In the central nervous system (CNS), neuronal functionality is highly dependent on mitochondrial integrity and activity. In the context of a damaged or diseased brain, mitochondrial dysfunction leads ...to reductions in ATP levels, thus impairing ATP-dependent neural firing and neurotransmitter dynamics. Restoring mitochondrial ability to generate ATP may be a basic premise to restore neuronal functionality. Recently, emerging data in rodent and human studies suggest that mitochondria and its components are surprisingly released into extracellular space and potentially transferred between cells. Transferred mitochondria may support oxidative phosphorylation in recipient cells. In this mini-review, we (a) survey recent findings in cell to cell mitochondrial transfer and the presence of cell-free extracellular mitochondria and its components, (b) review experimental details of how to detect extracellular mitochondria and mitochondrial transfer in the CNS, (c) discuss strategies and tissue sources for mitochondria isolation, and (d) explore exogenous mitochondrial transplantation as a novel approach for CNS therapies.
We propose a method for checking and enforcing multicontact stability based on the zero-tilting moment point (ZMP). The key to our development is the generalization of ZMP support areas to take into ...account: 1) frictional constraints and 2) multiple noncoplanar contacts. We introduce and investigate two kinds of ZMP support areas. First, we characterize and provide a fast geometric construction for the support area generated by valid contact forces, with no other constraint on the robot motion. We call this set the full support area. Next, we consider the control of humanoid robots by using the linear pendulum mode (LPM). We observe that the constraints stemming from the LPM induce a shrinking of the support area, even for walking on horizontal floors. We propose an algorithm to compute the new area, which we call the pendular support area. We show that, in the LPM, having the ZMP in the pendular support area is a necessary and sufficient condition for contact stability. Based on these developments, we implement a whole-body controller and generate feasible multicontact motions where an HRP-4 humanoid locomotes in challenging multicontact scenarios.
Although many studies have investigated markerless motion capture, the technology has not been applied to real sports or concerts. In this paper, we propose a markerless motion capture method with ...spatiotemporal accuracy and smoothness from multiple cameras in wide-space and multi-person environments. The proposed method predicts each person's 3D pose and determines the bounding box of multi-camera images small enough. This prediction and spatiotemporal filtering based on human skeletal model enables 3D reconstruction of the person and demonstrates high-accuracy. The accurate 3D reconstruction is then used to predict the bounding box of each camera image in the next frame. This is feedback from the 3D motion to 2D pose, and provides a synergetic effect on the overall performance of video motion capture. We evaluated the proposed method using various datasets and a real sports field. The experimental results demonstrate that the mean per joint position error (MPJPE) is 31.5 mm and the percentage of correct parts (PCP) is 99.5% for five people dynamically moving while satisfying the range of motion (RoM). Video demonstration, datasets, and additional materials are posted on our project page1.
•A method to realize multi-person motion capture was proposed.•The proposed method works even in a wide field using cameras with different fields of view placed at a single viewpoint.•The proposed method achieved 31.5 mm in MPJPE and 99.5% in PCP in an environment where 5 people move dynamically while satisfying RoM.•With the proposed method, all players' detailed motions in a futsal game were acquired only from a few cameras.
This paper describes a novel approach to linguistic mutual inference, which enables robots not only to linguistically interpret the motion patterns in the form of sentences but also to generate the ...motions from the sentences. The inference can be established based on two modules, the motion language model and the natural language model. The motion language model stochastically represents an association structure between symbols of motion patterns and the words in sentences assigned to the motion. This is a statistical model with a three layered structure of motion symbols, latent states and words. The natural language model statistically represents a structure of sentences based on word bigrams. The motion language model and the natural language model correspond to semantics and syntax respectively. An approach to the integration of motion language model with the natural language model allows the linguistic mutual inference for the robots. The two kinds of inference can be made by solving search problems, search for a sequence of words corresponding to a motion and search for a symbol of motion pattern corresponding to a sentence. The proposed approach to interpretation of motion patterns as sentences and generation of motion patterns from the sentences through the integration of motion language model with the natural language model is validated by an experiment on the human behavioral data.
Astrocytes comprise the major non-neuronal cell population in the mammalian neurovascular unit. Traditionally, astrocytes are known to play broad roles in central nervous system (CNS) homeostasis, ...including the management of extracellular ion balance and pH, regulation of neurotransmission, and control of cerebral blood flow and metabolism. After CNS injury, cell⁻cell signaling between neuronal, glial, and vascular cells contribute to repair and recovery in the neurovascular unit. In this mini-review, we propose the idea that astrocytes play a central role in organizing these signals. During CNS recovery, reactive astrocytes communicate with almost all CNS cells and peripheral progenitors, resulting in the promotion of neurogenesis and angiogenesis, regulation of inflammatory response, and modulation of stem/progenitor response. Reciprocally, changes in neurons and vascular components of the remodeling brain should also influence astrocyte signaling. Therefore, understanding the complex and interdependent signaling pathways of reactive astrocytes after CNS injury may reveal fundamental mechanisms and targets for re-integrating the neurovascular unit and augmenting brain recovery.
Grasping and manipulation with anthropomorphic robotic and prosthetic hands presents a scientific challenge regarding mechanical design, sensor system, and control. Apart from the mechanical design ...of such hands, embedding sensors needed for closed-loop control of grasping tasks remains a hard problem due to limited space and required high level of integration of different components. In this paper we present a scalable design model of artificial fingers, which combines mechanical design and embedded electronics with a sophisticated multi-modal sensor system consisting of sensors for sensing normal and shear force, distance, acceleration, temperature, and joint angles. The design is fully parametric, allowing automated scaling of the fingers to arbitrary dimensions in the human hand spectrum. To this end, the electronic parts are composed of interchangeable modules that facilitate the mechanical scaling of the fingers and are fully enclosed by the mechanical parts of the finger. The resulting design model allows deriving freely scalable and multimodally sensorised fingers for robotic and prosthetic hands. Four physical demonstrators are assembled and tested to evaluate the approach.
This article discusses a compliance optimization approach that satisfies positive definiteness. Physical human-robot interactions are an important topic in robotics, for which force or compliance ...control is a key technology. Operational space control (OSC) is one of the most common approaches for robot force control with redundant degrees of freedom. By linearizing OSC, we can derive joint stiffness and viscosity matrices equivalent to the OSC. For an appropriate control, it is important that these matrices are positive definite. However, the stiffness matrix equivalent to the OSC is not always positive definite. In this case, a high kinetic energy is required, which is a problem in terms of the control performance. Therefore, the control performance can be improved by explicitly considering the positive definiteness of the stiffness or compliance. In this article, the authors derive a dynamically consistent compliance formulation and propose a compliance optimization that satisfies positive definiteness. The space of the symmetric positive definite matrix is a Riemannian manifold. We show that minimizing the Riemaniann geodesic distance results in a better performance compared with using OSC. The proposed method is validated via forward dynamics simulations and experiments using a hydrostatically driven humanoid Hydra.
This paper proposes a novel framework for generating action descriptions from human whole body motions and objects to be manipulated. This generation is based on three modules: the first module ...categorizes human motions and objects; the second module associates the motion and object categories with words; and the third module extracts a sentence structure as word sequences. Human motions and objects to be manipulated are classified into categories in the first module, then words highly relevant to the motion and object categories are generated from the second module, and finally the words are converted into sentences in the form of word sequences by the third module. The motions and objects along with the relations among the motions, objects, and words are parametrized stochastically by the first and second modules. The sentence structures are parametrized from a dataset of word sequences in a dynamical system by the third module. The link of the stochastic representation of the motions, objects, and words with the dynamical representation of the sentences allows for synthesizing sentences descriptive to human actions. We tested our proposed method on synthesizing action descriptions for a human action dataset captured by an RGB-D sensor, and demonstrated its validity.
After stroke, peripheral immune cells are activated and these systemic responses may amplify brain damage, but how the injured brain sends out signals to trigger systemic inflammation remains ...unclear. Here we show that a brain-to-cervical lymph node (CLN) pathway is involved. In rats subjected to focal cerebral ischemia, lymphatic endothelial cells proliferate and macrophages are rapidly activated in CLNs within 24 h, in part via VEGF-C/VEGFR3 signalling. Microarray analyses of isolated lymphatic endothelium from CLNs of ischemic mice confirm the activation of transmembrane tyrosine kinase pathways. Blockade of VEGFR3 reduces lymphatic endothelial activation, decreases pro-inflammatory macrophages, and reduces brain infarction. In vitro, VEGF-C/VEGFR3 signalling in lymphatic endothelial cells enhances inflammatory responses in co-cultured macrophages. Lastly, surgical removal of CLNs in mice significantly reduces infarction after focal cerebral ischemia. These findings suggest that modulating the brain-to-CLN pathway may offer therapeutic opportunities to ameliorate systemic inflammation and brain injury after stroke.
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