This study sought to describe the impact of statins on individual coronary atherosclerotic plaques.
Although statins reduce the risk of major adverse cardiovascular events, their long-term effects on ...coronary atherosclerosis remain unclear.
We performed a prospective, multinational study consisting of a registry of consecutive patients without history of coronary artery disease who underwent serial coronary computed tomography angiography at an interscan interval of ≥2 years. Atherosclerotic plaques were quantitatively analyzed for percent diameter stenosis (%DS), percent atheroma volume (PAV), plaque composition, and presence of high-risk plaque (HRP), defined by the presence of ≥2 features of low-attenuation plaque, positive arterial remodeling, or spotty calcifications.
Among 1,255 patients (60 ± 9 years of age; 57% men), 1,079 coronary artery lesions were evaluated in statin-naive patients (n = 474), and 2,496 coronary artery lesions were evaluated in statin-taking patients (n = 781). Compared with lesions in statin-naive patients, those in statin-taking patients displayed a slower rate of overall PAV progression (1.76 ± 2.40% per year vs. 2.04 ± 2.37% per year, respectively; p = 0.002) but more rapid progression of calcified PAV (1.27 ± 1.54% per year vs. 0.98 ± 1.27% per year, respectively; p < 0.001). Progression of noncalcified PAV and annual incidence of new HRP features were lower in lesions in statin-taking patients (0.49 ± 2.39% per year vs. 1.06 ± 2.42% per year and 0.9% per year vs. 1.6% per year, respectively; all p < 0.001). The rates of progression to >50% DS were not different (1.0% vs. 1.4%, respectively; p > 0.05). Statins were associated with a 21% reduction in annualized total PAV progression above the median and 35% reduction in HRP development.
Statins were associated with slower progression of overall coronary atherosclerosis volume, with increased plaque calcification and reduction of high-risk plaque features. Statins did not affect the progression of percentage of stenosis severity of coronary artery lesions but induced phenotypic plaque transformation. (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging PARADIGM; NCT02803411).
Owing to their great success in unsupervised tasks, generative adversarial networks (GANs) are widely adopted for supervised (conditional) image-generation tasks such as in-painting. Unfortunately, ...designing an objective function using GANs is not trivial. For supervised tasks, the generator trained only with GAN loss does not yield the corresponding target for the given input because GAN is trained to match the data distribution, not to find the exact answer. Therefore, the loss function of a generator is often formulated by linearly combining supervised loss and GAN loss as similar to multi-task learning, expecting that each loss's weakness is complemented. Contrary to expectation, both losses cause a conflict in practice due to different optimum of each loss, yielding low objective and subjective image qualities. To address this problem, we empirically investigated the conflict caused by using a conventional GAN with pixel-wise losses; we then propose a novel (relativistic) accuracy-aware discriminator. Based on the proposed discriminator, we developed an accuracy-aware GAN (AAGAN) and proved its optimality under an ideal assumption. We then propose a relativistic accuracy-aware GAN (RAAGAN) by considering practical assumptions. Experimental results on supervised tasks demonstrated that the proposed schemes alleviated the competition between losses and outperformed conventional GANs in terms of both objective and subjective qualities.
Concrete structures often fail to perform their original functions due to problems such as deterioration and damage over time. Therefore, various repair materials have been studied to maintain ...deteriorated concrete structures. This study experimentally investigated the mechanical properties of high-early-strength cement-based repair materials for spraying. For spraying, the cement-based materials should have adoptable fluidity and strength: 200 ± 100 mm for flow; 20 MPa at 24 h and 40 MPa at 28 days for compressive strength, and 8 MPa at 28 days for flexural strength. Wollastonite mineral fibers (3-5 wt.%) and styrene-butadiene (SB) latex (5-7 wt.%) were studied to enhance this requirement. Fluidity was evaluated by flow test and measuring the heat of hydration; mechanical properties were evaluated in terms of compressive and flexural strength. The cement-to-silica sand ratio (C:S ratio) was also applied differently to adjust the pot life of polymer cement-based material (1:1 and 1:1.5) as a binder. Because wollastonite mineral fibers and SB latex affect workability, the water-to-binder ratio was regulated to reach the target flow according to the amount of wollastonite mineral fibers and SB latex. Regardless of the C:S ratio, all studied mixtures met the target 28 day compressive strength at 24 h, decreasing in strength with increasing amounts of wollastonite mineral fibers and latex. Flexural strength also fulfilled the target value, and it increased with increasing amounts of wollastonite mineral fibers and latex, unlike compressive strength. The optimal mix proportion of high-early-strength cement-based repair materials constituted 3 wt.% wollastonite mineral fibers and 5 wt.% SB latex as the binder in a C:S ratio of 1:1.5.
An electrical biosensor exploiting a nanostructured semiconductor is a promising technology for the highly sensitive, label‐free detection of biomolecules via a straightforward electronic signal. The ...facile and scalable production of a nanopatterned electrical silicon biosensor by block copolymer (BCP) nanolithography is reported. A cost‐effective and large‐area nanofabrication, based on BCP self‐assembly and single‐step dry etching, is developed for the hexagonal nanohole patterning of thin silicon films. The resultant nanopatterned electrical channel modified with biotin molecules successfully detects the two proteins, streptavidin and avidin, down to nanoscale molarities (≈1 nm). The nanoscale pattern comparable to the Debye screening length and the large surface area of the three‐dimensional silicon nanochannel enable excellent sensitivity and stability. A device simulation confirms that the nanopatterned structure used in this work is effective for biomolecule detection. This approach relying on the scalable self‐assembly principle offers a high‐throughput manufacturing process for clinical lab‐on‐a‐chip diagnoses and relevant biomolecular studies.
A nanopatterned silicon electrical biosensor is fabricated by block copolymer lithography and used for the detection of model proteins down to nanoscale molarities (≈1 nm). The nanoscale patterned silicon electrical channel enables the biosensor to realize excellent sensitivity and stability. A simulation is performed to demonstrate that the nanopatterned structure is effective for biomolecule detection.
Cytokines are proteins secreted by immune cells. They promote cell signal transduction and are involved in cell replication, death, and recovery. Cytokines are immune modulators, but their excessive ...secretion causes uncontrolled inflammation that attacks normal cells. Considering the properties of cytokines, monitoring the secretion of cytokines in vivo is of great value for medical and biological research. In this review, we offer a report on recent studies for cytokine detection, especially studies on aptasensors using aptamers. Aptamers are single strand nucleic acids that form a stable three-dimensional structure and have been receiving attention due to various characteristics such as simple production methods, low molecular weight, and ease of modification while performing a physiological role similar to antibodies.
Gait event detection is essential for controlling an orthosis and assessing the patient's gait. In this study, patients wearing an electromechanical (EM) knee-ankle-foot orthosis (KAFO) with a single ...IMU embedded in the thigh were subjected to gait event detection. The algorithm detected four essential gait events (initial contact (IC), toe off (TO), opposite initial contact (OIC), and opposite toe off (OTO)) and determined important temporal gait parameters such as stance/swing time, symmetry, and single/double limb support. These gait events were evaluated through gait experiments using four force plates on healthy adults and a hemiplegic patient who wore a one-way clutch KAFO and a pneumatic cylinder KAFO. Results showed that the smallest error in gait event detection was found at IC, and the largest error rate was observed at opposite toe off (OTO) with an error rate of -2.8 ± 1.5% in the patient group. Errors in OTO detection resulted in the largest error in determining the single limb support of the patient with an error of 5.0 ± 1.5%. The present study would be beneficial for the real-time continuous monitoring of gait events and temporal gait parameters for persons with an EM KAFO.
High-order graph matching is a feature-matching algorithm that uses geometric information among features. This algorithm is more robust to repetitive patterns or unclear areas than first-order ...matching that uses only feature descriptors. However, the processing speed of high-order matching is very slow because of its high computational complexity. To accelerate its speed, this paper proposes a new parallelization algorithm of high-order matching for GPU execution. The obstacle for parallelization is the write collision caused by multiple threads that must simultaneously update the data at the same memory location. In high-order matching, multiple formulations of the objective function can generate the same solution. By taking advantage of this property, the proposed algorithm replaces the operation causing write collision with another operation eliminating the collision while generating the same solution. The proposed algorithm is tested with GTX 960 and takes 31.3 ms, which is 68 times faster than the execution time with a CPU and approximately three times faster than that with a straightforward parallelization for the same GPU.
DRAM devices require periodic refresh operations to preserve data integrity. Slowing down the refresh rate can reduce the energy consumption; however, it may cause a loss of data stored in the DRAM ...cell. This paper proposes a new memory architecture of soft approximation for deep learning applications, which reduces the refresh energy consumption while maintaining accuracy and high performance. Utilizing the error-tolerant property of deep learning applications, the proposed memory architecture avoids the accuracy drop caused by data loss by flexibly controlling the refresh operation for different bits, depending on their criticality. For data storage, the approximate DRAM architecture reorganizes the data so that these data are sorted according to their bit significance. Critical bits are stored in more frequently refreshed devices while non-critical bits are stored in less frequently refreshed devices. In addition, for further reduction of the DRAM energy consumption, this paper combines hard approximation, which reduces the number of accesses to DRAM, with soft approximation. Simulation results show that the refresh energy consumption is reduced by 69.71%, and the total energy consumption is reduced by 26.0 % for the hybrid memory with a negligible drop in both training and testing phases on state-of-the-art deep networks.
Various kinds of nanostructured materials have been extensively investigated as lithium ion battery electrode materials derived from their numerous advantageous features including enhanced energy and ...power density and cyclability. However, little is known about the microscopic origin of how nanostructures can enhance lithium storage performance. Herein, we identify the microscopic origin of enhanced lithium storage in anatase TiO2 nanostructure and report a reversible and stable route to achieve enhanced lithium storage capacity in anatase TiO2. We designed hollow anatase TiO2 nanostructures composed of interconnected ∼5 nm sized nanocrystals, which can individually reach the theoretical lithium storage limit and maintain a stable capacity during prolonged cycling (i.e., 330 mAh g–1 for the initial cycle and 228 mAh g–1 for the 100th cycle, at 0.1 A g–1). In situ characterization by X-ray diffraction and X-ray absorption spectroscopy shows that enhanced lithium storage into the anatase TiO2 nanocrystal results from the insertion reaction, which expands the crystal lattice during the sequential phase transition (anatase TiO2 → Li0.55TiO2 → LiTiO2). In addition to the pseudocapacitive charge storage of nanostructures, our approach extends the utilization of nanostructured TiO2 for significantly stabilizing excess lithium storage in crystal structures for long-term cycling, which can be readily applied to other lithium storage materials.
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