TFEB triggers a matrix degradation and invasion program in triple-negative breast cancer cells upon mTORC1 repression.

The phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway is frequently hyperactivated in triple-negative breast cancers (TNBCs) associated with poor prognosis and is a therapeutic target in breast cancer management. Here, we describe the effects of repression of mTOR-containing complex 1 (mTORC1) through knockdown of several key mTORC1 components or with mTOR inhibitors used in cancer therapy. mTORC1 repression results in an ∼10-fold increase in extracellular matrix proteolytic degradation.

Teaching Motor Skills Without a Motor: A Semi-Passive Robot to Facilitate Learning.

Semi-passive rehabilitation robots resist and steer a patient's motion using only controllable passive force elements (e.g., controllable brakes).

A mechanosensitive caveolae-invadosome interplay drives matrix remodelling for cancer cell invasion.

Invadosomes and caveolae are mechanosensitive structures that are implicated in metastasis. Here, we describe a unique juxtaposition of caveola clusters and matrix degradative invadosomes at contact sites between the plasma membrane of cancer cells and constricting fibrils both in 2D and 3D type I collagen matrix environments. Preferential association between caveolae and straight segments of the fibrils, and between invadosomes and bent segments of the fibrils, was observed along with matrix remodelling.

Codependencies of mTORC1 signaling and endolysosomal actin structures.

The mechanistic target of rapamycin complex 1 (mTORC1) is part of the amino acid sensing machinery that becomes activated on the endolysosomal surface in response to nutrient cues. Branched actin generated by WASH and Arp2/3 complexes defines endolysosomal microdomains. Here, we find mTORC1 components in close proximity to endolysosomal actin microdomains.

Bioinspired preactivation reflex increases robustness of walking on rough terrain.

Walking on unknown and rough terrain is challenging for (bipedal) robots, while humans naturally cope with perturbations. Therefore, human strategies serve as an excellent inspiration to improve the robustness of robotic systems. Neuromusculoskeletal (NMS) models provide the necessary interface for the validation and transfer of human control strategies.

Invadopodia Methods: Detection of Invadopodia Formation and Activity in Cancer Cells Using Reconstituted 2D and 3D Collagen-Based Matrices.

Tumor dissemination involves cancer cell migration through the extracellular matrix (ECM). ECM is mainly composed of collagen fibers that oppose cell invasion. To overcome hindrance in the matrix, cancer cells deploy a protease-dependent program in order to remodel the matrix fibers.

mTOR Repression in Response to Amino Acid Starvation Promotes ECM Degradation Through MT1-MMP Endocytosis Arrest.

Under conditions of starvation, normal and tumor epithelial cells can rewire their metabolism toward the consumption of extracellular proteins, including extracellular matrix-derived components as nutrient sources. The mechanism of pericellular matrix degradation by starved cells has been largely overlooked. Here it is shown that matrix degradation by breast and pancreatic tumor cells and patient-derived xenograft explants increases by one order of magnitude upon amino acid and growth factor deprivation.

Motor Modules are Impacted by the Number of Reaching Directions Included in the Analysis.

Muscle synergy analysis is commonly used to study how the nervous system coordinates the activation of a large number of muscles during human reaching. In synergy analysis, muscle activation data collected from various reaching directions are subjected to dimensionality reduction techniques to extract muscle synergies. Typically, muscle activation data are obtained only from a limited set of reaches with an inherent assumption that the performed reaches adequately represent all possible reaches.

An Inductance-Based Sensing System for Bellows-Driven Continuum Joints in Soft Robots.

In this work we present a novel, inductance-based system to measure and control the motion of bellows-driven continuum joints in soft robots. The sensing system relies on coils of wire wrapped around the minor diameters of each bellows on the joint. As the bellows extend, these coils of wire become more distant, decreasing their mutual inductance.

Toward Controllable Hydraulic Coupling of Joints in a Wearable Robot.

In this paper, we develop theoretical foundations for a new class of rehabilitation robot: body powered devices that route power between a user's joints. By harvesting power from a healthy joint to assist an impaired joint, novel bimanual and self-assist therapies are enabled. This approach complements existing robotic therapies aimed at promoting recovery of motor function after neurological injury.

Evaluating physiological signal salience for estimating metabolic energy cost from wearable sensors.

Body-in-the-loop optimization algorithms have the capability to automatically tune the parameters of robotic prostheses and exoskeletons to minimize the metabolic energy expenditure of the user. However, current body-in-the-loop algorithms rely on indirect calorimetry to obtain measurements of energy cost, which are noisy, sparsely sampled, time-delayed, and require wearing a respiratory mask. To improve these algorithms, the goal of this work is to predict a user's steady-state energy cost quickly and accurately using physiological signals obtained from portable, wearable sensors.

An Overview on Principles for Energy Efficient Robot Locomotion.

Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of energy efficiency in legged robotic systems, this paper provides an overview on recent advancements in development of such platforms.

Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

Background: Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human motor system reduces muscle activation levels and movement excursions, ostensibly to minimize metabolic- and movement-related costs. Consequently, the patient remains passive and is not fully engaged during therapy.

Choosing appropriate prosthetic ankle work to reduce the metabolic cost of individuals with transtibial amputation.

Powered ankle prostheses have been designed to reduce the energetic burden that individuals with transtibial amputation experience during ambulation. There is an open question regarding how much power the prosthesis should provide, and whether approximating biological ankle kinetics is optimal to reduce the metabolic cost of users. We tested 10 individuals with transtibial amputation walking on a treadmill wearing the BiOM powered ankle prosthesis programmed with 6 different power settings (0-100%), including a prosthetist-chosen setting, chosen to approximate biological ankle kinetics.

All common bipedal gaits emerge from a single passive model.

In this paper, we systematically investigate passive gaits that emerge from the natural mechanical dynamics of a bipedal system. We use an energetically conservative model of a simple spring-leg biped that exhibits well-defined swing leg dynamics. Through a targeted continuation of periodic motions of this model, we systematically identify different gaits that emerge from simple bouncing in place.

A Portable Passive Rehabilitation Robot for Upper-Extremity Functional Resistance Training.

Objective: Loss of arm function is common in individuals with neurological damage, such as stroke or cerebral palsy. Robotic devices that address muscle strength deficits in a task-specific manner can assist in the recovery of arm function; however, current devices are typically large, bulky, and expensive to be routinely used in the clinic or at home. This study sought to address this issue by developing a portable planar passive rehabilitation robot, PaRRo.

Biomechanics and energetics of walking in powered ankle exoskeletons using myoelectric control versus mechanically intrinsic control.

Background: Controllers for assistive robotic devices can be divided into two main categories: controllers using neural signals and controllers using mechanically intrinsic signals. Both approaches are prevalent in research devices, but a direct comparison between the two could provide insight into their relative advantages and disadvantages. We studied subjects walking with robotic ankle exoskeletons using two different control modes: dynamic gain proportional myoelectric control based on soleus muscle activity (neural signal), and timing-based mechanically intrinsic control based on gait events (mechanically intrinsic signal).

A Semi-passive Planar Manipulandum for Upper-Extremity Rehabilitation.

Robotic rehabilitation is a promising approach to treat individuals with neurological or orthopedic disorders. However, despite significant advancements in the field of rehabilitation robotics, this technology has found limited traction in clinical practice. A key reason for this issue is that most robots are expensive, bulky, and not scalable for in-home rehabilitation.

Spine morphology and energetics: how principles from nature apply to robotics.

Inspired by the locomotive advantages that an articulated spine enables in quadrupedal animals, we explore and quantify the energetic effect that an articulated spine has in legged robots. We compare two model instances of a conceptual planar quadruped: one with a traditional rigid main body and one with an articulated main body with an actuated spinal joint. Both models feature four distinct legs, series elastic actuation, distributed mass in all body segments, and limits on actuator torque and speed.

Smart Braid Feedback for the Closed-Loop Control of Soft Robotic Systems.

This article experimentally investigates the potential of using flexible, inductance-based contraction sensors in the closed-loop motion control of soft robots. Accurate motion control remains a highly challenging task for soft robotic systems. Precise models of the actuation dynamics and environmental interactions are often unavailable.

Using wearable physiological sensors to predict energy expenditure.

Lower-limb assistive robotic devices are often evaluated by measuring a reduction in the user's energy cost. Using indirect calorimetry to estimate energy cost is poorly suited for real-time estimation and long-term collection. The goal of this study was to use data from wearable sensors to predict energy cost with better temporal resolution and less variability than breath measurements.

Comparing neural control and mechanically intrinsic control of powered ankle exoskeletons.

There are an infinite number of ways to control an assistive robotic device; however, there is little consensus on which ways are better than others and why. We designed this study to compare the control of powered ankle exoskeletons using neural measurements to drive control versus that using mechanically intrinsic measurements. The controller driven by neural measurements was a dynamic gain proportional myoelectric controller using user's soleus muscle activity for an actuation signal.

Contraction Sensing with Smart Braid McKibben Muscles.

The inherent compliance of soft fluidic actuators makes them attractive for use in wearable devices and soft robotics. Their flexible nature permits them to be used without traditional rotational or prismatic joints. Without these joints, however, measuring the motion of the actuators is challenging.