Though over 30 years old, 3D printing has seen an explosion of interest in recent years as technology has become sufficiently advanced and affordable, enabling widespread usage, and investigation of the technique as a method of manufacture. However, the materials commonly used for printing applications frequently suffer from poor mechanical properties and are only suitable for prototyping and non-load-bearing objects. We report a stable, tough resin formulation which incorporates spiroacetal molecules into the polymer backbone and displays widely varying and tunable mechanical properties. We characterize the system via (photo-)DSC, rheology, and tensile testing; further, we detail a comprehensive heat treatment investigation to optimize material performance and elucidate the structure-property relationships present in the printed and non-printed semi-crystalline photopolymer. Annealing the material at 40 8C for 120 hours produced a tough thiol-ene with a homogenous crystal structure. Printed samples exhibited comparable morphology their cast analogues, but suffered from reduced tensile properties as a result of interlayer adhesion. V C 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018, 135, 46259.

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Rationale: Inflammation plays a pivotal role in the pathogenesis of the acute coronary syndrome. Detecting plaques with high inflammatory activity and specifically treating those lesions can be crucial to prevent life-threatening cardiovascular events. Methods: Here, we developed a macrophage mannose receptor (MMR)-targeted theranostic nanodrug (mannose-polyethylene glycol-glycol chitosan-deoxycholic acid-cyanine 7-lobeglitazone; MMR-Lobe-Cy) designed to identify inflammatory activity as well as to deliver peroxisome proliferator-activated gamma (PPARγ) agonist, lobeglitazone, specifically to high-risk plaques based on the high mannose receptor specificity. The MMR-Lobe-Cy was intravenously injected into balloon-injured atheromatous rabbits and serial in vivo optical coherence tomography (OCT)-near-infrared fluorescence (NIRF) structural-molecular imaging was performed. Results: One week after MMR-Lobe-Cy administration, the inflammatory NIRF signals in the plaques notably decreased compared to the baseline whereas the signals in saline controls even increased over time. In accordance with in vivo imaging findings, ex vivo NIRF signals on fluorescence reflectance imaging (FRI) and plaque inflammation by immunostainings significantly decreased compared to oral lobeglitazone group or saline controls. The anti-inflammatory effect of MMR-Lobe-Cy was mediated by inhibition of TLR4/NF-κB pathway. Furthermore, acute resolution of inflammation altered the inflamed plaque into a stable phenotype with less macrophages and collagen-rich matrix. Conclusion: Macrophage targeted PPARγ activator labeled with NIRF rapidly stabilized the inflamed plaques in coronary sized artery, which could be quantitatively assessed using intravascular OCT-NIRF imaging. This novel theranostic approach provides a promising theranostic strategy for high-risk coronary plaques.

The purpose of this study was to develop and evaluate a mobile health application (Self-Management mobile Personal Health Record: "SmPHR") to ensure the interoperability of various personal health devices (PHDs) and electronic medical record systems (EMRs) for continuous self-management of chronic disease patients. The SmPHR was developed for Android 4.0.3, and implemented according to the optimized standard protocol for each interface of healthcare services adopted by the Continua Health Alliance (CHA). That is, the Personal Area Network (PAN) interface between the application and PHD implements ISO/IEEE 11073-20,601, 10,404, 10,407, 10,415, 10,417, and Bluetooth Health Device Profile (HDP), and EMRs with a wide area network (WAN) interface implement HL7 V2.6; the Health Record Network (HRN) interface implements Continuity of Care Document (CCD) and Continuity of Care Record (CCR). Also, for SmPHR, we evaluated the transmission error rate between the interface using four PHDs and personal health record systems (PHRs) from previous research, with 611 users and elderly people after receiving institutional review board (IRB) approval. In the evaluation, the PAN interface showed 15 (2.4 %) errors, and the WAN and HRN interface showed 13 (2.1 %) errors in a total of 611 transmission attempts. Also, we received opinions regarding SmPHR from 15 healthcare professionals who took part in the clinical trial. Thus, SmPHR can be provided as an interconnected PHR mobile health service to patients, allowing 'plug and play' of PHDs and EMRs through various standard protocols.

While high-speed intracoronary optical coherence tomography (OCT) provides three-dimensional (3D) visualization of coronary arteries , imaging speeds remain insufficient to avoid motion artifacts induced by heartbeat, limiting the clinical utility of OCT. In this paper, we demonstrate development of a high-speed intracoronary OCT system (frame rate: 500 frames/s, pullback speed: 100 mm/s) along with prospective electrocardiogram (ECG) triggering technology, which enabled volumetric imaging of long coronary segments within a single cardiac cycle (70 mm pullback in 0.7 s) with minimal cardiac motion artifact. This technology permitted detailed visualization of 3D architecture of the coronary arterial wall of a swine and fine structure of the implanted stent.

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In order to do requirement-based testing of embedded system, we must have correct requirement specifications. But, natural language requirements of a client have ambiguity, inaccuracy, and inconsistency. To solve these problems, natural language requirements are modeled with modeling language such as UML and Simulink. During a modeling phase, the requirements are rearranged and retranslated in use-case. These activities are disadvantages of modeling. In this paper, we propose the technique, which is how to model a embedded system requirement into a model without rearranging and retranslating. This technique 1) represent a embedded system requirement with graphical language, and 2) model a requirement into a model. Because this technique only describes "what-to-do" of the requirement, this technique is useful to not only the low-level requirements but also the high-level requirements. We show some example systems modeled by REED, which has adopted this technique.

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