (endomysium) stiffen as ages, and the volume ratio of connective tissues exhibits an age-related increase. However, limited skeletal muscle models take into account the microstructural characteristics as well as the volume fraction of tissue material. This study aims to provide a numerical investigation in which the muscle fibers and the ECM are explicitly represented to allow quantitative assessment of the age-related force reduction mechanism. To this end, a fiber-level honeycomb-like microstructure is constructed and modeled by a pixel-based Reproducing Kernel Particle Method (RKPM), which allows modeling of smooth transition in biomaterial properties across material interfaces. The numerical investigation reveals that the increased stiffness of the passive materials of muscle tissue reduces the force generation capability under concentric contraction while maintains the force generation capability under eccentric contraction. The proposed RKPM microscopic model provides effective means for the cellular-scale numerical investigation of skeletal muscle physiology. NOVELTY STATEMENT: A cellular-scale honeycomb-like microstructural muscle model constructed from a histological cross-sectional image of muscle is employed to study the causal relations between age-associated microstructural changes and age-related force loss using Reproducing Kernel Particle Method (RKPM). The employed RKPM offers an effective means for modeling biological materials based on pixel points in the medical images and allow modeling of smooth transition in the material properties across interfaces. The proposed microstructure-informed muscle model enables quantitative evaluation on how cellular-scale compositions contribute to muscle functionality and explain differences in age-related force changes during concentric, isometric and eccentric contractions

Implicit Discourse Relation Classification via Multi-Task Neural Networks

Without discourse connectives, classifying implicit discourse relations is a challenging task and a bottleneck for building a practical discourse parser. Previous research usually makes use of one kind of discourse framework such as PDTB or RST to improve the classification performance on discourse relations. Actually, under different discourse annotation frameworks, there exist multiple corpora which have internal connections. To exploit the combination of different discourse corpora, we design related discourse classification tasks specific to a corpus, and propose a novel Convolutional Neural Network embedded multi-task learning system to synthesize these tasks by learning both unique and shared representations for each task. The experimental results on the PDTB implicit discourse relation classification task demonstrate that our model achieves significant gains over baseline systems.Comment: This is the pre-print version of a paper accepted by AAAI-1

Physical modeling and validation of porpoises' directional emission via hybrid metamaterials

© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Dong, E., Zhang, Y., Song, Z., Zhang, T., Cai, C., & Fang, N. X. Physical modeling and validation of porpoises' directional emission via hybrid metamaterials. National Science Review, 6(5), (2019): 921-928, doi:10.1093/nsr/nwz085.In wave physics and engineering, directional emission sets a fundamental limitation on conventional simple sources as their sizes should be sufficiently larger than their wavelength. Artificial metamaterial and animal biosonar both show potential in overcoming this limitation. Existing metamaterials arranged in periodic microstructures face great challenges in realizing complex and multiphase biosonar structures. Here, we proposed a physical directional emission model to bridge the gap between porpoises’ biosonar and artificial metamaterial. Inspired by the anatomical and physical properties of the porpoise's biosonar transmission system, we fabricated a hybrid metamaterial system composed of multiple composite structures. We validated that the hybrid metamaterial significantly increased directivity and main lobe energy over a broad bandwidth both numerically and experimentally. The device displayed efficiency in detecting underwater target and suppressing false target jamming. The metamaterial-based physical model may be helpful to achieve the physical mechanisms of porpoise biosonar detection and has diverse applications in underwater acoustic sensing, ultrasound scanning, and medical ultrasonography.E.D., Y.Z., Z.S., T.Z. and C.C. acknowledge the financial support in part by the National Key Research and Development Program of China (2018YFC1407504), the National Natural Science Foundation of China (41676023, 41276040 and 41422604). N.X.F. acknowledges the support from the MIT Energy Initiative grant. Z.S. thanks the China Scholarship Council for the financial support of his oversea study in Woods Hole Oceanographic Institution

Hierarchical nanomechanics of collagen microfibrils

Collagen constitutes one third of the human proteome, providing mechanical stability, elasticity and strength to connective tissues. Collagen is also the dominating material in the extracellular matrix (ECM) and is thus crucial for cell differentiation, growth and pathology. However, fundamental questions remain with respect to the origin of the unique mechanical properties of collagenous tissues, and in particular its stiffness, extensibility and nonlinear mechanical response. By using x-ray diffraction data of a collagen fibril reported by Orgel et al. (Proceedings of the National Academy of Sciences USA, 2006) in combination with protein structure identification methods, here we present an experimentally validated model of the nanomechanics of a collagen microfibril that incorporates the full biochemical details of the amino acid sequence of the constituting molecules. We report the analysis of its mechanical properties under different levels of stress and solvent conditions, using a full-atomistic force field including explicit water solvent. Mechanical testing of hydrated collagen microfibrils yields a Young’s modulus of ≈300 MPa at small and ≈1.2 GPa at larger deformation in excess of 10% strain, in excellent agreement with experimental data. Dehydrated, dry collagen microfibrils show a significantly increased Young’s modulus of ≈1.8 to 2.25 GPa (or ≈6.75 times the modulus in the wet state) owing to a much tighter molecular packing, in good agreement with experimental measurements (where an increase of the modulus by ≈9 times was found). Our model demonstrates that the unique mechanical properties of collagen microfibrils can be explained based on their hierarchical structure, where deformation is mediated through mechanisms that operate at different hierarchical levels. Key mechanisms involve straightening of initially disordered and helically twisted molecules at small strains, followed by axial stretching of molecules, and eventual molecular uncoiling at extreme deformation. These mechanisms explain the striking difference of the modulus of collagen fibrils compared with single molecules, which is found in the range of 4.8±2 GPa or ≈10-20 times greater. These findings corroborate the notion that collagen tissue properties are highly scale dependent and nonlinear elastic, an issue that must be considered in the development of models that describe the interaction of cells with collagen in the extracellular matrix. A key impact the atomistic model of collagen microfibril mechanics reported here is that it enables the bottom-up elucidation of structure-property relationships in the broader class of collagen materials such as tendon or bone, including studies in the context of genetic disease where the incorporation of biochemical, genetic details in material models of connective tissue is essential

Analytical and numerical analyses of the micromechanics of soft fibrous connective tissues

State of the art research and treatment of biological tissues require accurate and efficient methods for describing their mechanical properties. Indeed, micromechanics motivated approaches provide a systematic method for elevating relevant data from the microscopic level to the macroscopic one. In this work the mechanical responses of hyperelastic tissues with one and two families of collagen fibers are analyzed by application of a new variational estimate accounting for their histology and the behaviors of their constituents. The resulting, close form expressions, are used to determine the overall response of the wall of a healthy human coronary artery. To demonstrate the accuracy of the proposed method these predictions are compared with corresponding 3-D finite element simulations of a periodic unit cell of the tissue with two families of fibers. Throughout, the analytical predictions for the highly nonlinear and anisotropic tissue are in agreement with the numerical simulations

A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally Compliant Joints

Most traditional robotic mechanisms feature inelastic joints that are unable to robustly handle large deformations and off-axis moments. As a result, the applied loads are transferred rigidly throughout the entire structure. The disadvantage of this approach is that the exerted leverage is magnified at each subsequent joint possibly damaging the mechanism. In this paper, we present two lightweight, elastic, bio-inspired tensegrity robotics arms which mitigate this danger while improving their mechanism's functionality. Our solutions feature modular tensegrity structures that function similarly to the human elbow and the human shoulder when connected. Like their biological counterparts, the proposed robotic joints are flexible and comply with unanticipated forces. Both proposed structures have multiple passive degrees of freedom and four active degrees of freedom (two from the shoulder and two from the elbow). The structural advantages demonstrated by the joints in these manipulators illustrate a solution to the fundamental issue of elegantly handling off-axis compliance.Comment: IROS 201