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30 years associated with Contact Lens-associated Microbe Keratitis in the Referral Medical center within São Paulo, Brazilian.
PURPOSE To develop a deep learning-based Bayesian estimation for MRI reconstruction. METHODS We modeled the MRI reconstruction problem with Bayes's theorem, following the recently proposed PixelCNN++ method. The image reconstruction from incomplete k-space measurement was obtained by maximizing the posterior possibility. A generative network was utilized as the image prior, which was computationally tractable, and the k-space data fidelity was enforced by using an equality constraint. The stochastic backpropagation was utilized to calculate the descent gradient in the process of maximum a posterior, and a projected subgradient method was used to impose the equality constraint. In contrast to the other deep learning reconstruction methods, the proposed one used the likelihood of prior as the training loss and the objective function in reconstruction to improve the image quality. RESULTS The proposed method showed an improved performance in preserving image details and reducing aliasing artifacts, compared with GRAPPA, ℓ 1 -ESPRiT, model-based deep learning architecture for inverse problems (MODL), and variational network (VN), last two were state-of-the-art deep learning reconstruction methods. The proposed method generally achieved more than 3 dB peak signal-to-noise ratio improvement for compressed sensing and parallel imaging reconstructions compared with the other methods. CONCLUSIONS The Bayesian estimation significantly improved the reconstruction performance, compared with the conventional ℓ 1 -sparsity prior in compressed sensing reconstruction tasks. More importantly, the proposed reconstruction framework can be generalized for most MRI reconstruction scenarios. © 2020 International Society for Magnetic Resonance in Medicine.28-year-old previously healthy male sustained a severe traumatic brain injury requiring decompressive craniectomy (DC) and evacuation of subdural hematoma after a motor vehicle collision on 7/29/2018. This article is protected by copyright. All rights reserved.PURPOSE The aim of this study was to demonstrate the feasibility of fluorine-19 (19 F) MRI of the human lungs using octafluorocyclobutane (OFCB, C4 F8 ). This gas has 8 magnetically equivalent fluorine nuclei and relatively long T1 and T2 (~50 ms), which render it suitable as an MRI contrast agent. Previous experiments in small laboratory animals showed that OFCB could be successfully used as an alternative to the gases often used for 19 F MRI (sulfur hexafluoride and perfluoropropane). HOpic order METHODS One male volunteer participated in this study. Immediately before an MRI scan, the volunteer inhaled the gas mixture-80% OFCB with 20% oxygen-and held his breath. Experiments were performed on a 0.5T whole-body MR scanner with a customized transmit-receive coil tuned at 19 F frequency. Fast spin echo in 2D and 3D modes was used for image acquisition. 2D images were obtained with in-plane resolution of 10 × 10 mm2 without slice selection. 3D images were obtained with the voxel size of 10 × 10 × 30 mm2 . Breath-hold duration was 20 s for 2D and 40 s for 3D imaging, respectively. RESULTS Anatomically consistent 19 F MR images of the human lungs were obtained with SNR around 50 in 2D mode and 20 in 3D mode. 3D volumetric images of the lungs were reconstructed and provided physiologically reasonable volume estimates. CONCLUSION The application of OFCB enables informative 19 F lung imaging even at low magnetic field strengths. The OFCB gas shows promise as an inhalable contrast agent for fluorine lung MRI and has a potential for clinical translation. © 2020 International Society for Magnetic Resonance in Medicine.OBJECTIVE The aim of this clinical trial is to evaluate the levels of Neuregulin-4 (Nrg4), Erb-b2 receptor tyrosine kinase 4 (ErbB4), interleukin (IL)-6, IL-10, nitric oxide synthase (NOS)-2 and arginase (Arg)-1 in periodontal health and disease. MATERIALS AND METHODS This study includes systemically healthy 20 periodontally healthy (H), 20 gingivitis (G), 20 stage II periodontitis (P1), and 20 stage III periodontitis (P2) subjects. Periodontal clinical measurements and samples of gingival crevicular fluid (GCF) and serum were obtained at baseline and 4 weeks after nonsurgical periodontal treatment (NSPT). Enzyme-linked immunosorbent assay (ELISA) was used to determine ErbB4, Nrg4, IL-6, IL-10, NOS2 and Arg1 levels in all samples. RESULTS GCF ErbB4 and Nrg4 total amounts and IL-6/IL-10 ratio were significantly higher in G, P1 and P2 groups than H group. Serum NOS2 levels were significantly lower, whereas serum Arg1 levels were higher in H group than the others. The GCF levels of ErbB4 and Nrg4 were significantly decreased after NSPT in G, P1 and P2 groups. Additionally, the GCF levels of ErbB4 and Nrg4 were positively correlated with all clinical parameters and IL-6/IL-10 ratio. CONCLUSIONS Nrg4 and its receptor ErbB4 might have crucial roles in the pathogenesis of periodontal disease. These results should be verified with future prospective studies to further clarify the exact role of those biomarkers. This article is protected by copyright. All rights reserved.The cell regulates complicated signaling and metabolism through strict transcriptional, translational, and post-translational regulation. Considerable advances have been made for monitoring transcription and translation over the past few decades. Until recently, there have not been generalizable methods for assessing the effects of post-translational regulation on enzymatic activity. Activity-based sensing (ABS) has emerged as a powerful approach for monitoring small-molecule and enzymatic activities within living systems. Initial examples of ABS were applied for measuring general enzymatic activity; however, a recent focus has been on increasing selectivity to monitor a single enzyme or isoform. The highest degree of selectivity is required for differentiating between isoforms, where the targets display significant structural similarities as a result of a gene duplication or alternative splicing. This review highlights key examples of small-molecule, isoform-selective probes with a focus on the relevance of isoform differentiation, design strategies to achieve selectivity, and applications in basic biology or in the clinic.
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