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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). [ABSTRACT FROM AUTHOR]

In corneal transplantation, 16 submillimeter-sized sutures are generated around the circular-shaped graft cornea. A major challenge in corneal transplantation is the generation of uniformly shaped sutures, where the suture shapes need to be changed depending on the patient. In this study, a corneal suturing robot that can produce sutures of the desired shape with high uniformity is described. The proposed robot manipulates the corneal tissue deformation before inserting the needle for suture shape control. A simulation using the finite element method was proposed to predict the suture shape. The suturing experiment was conducted on a porcine model, and the result was compared with the simulation. As a result, the proposed robot was able to generate sutures with a standard deviation of 108  $\mu$ m in length and 36  $\mu$ m in depth. The mean absolute error between the simulation and the experiment was 95  $\mu$ m in length and 31  $\mu$ m in depth. This is the first study to suggest a method for controlling the suture shape and quantitatively analyzing it in ophthalmic surgery. [ABSTRACT FROM AUTHOR]

Serial femtosecond crystallography (SFX) enables the determination of the room‐temperature crystal structure of macromolecules, as well as providing time‐resolved molecular dynamics data in pump–probe experiments. Fixed‐target SFX (FT‐SFX) can minimize sample consumption and physical effects on crystals during sample delivery. In FT‐SFX studies, having a sample holder that can stably fix crystal samples is one of the key elements required for efficient data collection. Hence, development of sample holders from new materials capable of supporting various crystal sizes and shapes may expand the applications of FT‐SFX. Here, a viscous‐media‐based crystal support in a sample holder for FT‐SFX is introduced. Crystal samples were embedded in viscous media, namely gelatin and agarose, which were enclosed in a polyimide film. In the vertically placed sample holder, 10–15%(w/v) viscous gelatin and 1–4%(w/v) agarose gel stably supported crystals between two polyimide films, thereby preventing the crystals from descending owing to gravity. Using this method, FT‐SFX experiments were performed with glucose isomerase and lysozyme embedded in gelatin and agarose, respectively. The room‐temperature crystal structures of glucose isomerase and lysozyme were successfully determined at 1.75 and 1.80 Å resolutions, respectively. The glucose isomerase and lysozyme diffraction analyses were not impeded by excessive background scattering from the viscous media. This method is useful for delivering crystal samples of various sizes and shapes in FT‐SFX experiments. [ABSTRACT FROM AUTHOR]

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 Å resolution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Hydraulic actuation systems have high power-to-weight ratio and durability characteristics, but its the non-backdrivability and high output stiffness of hydraulic prevented it from being actively applied to interactive control systems, especially in robotics. This paper describes a force/torque control strategy to address these interactive hydraulic system control problems, with hydro-elastic actuation, which is a combination of a hydraulic actuator with a spring installed on the output side. This configuration simplifies the hydraulic actuator force/torque control problem into a motion control problem. To achieve high performance, first we introduced a robust internal- loop compensator (RIC) for hydraulic motion control, which has equivalent properties to a disturbance observer (DOB) and applicability in non-linear hydraulic actuator dynamics by decoupling the inner-loop compensator and outer-loop controller. This also minimizes sensor requirements and computation costs versus conventional hydraulic motion controllers. Based on this first strategy, second, we propose link-side motion feedback to compensate for undesirable velocity disturbances from the link side to provide high-accuracy torque control for the HEA system. Finally, we propose cross-parallel connection strategy to HEA spring to achieve high durability and deflection linearity Experimental results with custom-designed hardware showed torque controllability, backdrivability, low output impedance, and robustness in linking motion disturbance in time domain zero-torque and stiffness control experiments, without losing much of the high-power potential. [ABSTRACT FROM AUTHOR]

Exact information about the shape of a lumbar pedicle can increase operation accuracy and safety during computer-aided spinal fusion surgery, which requires extreme caution on the part of the surgeon, due to the complexity and delicacy of the procedure. In this paper, a robust framework for segmenting the lumbar pedicle in computed tomography (CT) images is presented. The framework that has been designed takes a CT image, which includes the lumbar pedicle as input, and provides the segmented lumbar pedicle in the form of 3-D voxel sets. This multistep approach begins with 2-D dynamic thresholding using local optimal thresholds, followed by procedures to recover the spine geometry in a high curvature environment. A subsequent canal reference determination using proposed thinning-based integrated cost is then performed. Based on the obtained segmented vertebra and canal reference, the edge of the spinal pedicle is segmented. This framework has been tested on 84 lumbar vertebrae of 19 patients requiring spinal fusion. It was successfully applied, resulting in an average success rate of 93.22\% and a final mean error of 0.14\,\pm\,0.05 mm. Precision errors were smaller than 1\% for spine pedicle volumes. Intra- and interoperator precision errors were not significantly different. [ABSTRACT FROM AUTHOR]

This paper presents a method for building a probability grid map for autonomous mobile robots with ultrasonic sensors using a data association filter (DAF). The method is based on evaluating the possibility that the acquired sonar data are all reflected by the same object. The DAF is able to associate data points with each other. Data affected by specular reflection are not likely to be associated with the same object, so they are excluded from the data cluster by the DAF, thereby improving the reliability of the data used for the probability grid map. Since the corrupted data are not used to update the probability map, it is possible to build a good quality grid map even in a specular environment. The DAF was applied to the Bayesian and the Orientation probability models, which are typical models used to build grid maps, to verify its effectiveness. Experimental results were also obtained using a mobile robot in a real-world environment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

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., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

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).

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., (© 2022. The Author(s).)

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., (© Keondo Lee et al. 2022.)

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., (© 2021 Wiley-VCH GmbH.)

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.

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.

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.

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.

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., Competing Interests: The authors declare no conflict of interest.

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.

This paper proposes a gravity-based system capable of generating high-resolution pressure for precise cell manipulation or evaluation in a microfluidic channel. While the pressure resolution of conventional pumps for microfluidic applications is usually about hundreds of pascals as the resolution of their feedback sensors, precise cell manipulation at the pascal level cannot be done. The proposed system successfully achieves a resolution of 100 millipascals using water head pressure with an in-phase noise cancelation mechanism. The in-phase mechanism aims to suppress the noises from ambient vibrations to the system. The proposed pressure system is tested with a microfluidic platform for pressure validation. The experimental results show that the in-phase mechanism effectively reduces the pressure turbulence, and the pressure-driven cell movement matches the theoretical simulations. Preliminary experiments on deformability evaluation with red blood cells under incremental pressures of one pascal are successfully performed. Different deformation patterns are observed from cell to cell under precise pressure control.

Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode.

Both polarization sensitive optical coherence tomography (PS-OCT) and second harmonic generation (SHG) microscopy are 3D optical imaging methods providing information related to collagen in the skin. PS-OCT provides birefringence information which is due to the collagen composition of the skin. SHG microscopy visualizes collagen fibers in the skin based on their SHG property. These two modalities have been applied to the same skin pathologies associated with collagen changes, but their relationship has not been examined. In this study, we tried to find the relationship by imaging the same skin samples with both modalities. Various parts of the normal rat skin and burn damaged skin were imaged ex vivo, and their images were analyzed both qualitatively and quantitatively. PS-OCT images were analyzed to obtain tissue birefringence. SHG images were analyzed to obtain collagen orientation indices by applying 2D Fourier transform. The skin samples having higher birefringence values had higher collagen orientation indices, and a linear correlation was found between them. Burn damaged skin showed decreases in both parameters compared to the control skins. This relationship between the bulk and microscopic properties of skin may be useful for further skin studies.

Polarization-sensitive optical coherence tomography (PS-OCT) is a functional OCT providing both structural and birefringent information of the sample, and it has been applied to the studies of various organs having polarization properties. Fiber-based PS-OCT is sensitive to specular reflection from the sample surface, because signal saturation due to the strong specular reflection can make the polarization measurement difficult. We developed a dark-field PS-OCT which can avoid the specular reflection problem. Dark-field PS-OCT was implemented by adapting a hybrid method of Bessel-beam illumination and Gaussian-beam detection, and a PS-OCT method based on passive delay unit (PDU). The new system was characterized in comparison with the conventional Gaussian-beam based method in both polarization components and various samples including the human skin. Dark-field PS-OCT performed as good as the conventional PS-OCT without the specular reflection artifact. Dark-field PS-OCT may be useful in practical situations where the specular reflection is unavoidable.

We report a miniaturized probe-based combined two-photon microscopy (TPM) and optical coherence tomography (OCT) system. This system is to study the colorectal cancer in mouse models by visualizing both cellular and structural information of the colon in 3D with TPM and OCT respectively. The probe consisted of gradient index (GRIN) lenses and a 90° reflecting prism at its distal end for side-viewing, and it was added onto an objective lens-based TPM and OCT system. The probe was 2.2 mm in diameter and 60 mm in length. TPM imaging was performed by raster scanning of the excitation focus at the imaging speed of 15.4 frames/s. OCT imaging was performed by combining the linear sample translation and probe rotation along its axis. This miniaturized probe based dual-modal system was characterized with tissue phantoms containing fluorescent microspheres, and applied to image mouse colonic tissues ex vivo as a demonstration. As OCT and TPM provided structural and cellular information of the tissues respectively, this probe based multi-modal imaging system can be helpful for in vivo studies of preclinical animal models such as mouse colonic tumorigenesis.

Since the first occurrence in 1982, red tides have been observed annually in Korean coastal waters in the form of harmful dinoflagellate Cochlodinium polykrikoides blooms. The distinction in the proposed method for red tide monitoring is the focus on the narrow stripe red tide at an early stage to allow for advanced actions. The distance graph between Head of Narrow Red tide (HNR) and location of the robot have suggested in reference to unknown searching area. With mapping and path planning, then, it can quickly keep tracking out even if the magnitude and direction of current flow was changed. The one-hundred times simulations of different situations were attempted to comparison by box plot both algorithms of speed by reaching the right side of simulation window. Consequently, the red tide tracking algorithm is based on the red tide probability map and the tracking & recovering path planner. Inputs to the algorithm include the measured flow velocities and the detection or non-detection state at each robot location. Furthermore, a USV (Unmanned Surface Vehicle) model is added to evaluate the effectiveness of the algorithm. This approach for red tide monitoring may lead to a breakthrough in the field of environmental surveillance.

Background: An optimized pre-operative planning framework for lumbar spinal fusion was proposed, which augmented a novel functionality of suggesting optimal insertion trajectories and the screw size, considering operational safety and vertebra-screw interface strength, autonomously., Methods: Based on an accurate 3D pedicle model with pre-operative computed tomography (CT) data, the framework begins with safety margin estimation for each potential insertion trajectory, followed by procedures to collect a set of insertion trajectories satisfying the operation safety objective. Among the trajectory candidates, the insertion trajectory, which maximized the insertable depth of a pedicle screw into the vertebral body, was then chosen as optimal, because the insertable depth enhanced the strength of the screw-vertebra interface. The radius of a pedicle screw was chosen as 70% of the pedicle radius., Results: This framework has been tested on 176 spinal pedicles of 20 patients requiring spinal fusion. It was successfully applied, resulting in an average success rate of 100% and a final safety margin of 2.1 ± 0.2 mm. Planning accuracy and usefulness of the proposed surgical planner show significant differences compared with a conventional manual planner., Conclusion: We can expect that the derived conservative safety margin mitigates screw misplacement or pedicle breach, despite potential errors induced during registrations or intraoperative screw insertion., (Copyright © 2012 John Wiley & Sons, Ltd.)