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Robotic locomotion in subterranean environments is still unsolved, and it requires innovative designs and strategies to overcome the challenges of burrowing and moving in unstructured conditions with high pressure and friction at depths of a few centimeters. Inspired by antagonistic muscle contractions and constant volume coelomic chambers observed in earthworms, we designed and developed a modular soft robot based on a peristaltic soft actuator (PSA). The PSA demonstrates two active configurations from a neutral state by switching the input source between positive and negative pressure. PSA generates a longitudinal force for axial penetration and a radial force for anchorage, through bidirectional deformation of the central bellows-like structure, which demonstrates its versatility and ease of control. The performance of PSA depends on the amount and type of fluid confined in an elastomer chamber, generating different forces and displacements. The assembled robot with five PSA modules enabled to perform peristaltic locomotion in different media. The role of friction was also investigated during experimental locomotion tests by attaching passive scales like earthworm setae to the ventral side of the robot. This study proposes a new method for developing a peristaltic earthworm-like soft robot and provides a better understanding of locomotion in different environments.

Microorganisms move in challenging environments by periodic changes in body shape. In contrast, current artificial microrobots cannot actively deform, exhibiting at best passive bending under external fields. Here, by taking advantage of the wireless, scalable and spatiotemporally selective capabilities that light allows, we show that soft microrobots consisting of photoactive liquid-crystal elastomers can be driven by structured monochromatic light to perform sophisticated biomimetic motions. We realize continuum yet selectively addressable artificial microswimmers that generate travelling-wave motions to self-propel without external forces or torques, as well as microrobots capable of versatile locomotion behaviours on demand. Both theoretical predictions and experimental results confirm that multiple gaits, mimicking either symplectic or antiplectic metachrony of ciliate protozoa, can be achieved with single microswimmers. The principle of using structured light can be extended to other applications that require microscale actuation with sophisticated spatiotemporal coordination for advanced microrobotic technologies. Soft biomimetic microswimmers and microrobots made of photoactive liquid-crystal elastomers and whose body shape is controlled by structured light are able to self-propel and perform complex motion patterns on demand.

Microorganisms can move in complex media, respond to the environment and self-organize. The field of microrobotics strives to achieve these functions in mobile robotic systems of sub-millimetre size. However, miniaturization of traditional robots and their control systems to the microscale is not a viable approach. A promising alternative strategy in developing microrobots is to implement sensing, actuation and control directly in the materials, thereby mimicking biological matter. In this Review, we discuss design principles and materials for the implementation of robotic functionalities in microrobots. We examine different biological locomotion strategies, and we discuss how they can be artificially recreated in magnetic microrobots and how soft materials improve control and performance. We show that smart, stimuli-responsive materials can act as on-board sensors and actuators and that ‘active matter’ enables autonomous motion, navigation and collective behaviours. Finally, we provide a critical outlook for the field of microrobotics and highlight the challenges that need to be overcome to realize sophisticated microrobots, which one day might rival biological machines. Microrobots are envisioned to revolutionize microsurgery and targeted drug delivery. Their design, operation, locomotion and interaction with the environment are inspired by microorganisms. This Review highlights soft, responsive and active materials for the development of (semi-)autonomous microrobots.

The development of functional microsystems and microrobots that have characterized the last decade is the result of a synergistic and effective interaction between the progress of fabrication techniques and the increased availability of smart and responsive materials to be employed in the latter. Functional structures on the microscale have been relevant for a vast plethora of technologies that find application in different sectors including automotive, sensing devices, and consumer electronics, but are now also entering medical clinics. Working on or inside the human body requires increasing complexity and functionality on an ever-smaller scale, which is becoming possible as a result of emerging technology and smart materials over the past decades. In recent years, additive manufacturing has risen to the forefront of this evolution as the most prominent method to fabricate complex 3D structures. In this review, we discuss the rapid 3D manufacturing techniques that have emerged and how they have enabled a great leap in microrobotic applications. The arrival of smart materials with inherent functionalities has propelled microrobots to great complexity and complex applications. We focus on which materials are important for actuation and what the possibilities are for supplying the required energy. Furthermore, we provide an updated view of a new generation of microrobots in terms of both materials and fabrication technology. While two-photon lithography may be the state-of-the-art technology at the moment, in terms of resolution and design freedom, new methods such as two-step are on the horizon. In the more distant future, innovations like molecular motors could make microscale robots redundant and bring about nanofabrication.

Current magnetic systems for microrobotic navigation consist of assemblies of electromagnets, which allow for the wireless accurate steering and propulsion of sub-millimetric bodies. However, large numbers of windings and/or high currents are needed in order to generate suitable magnetic fields and gradients. This means that magnetic navigation systems are typically cumbersome and require a lot of power, thus limiting their application fields. In this paper, we propose a novel propulsion method that is able to dramatically reduce the power demand of such systems. This propulsion method was conceived for navigation systems that achieve propulsion by pulling microrobots with magnetic gradients. We compare this power-efficient propulsion method with the traditional pulling propulsion, in the case of a microrobot swimming in a micro-structured confined liquid environment. Results show that both methods are equivalent in terms of accuracy and the velocity of the motion of the microrobots, while the new approach requires only one ninth of the power needed to generate the magnetic gradients. Substantial equivalence is demonstrated also in terms of the manoeuvrability of user-controlled microrobots along a complex path.

Transurethral resection of the prostate (TURP) is a minimally invasive endoscopic procedure that requires experience and skill of the surgeon. To permit surgical training under realistic conditions we report a novel phantom of the human prostate that can be resected with TURP. The phantom mirrors the anatomy and haptic properties of the gland and permits quantitative evaluation of important surgical performance indicators. Mixtures of soft materials are engineered to mimic the physical properties of the human tissue, including the mechanical strength, the electrical and thermal conductivity, and the appearance under an endoscope. Electrocautery resection of the phantom closely resembles the procedure on human tissue. Ultrasound contrast agent was applied to the central zone, which was not detectable by the surgeon during the surgery but showed high contrast when imaged after the surgery, to serve as a label for the quantitative evaluation of the surgery. Quantitative criteria for performance assessment are established and evaluated by automated image analysis. We present the workflow of a surgical simulation on a prostate phantom followed by quantitative evaluation of the surgical performance. Surgery on the phantom is useful for medical training, and enables the development and testing of endoscopic and minimally invasive surgical instruments.

Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing conditions. Albeit, because of the lack of accurate locomotion models, and given the intrinsic variability among microrobots, analytical control design is not possible. Common data-driven approaches, on the other hand, require running prohibitive numbers of experiments and lead to very sample-specific results. Here we propose a probabilistic learning approach for light-controlled soft microrobots based on Bayesian Optimization (BO) and Gaussian Processes (GPs). The proposed approach results in a learning scheme that is data-efficient, enabling gait optimization with a limited experimental budget, and robust against differences among microrobot samples. These features are obtained by designing the learning scheme through the comparison of different GP priors and BO settings on a semi-synthetic data set. The developed learning scheme is validated in microrobot experiments, resulting in a 115% improvement in a microrobot's locomotion performance with an experimental budget of only 20 tests. These encouraging results lead the way toward self-adaptive microrobotic systems based on light-controlled soft microrobots and probabilistic learning control.

Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate properties of living systems. While only biological materials fully embody these principles, artificial versions are advancing rapidly, promising transformative impacts across various sectors. This roadmap presents authoritative perspectives on animate materials across different disciplines and scales, highlighting their interdisciplinary nature and potential applications in diverse fields including nanotechnology, robotics and the built environment. It underscores the need for concerted efforts to address shared challenges such as complexity management, scalability, evolvability, interdisciplinary collaboration, and ethical and environmental considerations. The framework defined by classifying materials based on their level of animacy can guide this emerging field encouraging cooperation and responsible development. By unravelling the mysteries of living matter and leveraging its principles, we can design materials and systems that will transform our world in a more sustainable manner.

Background Prehypertension predicts established hypertension. In this study, the aim was to analyze left ventricular (LV) mechanics in borderline prehypertensive (pre-HT) and hypertensive (HT) subjects through two-dimensional (2D)-strain echocardiography and then evaluate possible relations between cardiac parameters and insulin metabolism (homeostasis model assessment of insulin resistance (HOMAIR)). Methods Seventy-four consecutive newly diagnosed, untreated HT were divided, on the basis of their office blood pressure (BP) measurements, confirmed by ambulatory BP monitoring (ABPM), in 41 borderline pre-HT (ABPM: 122.5 ± 6.7/76.2 ± 5.2mmHg) and 33 never-treated mild HT (ABPM: 138.3 ± 7.3/87.6 ± 7.1mmHg). Thirty-three healthy normotensive (NT) controls (ABPM: 114.8 ± 6.3/73.1 ± 6.1mmHg) (P < 0.0001) were also studied (NT). All subjects performed 2D color Doppler and pulsed-wave tissue Doppler imaging (PW-TDI). Results Left ventricular mass (LVM) was significantly higher in pre-HT (39.2 ± 8.7g/m2.7) and in HT (43.6 ± 8.5g/m2.7) compared with NT (30.9 ± 7.4g/m2.7) (P < 0.0001). A mild LV diastolic dysfunction was found both with Doppler mitral flow velocity and PW-TDI at mitral annulus level analysis. Longitudinal 2D strain in pre-HT (−18.9% ± 3.4) and in HT (−18.0% ± 3.3) was significantly lower than in NT (−23.9% ± 3.0) (P < 0.002). These LV abnormalities were associated with systolic ABPM, LVM, and HOMAIR. Conclusions Early abnormalities of LV longitudinal systolic deformation were found both in pre-HT and HT, together with a mild LV diastolic dysfunction. In both groups this early cardiac systolic and diastolic dysfunction is associated to insulin resistance, systolic pressure load, and cardiac remodeling.

Disease gene prediction is to date one of the main computational challenges of precision medicine. It is still uncertain if disease genes have unique functional properties that distinguish them from other non-disease genes or, from a network perspective, if they are located randomly in the interactome or show specific patterns in the network topology. In this study, we propose a new method for disease gene prediction based on the use of biological knowledge-bases (gene-disease associations, genes functional annotations, etc.) and interactome network topology. The proposed algorithm called MOSES is based on the definition of two somewhat opposing sets of genes both disease-specific from different perspectives: warm seeds (i.e., disease genes obtained from databases) and cold seeds (genes far from the disease genes on the interactome and not involved in their biological functions). The application of MOSES to a set of 40 diseases showed that the suggested putative disease genes are significantly enriched in their reference disease. Reassuringly, known and predicted disease genes together, tend to form a connected network module on the human interactome, mitigating the scattered distribution of disease genes which is probably due to both the paucity of disease-gene associations and the incompleteness of the interactome.