Modular multi-degree-of-freedom soft origami robots with reprogrammable electrothermal actuation.

Soft robots often draw inspiration from nature to navigate different environments. Although the inching motion and crawling motion of caterpillars have been widely studied in the design of soft robots, the steering motion with local bending control remains challenging. To address this challenge, we explore modular origami units which constitute building blocks for mimicking the segmented caterpillar body. Based on this concept, we report a modular soft Kresling origami crawling robot enabled by electrothermal actuation. A compact and lightweight Kresling structure is designed, fabricated, and characterized with integrated thermal bimorph actuators consisting of liquid crystal elastomer and polyimide layers. With the modular design and reprogrammable actuation, a multiunit caterpillar-inspired soft robot composed of both active units and passive units is developed for bidirectional locomotion and steering locomotion with precise curvature control. We demonstrate the modular design of the Kresling origami robot with an active robotic module picking up cargo and assembling with another robotic module to achieve a steering function. The concept of modular soft robots can provide insight into future soft robots that can grow, repair, and enhance functionality.

Single-step precision programming of decoupled multiresponsive soft millirobots.

Stimuli-responsive soft robots offer new capabilities for the fields of medical and rehabilitation robotics, artificial intelligence, and soft electronics. Precisely programming the shape morphing and decoupling the multiresponsiveness of such robots is crucial to enable them with ample degrees of freedom and multifunctionality, while ensuring high fabrication accuracy. However, current designs featuring coupled multiresponsiveness or intricate assembly processes face limitations in executing complex transformations and suffer from a lack of precision. Therefore, we propose a one-stepped strategy to program multistep shape-morphing soft millirobots (MSSMs) in response to decoupled environmental stimuli. Our approach involves employing a multilayered elastomer and laser scanning technology to selectively process the structure of MSSMs, achieving a minimum machining precision of 30 µm. The resulting MSSMs are capable of imitating the shape morphing of plants and hand gestures and resemble kirigami, pop-up, and bistable structures. The decoupled multistimuli responsiveness of the MSSMs allows them to conduct shape morphing during locomotion, perform logic circuit control, and remotely repair circuits in response to humidity, temperature, and magnetic field. This strategy presents a paradigm for the effective design and fabrication of untethered soft miniature robots with physical intelligence, advancing the decoupled multiresponsive materials through modular tailoring of robotic body structures and properties to suit specific applications.

Defected twisted ring topology for autonomous periodic flip-spin-orbit soft robot.

Periodic spin-orbit motion is ubiquitous in nature, observed from electrons orbiting nuclei to spinning planets orbiting the Sun. Achieving autonomous periodic orbiting motions, along circular and noncircular paths, in soft mobile robotics is crucial for adaptive and intelligent exploration of unknown environments-a grand challenge yet to be accomplished. Here, we report leveraging a closed-loop twisted ring topology with a defect for an autonomous soft robot capable of achieving periodic spin-orbiting motions with programmed circular and re-programmed irregular-shaped trajectories. Constructed by bonding a twisted liquid crystal elastomer ribbon into a closed-loop ring topology, the robot exhibits three coupled periodic self-motions in response to constant temperature or constant light sources: inside-out flipping, self-spinning around the ring center, and self-orbiting around a point outside the ring. The coupled spinning and orbiting motions share the same direction and period. The spinning or orbiting direction depends on the twisting chirality, while the orbital radius and period are determined by the twisted ring geometry and thermal actuation. The flip-spin and orbiting motions arise from the twisted ring topology and a bonding site defect that breaks the force symmetry, respectively. By utilizing the twisting-encoded autonomous flip-spin-orbit motions, we showcase the robot's potential for intelligently mapping the geometric boundaries of unknown confined spaces, including convex shapes like circles, squares, triangles, and pentagons and concaves shapes with multi-robots, as well as health monitoring of unknown confined spaces with boundary damages.

Multiple forces facilitate the aquatic acrobatics of grasshopper and bioinspired robot.

Aquatic locomotion is challenging for land-dwelling creatures because of the high degree of fluidity with which the water yields to loads. We surprisingly found that the Chinese rice grasshopper Oxya chinensis, known for its terrestrial acrobatics, could swiftly launch itself off the water's surface in around 25 ms and seamlessly transition into flight. Biological observations showed that jumping grasshoppers use their front and middle legs to tilt up bodies first and then lift off by propelling the water toward the lower back with hind legs at angular speeds of up to 18°/ms, whereas the swimming grasshoppers swing their front and middle legs in nearly horizontal planes and move hind legs less violently (~8°/ms). Force measurement and model analysis indicated that the weight support could be achieved by hydrostatics which are proportionate to the mass of the grasshoppers, while the propulsions for motion are derived from the controlled limb-water interactions (i.e., the hydrodynamics). After learning the structural and behavioral strategies of the grasshoppers, a robot was created and was capable of swimming and jumping on the water surface like the insects, further demonstrating the effectiveness of decoupling the challenges of aquatic locomotion by the combined use of the static and dynamic hydro forces. This work not only uncovered the combined mechanisms responsible for facilitating aquatic acrobatics in this species but also laid a foundation for developing bioinspired robots that can locomote across multiple media.

Insect-scale jumping robots enabled by a dynamic buckling cascade.

Millions of years of evolution have allowed animals to develop unusual locomotion capabilities. A striking example is the legless-jumping of click beetles and trap-jaw ants, which jump more than 10 times their body length. Their delicate musculoskeletal system amplifies their muscles' power. It is challenging to engineer insect-scale jumpers that use onboard actuators for both elastic energy storage and power amplification. Typical jumpers require a combination of at least two actuator mechanisms for elastic energy storage and jump triggering, leading to complex designs having many parts. Here, we report the new concept of dynamic buckling cascading, in which a single unidirectional actuation stroke drives an elastic beam through a sequence of energy-storing buckling modes automatically followed by spontaneous impulsive snapping at a critical triggering threshold. Integrating this cascade in a robot enables jumping with unidirectional muscles and power amplification (JUMPA). These JUMPA systems use a single lightweight mechanism for energy storage and release with a mass of 1.6 g and 2 cm length and jump up to 0.9 m, 40 times their body length. They jump repeatedly by reengaging the latch and using coiled artificial muscles to restore elastic energy. The robots reach their performance limits guided by theoretical analysis of snap-through and momentum exchange during ground collision. These jumpers reach the energy densities typical of the best macroscale jumping robots, while also matching the rapid escape times of jumping insects, thus demonstrating the path toward future applications including proximity sensing, inspection, and search and rescue.

Programmable self-organization of heterogeneous microrobot collectives.

At the microscale, coupled physical interactions between collectives of agents can be exploited to enable self-organization. Past systems typically consist of identical agents; however, heterogeneous agents can exhibit asymmetric pairwise interactions which can be used to generate more diverse patterns of self-organization. Here, we study the effect of size heterogeneity in microrobot collectives composed of circular, magnetic microdisks on a fluid-air interface. Each microrobot spins or oscillates about its center axis in response to an external oscillating magnetic field, in turn producing local magnetic, hydrodynamic, and capillary forces that enable diverse collective behaviors. We demonstrate through physical experiments and simulations that the heterogeneous collective can exploit the differences in microrobot size to enable programmable self-organization, density, morphology, and interaction with external passive objects. Specifically, we can control the level of self-organization by microrobot size, enable organized aggregation, dispersion, and locomotion, change the overall shape of the collective from circular to ellipse, and cage or expel objects. We characterize the fundamental self-organization behavior across a parameter space of magnetic field frequency, relative disk size, and relative populations; we replicate the behavior through a physical model and a swarming coupled oscillator model to show that the dominant effect stems from asymmetric interactions between the different-sized disks. Our work furthers insights into self-organization in heterogeneous microrobot collectives and moves us closer to the goal of applying such collectives to programmable self-assembly and active matter.

Actuation-enhanced multifunctional sensing and information recognition by magnetic artificial cilia arrays.

Artificial cilia integrating both actuation and sensing functions allow simultaneously sensing environmental properties and manipulating fluids in situ, which are promising for environment monitoring and fluidic applications. However, existing artificial cilia have limited ability to sense environmental cues in fluid flows that have versatile information encoded. This limits their potential to work in complex and dynamic fluid-filled environments. Here, we propose a generic actuation-enhanced sensing mechanism to sense complex environmental cues through the active interaction between artificial cilia and the surrounding fluidic environments. The proposed mechanism is based on fluid-cilia interaction by integrating soft robotic artificial cilia with flexible sensors. With a machine learning-based approach, complex environmental cues such as liquid viscosity, environment boundaries, and distributed fluid flows of a wide range of velocities can be sensed, which is beyond the capability of existing artificial cilia. As a proof of concept, we implement this mechanism on magnetically actuated cilia with integrated laser-induced graphene-based sensors and demonstrate sensing fluid apparent viscosity, environment boundaries, and fluid flow speed with a reconfigurable sensitivity and range. The same principle could be potentially applied to other soft robotic systems integrating other actuation and sensing modalities for diverse environmental and fluidic applications.

Do we empathize humanoid robots and humans in the same way? Behavioral and multimodal brain imaging investigations.

Humanoid robots have been designed to look more and more like humans to meet social demands. How do people empathize humanoid robots who look the same as but are essentially different from humans? We addressed this issue by examining subjective feelings, electrophysiological activities, and functional magnetic resonance imaging signals during perception of pain and neutral expressions of faces that were recognized as patients or humanoid robots. We found that healthy adults reported deceased feelings of understanding and sharing of humanoid robots' compared to patients' pain. Moreover, humanoid robot (vs. patient) identities reduced long-latency electrophysiological responses and blood oxygenation level-dependent signals in the left temporoparietal junction in response to pain (vs. neutral) expressions. Furthermore, we showed evidence that humanoid robot identities inhibited a causal input from the right ventral lateral prefrontal cortex to the left temporoparietal junction, contrasting the opposite effect produced by patient identities. These results suggest a neural model of modulations of empathy by humanoid robot identity through interactions between the cognitive and affective empathy networks, which provides a neurocognitive basis for understanding human-robot interactions.

Adjustable object floating states based on three-segment three-phase contact line evolution.

SignificanceAdjusting the floating states when objects float on water shows great potential for assembly, mineral flotation, nanostructured construction, and floating robot design, but the real-time regulation of floating states is challenging. Inspired by the different floating states of a falling fruit, we propose a facile strategy to transform the object between different floating states based on a three-segment three-phase contact line evolution. In addition, the potential of floating state transformation in solar-powered water evaporation, interface catalysis, and drug delivery is demonstrated. These findings provide insights into floating regulation and show great potential for floating-related applications.

Twisting for soft intelligent autonomous robot in unstructured environments.

Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.

Optomagnetic Coordination Helical Robot with Shape Transformation and Multimodal Motion Capabilities.

Soft robots with magnetic responsiveness exhibit diverse motion modes and programmable shape transformations. While the fixed magnetization configuration facilitates coupling control of robot posture and motion, it limits individual posture control to some extent. This poses a challenge in independently controlling the robot's transformation and motion, restricting its versatile applications. This research introduces a multifunctional helical robot responsive to both light and magnetism, segregating posture control from movements. Light fields assist in robot shaping, achieving a 78% maximum diameter shift. Magnetic fields guide helical robots in multimodal motions, encompassing rotation, flipping, rolling, and spinning-induced propulsion. By controlling multimodal locomotion and shape transformation on demand, helical robots gain enhanced flexibility. This innovation allows them to tightly grip and wirelessly transport designated payloads, showcasing potential applications in drug delivery, soft grippers, and chemical reaction platforms. The unique combination of structural design and control methods holds promise for intelligent robots in the future.

Retrospective analysis of the learning curve in perineal robot-assisted prostate biopsy.

INTRODUCTION: Magnetic resonance imaging-transrectal ultrasound (MRI-TRUS)-fusion biopsy (FBx) of the prostate allows targeted sampling of suspicious lesions within the prostate, identified by multiparametric MRI. Due to its reliable results and feasibility, perineal MRI/TRUS FBx is now the gold standard for prostate cancer (PC) diagnosis. There are various systems for performing FBx on the market, for example, software-based, semirobotic, or robot-assisted platform solutions. Their semiautomated workflow promises high process quality independent of the surgeon's experience. The aim of this study was to analyze how the surgeon's experience influences the cancer detection rate (CDR) via targeted biopsy (TB) and the procedure's duration in robot-assisted FBx. PATIENTS AND METHODS: A total of 1716 men who underwent robot-assisted FBx involving a combination of targeted and systematic sampling between October 2015 and April 2022 were analyzed. We extracted data from the patients' electronic medical records retrospectively. Primary endpoints were the CDR by TB and the procedure's duration. For our analysis, surgeons were divided into three levels of experience: ≤20 procedures (little), 21-100 procedures (intermediate), and >100 procedures (high). Statistical analysis was performed via regression analyses and group comparisons. RESULTS: Median age, prostate-specific antigen level, and prostate volume of the cohort were 67 (±7.7) years, 8.13 (±9.4) ng/mL, and 53 (±34.2) mL, respectively. Median duration of the procedure was 26 (±10.9) min. The duration decreased significantly with the surgeon's increasing experience from 35.1 (little experience) to 28.4 (intermediate experience) to 24.0 min (high experience) (p < 0.001). Using TB only, significant PC (sPC) was diagnosed in 872/1758 (49.6%) of the men. The CDR revealed no significant correlation with the surgeon's experience in either group comparison (p = 0.907) or in regression analysis (p = 0.65). CONCLUSION: While the duration of this procedure decreases with increasing experience, the detection rate of sPC in TB is not significantly associated with the experience of the surgeon performing robot-assisted FBx. This robot-assisted biopsy system's diagnostic accuracy therefore appears to be independent of experience.

Assessing the efficacy of pelvic floor muscle training and duloxetine on urinary continence recovery following radical prostatectomy: A randomized clinical trial.

BACKGROUND: Urinary incontinence (UI) can negatively impact quality of life (QoL) after robot-assisted radical prostatectomy (RARP). Pelvic floor muscle training (PFMT) and duloxetine are used to manage post-RARP UI, but their efficacy remains uncertain. We aimed to investigate the efficacy of PFMT and duloxetine in promoting urinary continence recovery (UCR) after RARP. METHODS: A randomized controlled trial involving patients with urine leakage after RARP from May 2015 to February 2018. Patients were randomized into 1 of 4 arms: (1) PFMT-biofeedback, (2) duloxetine, (3) combined PFMT-biofeedback and duloxetine, (4) control arm. PFMT consisted of pelvic muscle exercises conducted with electromyographic feedback weekly, for 3 months. Oral duloxetine was administered at bedtime for 3 months. The primary outcome was prevalence of continence at 6 months, defined as using ≤1 security pad. Urinary symptoms and QoL were assessed by using a visual analogue scale, and validated questionnaires. RESULTS: From the 240 patients included in the trial, 89% of patients completed 1 year of follow-up. Treatment compliance was observed in 88% (92/105) of patients receiving duloxetine, and in 97% (104/107) of patients scheduled to PFMT-biofeedback sessions. In the control group 96% of patients had achieved continence at 6 months, compared with 90% (p = 0.3) in the PMFT-biofeedback, 73% (p = 0.008) in the duloxetine, and 69% (p = 0.003) in the combined treatment arm. At 6 months, QoL was classified as uncomfortable or worse in 17% of patients in the control group, compared with 44% (p = 0.01), 45% (p = 0.008), and 34% (p = 0.07), respectively. Complete preservation of neurovascular bundles (NVB) (OR: 2.95; p = 0.048) was the only perioperative intervention found to improve early UCR. CONCLUSIONS: PFMT-biofeedback and duloxetine demonstrated limited impact in improving UCR after RP. Diligent NVB preservation, along with preoperative patient and disease characteristics, are the primary determinants for early UCR.

An Untethered Soft Crawling Robot Driven by Wireless Power Transfer Technology.

Soft robots based on flexible materials have attracted the attention due to high flexibility and great environmental adaptability. Among the common driving modes, electricity, light, and magnetism have the limitations of wiring, poor penetration capability, and sophisticated equipment, respectively. Here, an emerging wireless driving mode is proposed for the soft crawling robot based on wireless power transfer (WPT) technology. The receiving coil at the robot's tail, as an energy transfer station, receives energy from the transmitting coil and supplies the electrothermal responsiveness to drive the robot's crawling. By regulating the WPT's duration to control the friction between the robot and the ground, bidirectional crawling is realized. Furthermore, the receiving coil is also employed as a sensory organ to equip the robot with localization, ID recognition, and sensing capabilities based on electromagnetic coupling. This work provides an innovative and promising strategy for the design and integration of soft crawling robots, exhibiting great potential in the field of intelligent robots.

UV Light-Mediated Hydrolytic Reaction to Develop Magnetic Hydrogel Actuators with Spatially Distributed Ferriferous Oxide Microparticles.

Magnetic hydrogel actuators are developed by incorporating magnetic fillers into the hydrogel matrix. Regulating the distribution of these fillers is key to the exhibited functionalities but is still challenging. Here a facile way to spatially synthesize ferrosoferric oxide (Fe3O4) microparticles in situ in a thermal-responsive hydrogel is reported. This method involves the photo-reduction of Fe3+ ions coordinated with carboxylate groups in polymer chains, and the hydrolytic reaction of the reduced Fe2+ ions with residual Fe3+ ions. By controlling the irradiation time and position, the concentration of Fe3O4 microparticles can be spatially controlled, and the resulting Fe3O4 pattern enables the hydrogel to exhibit complex locomotion driven by magnet, temperature, and NIR light. This method is convenient and extendable to other hydrogel systems to realize more complicated magneto-responsive functionalities.

Electricity-Driven Strategies for Bioinspired Multifunctional Swimming Marangoni Robots Based on Super-Aligned Carbon Nanotube Composites.

Marangoni actuators that are propelled by surface tension gradients hold significant potential in small-scale swimming robots. Nevertheless, the release of "fuel" for conventional chemical Marangoni actuators is not easily controllable, and the single swimming function also limits application areas. Constructing controllable Marangoni robots with multifunctions is still a huge challenge. Herein, inspired by water striders, electricity-driven strategies are proposed for a multifunctional swimming Marangoni robot (MSMR), which is fabricated by super-aligned carbon nanotube (SACNT) and polyimide (PI) composite. The MSMR consists of a Marangoni actuator and air-ambient actuators. Owing to the temperature gradient generated by the electrical stimulation on the water surface, the Marangoni actuators can swim controllably with linear, turning, and rotary motions, mimicking the walking motion of water striders. In addition, the Marangoni actuators can also be driven by light. Importantly, the air-ambient actuators fabricated by SACNT/PI bilayer structures demonstrate the function of grasping objects on the water surface when electrically Joule-heated, mimicking the predation behavior of water striders. With the synergistic effect of the Marangoni actuator and air-ambient actuators, the MSMR can navigate mazes with tunnels and grasp objects. This research will provide a new inspiration for smart actuators and swimming robots.

Field-Directed Motion, Cargo Capture, and Closed-Loop Controlled Navigation of Microellipsoids.

Microrobots have the potential for diverse applications, including targeted drug delivery and minimally invasive surgery. Despite advancements in microrobot design and actuation strategies, achieving precise control over their motion remains challenging due to the dominance of viscous drag, system disturbances, physicochemical heterogeneities, and stochastic Brownian forces. Here, a precise control over the interfacial motion of model microellipsoids is demonstrated using time-varying rotating magnetic fields. The impacts of microellipsoid aspect ratio, field characteristics, and magnetic properties of the medium and the particle on the motion are investigated. The role of mobile micro-vortices generated is highlighted by rotating microellipsoids in capturing, transporting, and releasing cargo objects. Furthermore, an approach is presented for controlled navigation through mazes based on real-time particle and obstacle sensing, path planning, and magnetic field actuation without human intervention. The study introduces a mechanism of directing motion of microparticles using rotating magnetic fields, and a control scheme for precise navigation and delivery of micron-sized cargo using simple microellipsoids as microbots.

Integrated Sensors for Soft Medical Robotics.

Minimally invasive procedures assisted by soft robots for surgery, diagnostics, and drug delivery have unprecedented benefits over traditional solutions from both patient and surgeon perspectives. However, the translation of such technology into commercialization remains challenging. The lack of perception abilities is one of the obstructive factors paramount for a safe, accurate and efficient robot-assisted intervention. Integrating different types of miniature sensors onto robotic end-effectors is a promising trend to compensate for the perceptual deficiencies in soft robots. For example, haptic feedback with force sensors helps surgeons to control the interaction force at the tool-tissue interface, impedance sensing of tissue electrical properties can be used for tumor detection. The last decade has witnessed significant progress in the development of multimodal sensors built on the advancement in engineering, material science and scalable micromachining technologies. This review article provides a snapshot on common types of integrated sensors for soft medical robots. It covers various sensing mechanisms, examples for practical and clinical applications, standard manufacturing processes, as well as insights on emerging engineering routes for the fabrication of novel and high-performing sensing devices.

Perioperative, Oncological, and Functional Outcomes Between Robot-Assisted Laparoscopic Prostatectomy and Open Radical Retropubic Prostatectomy: A Randomized Clinical Trial.

PURPOSE: Limited high-quality studies have compared robot-assisted laparoscopic prostatectomy (RALP) vs open retropubic radical prostatectomy. We sought to compare their postoperative outcomes in a randomized setting. MATERIALS AND METHODS: In a single center, 354 men with newly diagnosed prostate cancer were assessed for eligibility; 342 were randomized (1:1). The primary outcome was 90-day complication rates. Functional outcomes and quality of life were assessed over 18 months, and oncological outcomes, biochemical recurrence-free survival, and additional treatment over 36 months. RESULTS: From 2014 to 18, 327 patients underwent surgery (retropubic radical prostatectomy = 156, RALP = 171). Complications occurred in 27 (17.3%) vs 19 (11.1%; P = .107). Patients undergoing RALP experienced lower median bleeding (250.0 vs 719.5 mL; P < .001) and shorter hospitalization time. Urinary EPIC (Expanded Prostate Cancer Index Composite) median scores were better for RALP over 18 months, with higher continence rate at 3 months (80.5% vs 64.7%; P = .002), 6 months (90.1% vs 81.6%; P = .036) and 18 months (95.4% vs 78.8%; P < .001). Sexual EPIC and Sexual Health Inventory for Men median scores were higher with RALP up to 12 months, while the potency rate was superior at 3 months (23.9% vs 5.3%; P = .001) and 6 months (30.6% vs 6.9%; P < .001). Quality of life over the 18 months and oncological outcomes over 36 months were not significantly different between arms. CONCLUSIONS: Complications at 90 days were similar. RALP showed superior sexual outcomes at 1 year, improved urinary outcomes at 18 months, and comparable oncological outcomes at 36 months. TRIAL REGISTRATION: Prospective Analysis of Robot-Assisted Surgery; NCT02292914. https://clinicaltrials.gov/ct2/show/NCT02292914?cond=NCT02292914&draw=2&rank=1.

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.