Design of 3D Controller Using Nanocracking Structure-Based Stretchable Strain Sensor.

In this study, we introduce a novel design for a three-dimensional (3D) controller, which incorporates the omni-purpose stretchable strain sensor (OPSS sensor). This sensor exhibits both remarkable sensitivity, with a gauge factor of approximately 30, and an extensive working range, accommodating strain up to 150%, thereby enabling accurate 3D motion sensing. The 3D controller is structured such that its triaxial motion can be discerned independently along the X, Y, and Z axes by quantifying the deformation of the controller through multiple OPSS sensors affixed to its surface. To ensure precise and real-time 3D motion sensing, a machine learning-based data analysis technique was implemented for the effective interpretation of the multiple sensor signals. The outcomes reveal that the resistance-based sensors successfully and accurately track the 3D controller's motion. We believe that this innovative design holds the potential to augment the performance of 3D motion sensing devices across a diverse range of applications, encompassing gaming, virtual reality, and robotics.

Cable-Driven Haptic Interface With Movable Bases Achieving Maximum Workspace and Isotropic Force Exertion.

Haptic interactions play an essential role in education to enhance learning efficiency; however, haptic information for virtual educational content remains lacking. This article proposes a planar cable-driven haptic interface with movable bases that can display isotropic force feedback with maximum workspace extension on a commercial screen display. A generalized kinematic and static analysis of the cable-driven mechanism is derived by considering movable pulleys. Based on the analyses, a system including movable bases is designed and controlled to maximize the workspace subject to isotropic force exertion for the target screen area. The proposed system is evaluated experimentally as a haptic interface represented by the workspace, isotropic force-feedback range, bandwidth, Z-width, and user experiment. The results indicate that the proposed system can maximize workspace to the target rectangular area and exert isotropic force up to 94.0% of the theoretical computed one within the workspace.

Biohybrid 3D Printing of a Tissue-Sensor Platform for Wireless, Real-Time, and Continuous Monitoring of Drug-Induced Cardiotoxicity.

Drug-induced cardiotoxicity is regarded as a major hurdle in the early stages of drug development. Although there are various methods for preclinical cardiotoxicity tests, they cannot completely predict the cardiotoxic potential of a compound due to the lack of physiological relevance. Recently, 3D engineered heart tissue (EHT) has been used to investigate cardiac muscle functions as well as pharmacological effects by exhibiting physiological auxotonic contractions. However, there is still no adequate platform for continuous monitoring to test acute and chronic pharmacological effects in vitro. Here, a biohybrid 3D printing method for fabricating a tissue-sensor platform, composed of a bipillar-grafted strain gauge sensor and EHT, is first introduced. Two pillars are three-dimensionally printed as grafts onto a strain gauge-embedded substrate to promote the EHT contractility and guide the self-assembly of the EHTs along with the strain gauge. In addition, the integration of a wireless multi-channel electronic system allows for continuous monitoring of the EHT contractile force by the tissue-sensor platform and, ultimately, for the observation of the acute and chronic drug effects of cardiotoxicants. In summary, biohybrid 3D printing technology is expected to be a potential fabrication method to provide a next-generation tissue-sensor platform for an effective drug development process.

Upgraded User-Friendly Image-Activated Microfluidic Cell Sorter Using an Optimized and Fast Deep Learning Algorithm.

Image-based cell sorting is essential in biological and biomedical research. The sorted cells can be used for downstream analysis to expand our knowledge of cell-to-cell differences. We previously demonstrated a user-friendly image-activated microfluidic cell sorting technique using an optimized and fast deep learning algorithm. Real-time isolation of cells was carried out using this technique with an inverted microscope. In this study, we devised a recently upgraded sorting system. The cell sorting techniques shown on the microscope were implemented as a real system. Several new features were added to make it easier for the users to conduct the real-time sorting of cells or particles. The newly added features are as follows: (1) a high-resolution linear piezo-stage is used to obtain in-focus images of the fast-flowing cells; (2) an LED strobe light was incorporated to minimize the motion blur of fast-flowing cells; and (3) a vertical syringe pump setup was used to prevent the cell sedimentation. The sorting performance of the upgraded system was demonstrated through the real-time sorting of fluorescent polystyrene beads. The sorter achieved a 99.4% sorting purity for 15 µm and 10 µm beads with an average throughput of 22.1 events per second (eps).

Regulation of BRCA1 stability through the tandem UBX domains of isoleucyl-tRNA synthetase 1.

Aminoacyl-tRNA synthetases (ARSs) have evolved to acquire various additional domains. These domains allow ARSs to communicate with other cellular proteins in order to promote non-translational functions. Vertebrate cytoplasmic isoleucyl-tRNA synthetases (IARS1s) have an uncharacterized unique domain, UNE-I. Here, we present the crystal structure of the chicken IARS1 UNE-I complexed with glutamyl-tRNA synthetase 1 (EARS1). UNE-I consists of tandem ubiquitin regulatory X (UBX) domains that interact with a distinct hairpin loop on EARS1 and protect its neighboring proteins in the multi-synthetase complex from degradation. Phosphomimetic mutation of the two serine residues in the hairpin loop releases IARS1 from the complex. IARS1 interacts with BRCA1 in the nucleus, regulates its stability by inhibiting ubiquitylation via the UBX domains, and controls DNA repair function.

Combination of an inject-and-transfer system for serial femtosecond crystallography.

Serial femtosecond crystallography (SFX) enables the determination of room-temperature crystal structures of macromolecules with minimized radiation damage and provides time-resolved molecular dynamics by pump-probe or mix-and-inject experiments. In SFX, a variety of sample delivery methods with unique advantages have been developed and applied. The combination of existing sample delivery methods can enable a new approach to SFX data collection that combines the advantages of the individual methods. This study introduces a combined inject-and-transfer system (BITS) method for sample delivery in SFX experiments: a hybrid injection and fixed-target scanning method. BITS allows for solution samples to be reliably deposited on ultraviolet ozone (UVO)-treated polyimide films, at a minimum flow rate of 0.5 nl min-1, in both vertical and horizontal scanning modes. To utilize BITS in SFX experiments, lysozyme crystal samples were embedded in a viscous lard medium and injected at flow rates of 50-100 nl min-1 through a syringe needle onto a UVO-treated polyimide film, which was mounted on a fixed-target scan stage. The crystal samples deposited on the film were raster scanned with an X-ray free electron laser using a motion stage in both horizontal and vertical directions. Using the BITS method, the room-temperature structure of lysozyme was successfully determined at a resolution of 2.1 Å, and thus BITS could be utilized in future SFX experiments.

Promoting Long-Term Cultivation of Motor Neurons for 3D Neuromuscular Junction Formation of 3D In Vitro Using Central-Nervous-Tissue-Derived Bioink.

3D cell printing technology is in the spotlight for producing 3D tissue or organ constructs useful for various medical applications. In printing of neuromuscular tissue, a bioink satisfying all the requirements is a challenging issue. Gel integrity and motor neuron activity are two major characters because a harmonious combination of extracellular materials essential to motor neuron activity consists of disadvantages in mechanical properties. Here, a method for fabrication of 3D neuromuscular tissue is presented using a porcine central nervous system tissue decellularized extracellular matrix (CNSdECM) bioink. CNSdECM retains CNS tissue-specific extracellular molecules, provides rheological properties crucial for extrusion-based 3D cell printing, and reveals positive effects on the growth and maturity of axons of motor neurons compared with Matrigel. It also allows long-term cultivation of human-induced-pluripotent-stem-cell-derived lower motor neurons and sufficiently supports their cellular behavior to carry motor signals to muscle fibers. CNSdECM bioink holds great promise for producing a tissue-engineered motor system using 3D cell printing.

Real-time measurement of intraocular pressure variation during automatic intravitreal injections: An ex-vivo experimental study using porcine eyes.

PURPOSE: To measure needle insertion force and change in intraocular pressure (IOP) in real-time during intravitreal injection (IVI). The effects of needle size, insertion speed, and injection rate to IOP change were investigated. METHODS: Needle insertion and fluid injection were performed on 90 porcine eyeballs using an automatic IVI device. The IVI conditions were divided according to needle sizes of 27-gauge (G), 30G, and 33G; insertion speeds of 1, 2, and 5 mm/s; and injection rates of 0.01, 0.02, and 0.05 mL/s. Insertion force and IOP were measured in real-time using a force sensor and a pressure transducer. RESULTS: The peak IOP was observed when the needle penetrated the sclera; the average IOP elevation was 96.3, 67.1, and 59.4 mmHg for 27G, 30G, and 33G needles, respectively. An increase in insertion speed caused IOP elevation at the moment of penetration, but this effect was reduced as needle size decreased: 109.8-85.9 mmHg in 27G for 5-1 mm/s (p = 0.0149) and 61.8-60.7 mmHg in 33G for 5-1 mm/s (p = 0.8979). Injection speed was also related to IOP elevation during the stage of drug injection: 16.65 and 11.78 mmHg for injection rates of 0.05 and 0.01 mL/s (p < 0.001). CONCLUSION: The presented data offers an understanding of IOP changes during each step of IVI. Slow needle insertion can reduce IOP elevation when using a 27G needle. Further, the injection rate must be kept low to avoid IOP elevations during the injection stage.

Sensor-Embedded Automatic Grasping Forceps for Precise Corneal Suture in Penetrating Keratoplasty.

In penetrating keratoplasty (PKP), the proper corneal suture placement is very important for successful transplantation and restoring functional vision. Generating sutures with accurate depth is difficult for the surgeon because of the tissue's softness, lack of depth information, and hand tremors. In this paper, an automatic cornea grasping device is proposed, which detects when the device reaches the target suture depth. When the device reaches the target depth, the device rapidly grasps the cornea to prevent error induced by human hand tremors. In the paper, the performance of the proposed sensor, the actuator, and the device are experimentally verified with ex vivo experiment. The result showed that the proposed device could enhance the accuracy and precision of the corneal suture depth.

User-friendly image-activated microfluidic cell sorting technique using an optimized, fast deep learning algorithm.

Image-activated cell sorting is an essential biomedical research technique for understanding the unique characteristics of single cells. Deep learning algorithms can be used to extract hidden cell features from high-content image information to enable the discrimination of cell-to-cell differences in image-activated cell sorters. However, such systems are challenging to implement from a technical perspective due to the advanced imaging and sorting requirements and the long processing times of deep learning algorithms. Here, we introduce a user-friendly image-activated microfluidic sorting technique based on a fast deep learning model under the TensorRT framework to enable sorting decisions within 3 ms. The proposed sorter employs a significantly simplified operational procedure based on the use of a syringe connected to a piezoelectric actuator. The sorter has a 2.5 ms latency. The utility of the sorter was demonstrated through real-time sorting of fluorescent polystyrene beads and cells. The sorter achieved 98.0%, 95.1%, and 94.2% sorting purities for 15 µm and 10 µm beads, HL-60 and Jurkat cells, and HL-60 and K562 cells, respectively, with a throughput of up to 82.8 events per second (eps).

Application of a high-throughput microcrystal delivery system to serial femtosecond crystallography.

Microcrystal delivery methods are pivotal in the use of serial femtosecond crystallography (SFX) to resolve the macromolecular structures of proteins. Here, the development of a novel technique and instruments for efficiently delivering microcrystals for SFX are presented. The new method, which relies on a one-dimensional fixed-target system that includes a microcrystal container, consumes an extremely low amount of sample compared with conventional two-dimensional fixed-target techniques at ambient temperature. This novel system can deliver soluble microcrystals without highly viscous carrier media and, moreover, can be used as a microcrystal growth device for SFX. Diffraction data collection utilizing this advanced technique along with a real-time visual servo scan system has been successfully demonstrated for the structure determination of proteinase K microcrystals at 1.85 Šresolution.

Training-Free Bayesian Self-Adaptive Classification for sEMG Pattern Recognition Including Motion Transition.

A direct, ready-to-use surface electromyogram (sEMG) pattern classification algorithm that does not require prerequisite training, regardless of the user, is proposed herein. In addition to data collection, conventional supervised learning approaches for sEMG require labeling and segmenting the data and additional time for the learning algorithm. Consequently, these approaches cannot cope well with sEMG patterns during motion transitions of various movement speeds. The proposed unsupervised and self-adaptive method employs an iterative self-adaptive procedure realized by the probabilistic methods of diffusion, updating, and registration to cluster the activation patterns simultaneously in real time, and classify the current sEMG as new clustered patterns. Experiments demonstrated that even for the same motion, the proposed method could autonomously detect changes in muscular activation patterns varying with the speed of motion. Furthermore, some patterns of both steady- and transient-state motions could be distinguished. In addition, it was verified that the classified sEMG pattern could be correlated consistently with the actual motion, thereby realizing a high level of motion classification.

Preliminary Study of Virtual sEMG Signal-Assisted Classification.

Surface electromyography (sEMG) is widely used in various fields to analyze user intentions. Conventional sEMG-based classifications are electrode-dependent; thus, trained classifiers cannot be applied to other electrodes that have different parameters. This defect degrades the practicability of sEMG-based applications. In this study, we propose a virtual sEMG signal-assisted classification to achieve electrode-independent classification. The virtual signal for any electrode configuration can be generated using muscle activation signals obtained from the proposed model. The feasibility of the virtual signal is demonstrated with regard to i) classifications using fewer sEMG channels by a pre-trained classifier without re-training and ii) electrode-independent classifications. This study focuses on preliminary tests of virtual sEMG signal-assisted classification. Future studies should consider model improvement and experiments involving more subjects to achieve plug-and-play classification.

Nylon mesh-based sample holder for fixed-target serial femtosecond crystallography.

Fixed-target serial femtosecond crystallography (FT-SFX) was an important advance in crystallography by dramatically reducing sample consumption, while maintaining the benefits of SFX for obtaining crystal structures at room temperature without radiation damage. Despite a number of advantages, preparation of a sample holder for the sample delivery in FT-SFX with the use of many crystals in a single mount at ambient temperature is challenging as it can be complicated and costly, and thus, development of an efficient sample holder is essential. In this study, we introduced a nylon mesh-based sample holder enclosed by a polyimide film. This sample holder can be rapidly manufactured using a commercially available nylon mesh with pores of a desired size at a low cost without challenging technology. Furthermore, this simple device is highly efficient in data acquisition. We performed FT-SFX using a nylon mesh-based sample holder and collected over 130,000 images on a single sample holder using a 30 Hz X-ray pulse for 1.2 h. We determined the crystal structures of lysozyme and glucose isomerase using the nylon mesh at 1.65 and 1.75 Å, respectively. The nylon mesh exposed to X-rays produced very low levels of background scattering at 3.75 and 4.30 Å, which are negligible for data analysis. Our method provides a simple and rapid but highly efficient way to deliver samples for FT-SFX.

A 3D cell printed muscle construct with tissue-derived bioink for the treatment of volumetric muscle loss.

Volumetric muscle loss (VML) is an irrecoverable injury associated with muscle loss greater than 20%. Although hydrogel-based 3D engineered muscles and the decellularized extracellular matrix (dECM) have been considered for VML treatment, they have shown limited efficacy. We established a novel VML treatment with dECM bioink using 3D cell printing technology. Volumetric muscle constructs composed of cell-laden dECM bioinks were generated with a granule-based printing reservoir. The 3D cell printed muscle constructs exhibited high cell viability without generating hypoxia and enhanced de novo muscle formation in a VML rat model. To improve functional recovery, prevascularized muscle constructs that mimic the hierarchical architecture of vascularized muscles were fabricated through coaxial nozzle printing with muscle and vascular dECM bioinks. Spatially printing tissue-specific dECM bioinks offers organized microenvironmental cues for the differentiation of each cell and improves vascularization, innervation, and functional recovery. Our present results suggest that a 3D cell printing and tissue-derived bioink-based approach could effectively generate biomimetic engineered muscles to improve the treatment of VML injuries.

Simple and Fast Compensation of sEMG Interface Rotation for Robust Hand Motion Recognition.

Surface electromyography (sEMG) measurements have demonstrated the potential to recognize complex hand motions. In addition, sEMG enables natural recognition without disturbing movements, and thus, can be used in various fields such as teleoperation, assistant robots, and prosthetic hands. However, sEMG signals highly depend on electrode placements due to the complex muscle structures. A shift of the electrode can lead to inconsistent signal measurement. Thus, sEMG-based recognition is not practical for applications that require long-term and repeated usage. This paper proposes compensation of sEMG interface rotation for robust motion recognition. Once the relationship between sEMG signals and motions is trained, additional training for different electrode configurations is not necessary for a band-type interface. The proposed process is simple and fast. The interface rotation can be compensated for by performing only a single motion for approximately 2 s. The single motion for compensation is dependent on the muscle properties of the user. Generally, ulnar deviation may work. To demonstrate the proposed compensation, recognition of five hand motions is conducted. The experimental results indicate that the proposed compensation can cover the overall range of rotation. In addition, the proposed compensation is validated with a transradial amputee.

Fully chip-embedded automation of a multi-step lab-on-a-chip process using a modularized timer circuit.

For highly-integrated microfluidic systems, an actuation system is necessary to control the flow; however, the bulk of actuation devices including pumps or valves has impeded the broad application of integrated microfluidic systems. Here, we suggest a microfluidic process control method based on built-in microfluidic circuits. The circuit is composed of a fluidic timer circuit and a pneumatic logic circuit. The fluidic timer circuit is a serial connection of modularized timer units, which sequentially pass high pressure to the pneumatic logic circuit. The pneumatic logic circuit is a NOR gate array designed to control the liquid-controlling process. By using the timer circuit as a built-in signal generator, multi-step processes could be done totally inside the microchip without any external controller. The timer circuit uses only two valves per unit, and the number of process steps can be extended without limitation by adding timer units. As a demonstration, an automation chip has been designed for a six-step droplet treatment, which entails 1) loading, 2) separation, 3) reagent injection, 4) incubation, 5) clearing and 6) unloading. Each process was successfully performed for a pre-defined step-time without any external control device.

Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip.

Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.

Wireless sEMG System with a Microneedle-Based High-Density Electrode Array on a Flexible Substrate.

Surface electromyography (sEMG) signals reflect muscle contraction and hence, can provide information regarding a user's movement intention. High-density sEMG systems have been proposed to measure muscle activity in small areas and to estimate complex motion using spatial patterns. However, conventional systems based on wet electrodes have several limitations. For example, the electrolyte enclosed in wet electrodes restricts spatial resolution, and these conventional bulky systems limit natural movements. In this paper, a microneedle-based high-density electrode array on a circuit integrated flexible substrate for sEMG is proposed. Microneedles allow for high spatial resolution without requiring conductive substances, and flexible substrates guarantee stable skin-electrode contact. Moreover, a compact signal processing system is integrated with the electrode array. Therefore, sEMG measurements are comfortable to the user and do not interfere with the movement. The system performance was demonstrated by testing its operation and estimating motion using a Gaussian mixture model-based, simplified 2D spatial pattern.

In vivo 3D measurement of moxifloxacin and gatifloxacin distributions in the mouse cornea using multiphoton microscopy.

Moxifloxacin and gatifloxacin are fourth-generation fluoroquinolone antibiotics used in the clinic to prevent or treat ocular infections. Their pharmacokinetics in the cornea is usually measured from extracted ocular fluids or tissues, and in vivo direct measurement is difficult. In this study multiphoton microscopy (MPM), which is a 3D optical microscopic technique based on multiphoton fluorescence, was applied to the measurement of moxifloxacin and gatifloxacin distribution in the cornea. Intrinsic multiphoton fluorescence properties of moxifloxacin and gatifloxacin were characterized, and their distributions in mouse cornea in vivo were measured by 3D MPM imaging. Both moxifloxacin and gatifloxacin had similar multiphoton spectra, while moxifloxacin had stronger fluorescence than gatifloxacin. MPM imaging of mouse cornea in vivo showed (1) moxifloxacin had good penetration through the superficial corneal epithelium, while gatifloxacin had relatively poor penetration, (2) both ophthalmic solutions had high intracellular distribution. In vivo MPM results were consistent with previous studies. This study demonstrates the feasibility of MPM as a method for in vivo direct measurement of moxifloxacin and gatifloxacin in the cornea.