Loop 6 and the ß-hairpin flap are structural hotspots that determine cofactor specificity in the FMN-dependent family of ene-reductases.

Flavin mononucleotide (FMN)-dependent ene-reductases constitute a large family of oxidoreductases that catalyze the enantiospecific reduction of carbon-carbon double bonds. The reducing equivalents required for substrate reduction are obtained from reduced nicotinamide by hydride transfer. Most ene-reductases significantly prefer, or exclusively accept, either NADPH or NADH. Despite their usefulness in biocatalytic applications, the structural determinants for cofactor preference remain elusive. We employed the NADPH-preferring 12-oxophytodienoic acid reductase 3 from Solanum lycopersicum (SlOPR3) as a model enzyme of the ene-reductase family and applied computational and structural methods to investigate the binding specificity of the reducing coenzymes. Initial docking results indicated that the arginine triad R283, R343, and R366 residing on and close to a critical loop at the active site (loop 6) are the main contributors to NADPH binding. In contrast, NADH binds unfavorably in the opposite direction toward the ß-hairpin flap within a largely hydrophobic region. Notably, the crystal structures of SlOPR3 in complex with either NADPH4 or NADH4 corroborated these different binding modes. Molecular dynamics simulations confirmed NADH binding near the ß-hairpin flap and provided structural explanations for the low binding affinity of NADH to SlOPR3. We postulate that cofactor specificity is determined by the arginine triad/loop 6 and the residue(s) controlling access to a hydrophobic cleft formed by the ß-hairpin flap. Thus, NADPH preference depends on a properly positioned arginine triad, whereas granting access to the hydrophobic cleft at the ß-hairpin flap favors NADH binding.

Illuminating the inner workings of a natural protein switch: Blue-light sensing in LOV-activated diguanylate cyclases.

Regulatory proteins play a crucial role in adaptation to environmental cues. Especially for lifestyle transitions, such as cell proliferation or apoptosis, switch-like characteristics are desirable. While nature frequently uses regulatory circuits to amplify or dampen signals, stand-alone protein switches are interesting for applications like biosensors, diagnostic tools, or optogenetics. However, such stand-alone systems frequently feature limited dynamic and operational ranges and suffer from slow response times. Here, we characterize a LOV-activated diguanylate cyclase (LadC) that offers precise temporal and spatial control of enzymatic activity with an exceptionally high dynamic range over four orders of magnitude. To establish this pronounced activation, the enzyme exhibits a two-stage activation process in which its activity is inhibited in the dark by caging its effector domains and stimulated upon illumination by the formation of an extended coiled-coil. These switch-like characteristics of the LadC system can be used to develop new optogenetic tools with tight regulation.

A Novel High-Throughput Nanopore-Sequencing-Based Strategy for Rapid and Automated S-Protein Typing of SARS-CoV-2 Variants.

Rapid molecular surveillance of SARS-CoV-2 S-protein variants leading to immune escape and/or increased infectivity is of utmost importance. Among global bottlenecks for variant monitoring in diagnostic settings are sequencing and bioinformatics capacities. In this study, we aimed to establish a rapid and user-friendly protocol for high-throughput S-gene sequencing and subsequent automated identification of variants. We designed two new primer pairs to amplify only the immunodominant part of the S-gene for nanopore sequencing. Furthermore, we developed an automated "S-Protein-Typer" tool that analyzes and reports S-protein mutations on the amino acid level including a variant of concern indicator. Validation of our primer panel using SARS-CoV-2-positive respiratory specimens covering a broad Ct range showed successful amplification for 29/30 samples. Restriction to the region of interest freed sequencing capacity by a factor of 12-13, compared with whole-genome sequencing. Using either the MinION or Flongle flow cell, our sequencing strategy reduced the time required to identify SARS-CoV-2 variants accordingly. The S-Protein-Typer tool identified all mutations correctly when challenged with our sequenced samples and 50 deposited sequences covering all VOCs (December 2021). Our proposed S-protein variant screening offers a simple, more rapid, and low-cost entry into NGS-based SARS-CoV-2 analysis, compared with current whole-genome approaches.

Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization.

Pneumatic artificial muscles (PAMs) are one of the key technologies in soft robotics, and they enable actuation in mobile robots, in wearable devices and exoskeletons for assistive and rehabilitative purposes. While they recently showed relevant improvements, they still present quite low payload, limited bandwidth, and lack of repeatability, controllability and robustness. Vacuum-based actuation has been recently demonstrated as a very promising solution, and many challenges are still open, like generating at the same time a large contraction ratio, and a high blocking force with enhanced axial stiffness. In this paper, a novel Ultralight Hybrid PAM (UH-PAM), based on bellow-type elastomeric skin and vacuum actuation, is presented. In particular, open-cell foam is exploited as a structural backbone, together with plastic rings, all embedded in a thin skin. The design and optimization combine numerical, analytical, and experimental data. Both static and dynamic analysis are performed. The weight of the optimized actuator is only 20 g. Nevertheless, a contraction ratio up to 50% and a maximum payload of 3 kg can be achieved. From a dynamic point of view, a rise time of 0.5 s for the contraction phase is observed. Although hysteresis is significant when using the whole contraction span, it can be reduced (down to 11.5%) by tuning both the vacuum range and the operating frequency for cyclic movements. Finally, to demonstrate the potentiality of this soft actuation approach, a 3 DoFs Stewart platform is built. The feasibility of performing smooth movements by exploiting open-loop control is shown through simple and more complex handwriting figures projected on the XY plane.

Sensing Deformation in Vacuum Driven Foam-Based Actuator via Inductive Method.

Perception in soft robotics is crucial to allow a safe interaction to effectively explore the environment. Despite the inherent capabilities of soft materials, embedding reliable sensing in soft actuators or robots could introduce constraints in the overall design (e.g., loss of deformability, undesired trajectories, etc.) or reduce their compliant characteristics. Consequently, an adequate stiffness for both sensor and actuator becomes a crucial design parameter. In particular, for sensing the deformation related to actuation motion, sensing and actuating strategies must work in full mechanical synergy. In this view, an inductive sensing solution is presented, exploiting open-cell foam and a copper (Cu) wire in an Inductive Foam Sensor (IFS). Due to entangled air cells high deformability is enabled upon vacuum pressure, and proprioceptive information is provided. The IFS is then successfully integrated into the earlier developed Ultralight Hybrid Pneumatic Artificial Muscle (UH-PAM), which encases an elastomeric bellow skin and plastic rings. Such sensorized UH-PAM (SUH-PAM) is capable of a high contraction ratio (54% upon -80 kPa), while the inductive sensing shows a high sensitivity of 0.01031/1% and a hysteresis of 5.35%, with an average error of 1.85%, respectively. In order to implement a robust feedback control system, an adaptable proportional sliding mode control is presented. As a result, the SUH-PAM motion can be controlled to the mm-scale, with an RMSE of 0.925 mm, and high robustness against disturbances is demonstrated.

3D Printing Materials for Soft Robotics.

Soft robotics is a growing field of research, focusing on constructing motor-less robots from highly compliant materials, some are similar to those found in living organisms. Soft robotics has a high potential for applications in various fields such as soft grippers, actuators, and biomedical devices. 3D printing of soft robotics presents a novel and promising approach to form objects with complex structures, directly from a digital design. Here, recent developments in the field of materials for 3D printing of soft robotics are summarized, including high-performance flexible and stretchable materials, hydrogels, self-healing materials, and shape memory polymers, as well as fabrication of all-printed robots (multi-material printing, embedded electronics, untethered and autonomous robotics). The current challenges in the fabrication of 3D printed soft robotics, including the materials available and printing abilities, are presented and the recent activities addressing these challenges are also surveyed.

Mechanical Sensing for Lower Limb Soft Exoskeletons: Recent Progress and Challenges.

Soft exoskeletons hold promise for facilitating monitoring and assistance in case of light impairment and for prolonging independent living. In contrast to rigid material-based exoskeletons, they strongly demand for new approaches of soft sensing and actuation solutions. This chapter overviews soft exoskeletons in contrast to rigid exoskeletons and focuses on the recent advancements on the movement monitoring in lower limb soft exoskeletons. Compliant materials and soft tactile sensing approaches can be utilized to build smart sensorized garments for joint angle measurements (needed for both control and monitoring). However, currently there are still several open challenges derived from the needed close interaction between the human body and the soft exoskeleton itself, especially related to how sensing function and robustness are strongly affected by wearability, which will need to be overcome in the near future.

Editorial for the Special Issue on Tactile Sensing for Soft Robotics and Wearables.

Tactile feedback is needed for the interaction of humans with a worn device, and to enable robots to gather environmental cues and react to their surroundings [...].

Toward Perceptive Soft Robots: Progress and Challenges.

In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real-world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero- and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field.

Integrated Simultaneous Detection of Tactile and Bending Cues for Soft Robotics.

Soft robots should move in an unstructured environment and explore it and, to do so, they should be able to measure and distinguish proprioceptive and exteroceptive stimuli. This can be done by embedding mechanosensing systems in the body of the robot. Here, we present a polydimethylsiloxane block sensorized with an electro-optical system and a resistive strain gauge made with the supersonic cluster beam implantation (SCBI) technique. We show how to integrate these sensing elements during the whole fabrication process of the soft body and we demonstrate that their presence does not change the mechanical properties of the bulk material. Exploiting the position of both sensing systems and a proper combination of the output signals, we present a strategy to measure simultaneously external pressure and positive/negative bending of the body. In particular, the optical system can reveal any mechanical stimulation (external from the soft block or due to its own deformation), while the resistive strain gauge is insensitive to the external pressure, but sensitive to the bending of the body. This solution, here applied to a simple block of soft material, could be extended to the whole body of a soft robot. This approach provides detection and discrimination of the two stimuli (pressure and bending), with low computational effort and without significant mechanical constraint.

Soft Smart Garments for Lower Limb Joint Position Analysis.

Revealing human movement requires lightweight, flexible systems capable of detecting mechanical parameters (like strain and pressure) while being worn comfortably by the user, and not interfering with his/her activity. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for retrieving movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed around knee and ankle. Results show an excellent behavior in the ~30% strain range, hence the correlation between sensors' responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. Ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both knee and ankle smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

Revealing bending and force in a soft body through a plant root inspired approach.

An emerging challenge in soft robotics research is to reveal mechanical solicitations in a soft body. Nature provides amazing clues to develop unconventional components that are capable of compliant interactions with the environment and living beings, avoiding mechanical and algorithmic complexity of robotic design. We inspire from plant-root mechanoperception and develop a strategy able to reveal bending and applied force in a soft body with only two sensing elements of the same kind, and a null computational effort. The stretching processes that lead to opposite tissue deformations on the two sides of the root wall are emulated with two tactile sensing elements, made of soft and stretchable materials, which conform to reversible changes in the shape of the body they are built in and follow its deformations. Comparing the two sensory responses, we can discriminate the concave and the convex side of the bent body. Hence, we propose a new strategy to reveal in a soft body the maximum bending angle (or the maximum deflection) and the externally applied force according to the body's mechanical configuration.

Flexible three-axial force sensor for soft and highly sensitive artificial touch.

A soft tactile sensor able to detect both normal and tangential forces is fabricated with a simple method using conductive textile. Owing to the multi-layered architecture, the capacitive-based tactile sensor is highly sensitive (less than 10 mg and 8 µm, for minimal detectable weight and displacement, respectively) within a wide normal force range (potentially up to 27 N (400 kPa)) and natural touch-like tangential force ranges (from about 0.5 N to 1.8 N). Being flexible, soft, and low cost, this sensor represents an original approach in the emulation of natural touch.

Seebeck coefficient of nanowires interconnected into large area networks.

We measured the macroscopic Seebeck coefficient of silicon nanowires (SiNWs), organized in a highly interconnected networks on large areas (order of mm(2)). The fabricated networks are very reliable with respect to random nanowire failure and are electrically and thermally equivalent to many SiNWs placed in parallel between the electrical contacts. The equivalent SiNWs have a macroscopic length of the order of millimeters and are very narrow (width smaller than 100 nm) so that they can be used to exploit thermoelectric properties at nanoscale for macroscopic electrical power generation and/or cooling. The measurement of the Seebeck coefficient S, facilitated by the macroscopic dimensions of the network, gives an insight into two questions, nanowire effective doping and carrier mobility, which are widely discussed in the literature. We found that the measured value of S is compatible with an effective doping that is higher than that of the original wafer. This higher doping is consistent with the value estimated from the measured electrical conductivity of the SiNWs with the assumption that the electron mobility inside the nanowire is equal to that of bulk silicon.

Correlation between surface stress and apparent Young's modulus of top-down silicon nanowires.

In this work, we report experimental evidence of surface stress effects on the mechanical properties of silicon nanostructures. As-fabricated, top-down silicon nanowires (SiNWs) are bent up without any applied force. This self-buckling is related to the surface relaxation that reaches an equilibrium with bulk deformation due to the material elasticity. We measure the SiNW self-deformation by atomic force microscopy (AFM), and we apply a simple physical model in order to give an estimation of the surface stress. If the equilibrium is altered by a nanoforce, applied by an AFM tip, nanowires find a new equilibrium condition bending down (mechanical bistability). In this work, for the first time, we report a clear and quantitative relationship between the SiNWs' apparent Young's modulus, measured by force-deflection spectroscopy, and the estimated value of surface stress, obtained by self-buckling measurements taking into account the Young's modulus of bulk silicon. This is an experimental confirmation that the surface stress is fundamental in determining mechanical properties of SiNWs, and that the elastic behavior of nanostructures strongly depends on their surfaces.