Publications by authors named "Le Thanh Dat"

Background: Atherosclerotic calcification is a complex pathological process associated with an increased risk of cardiovascular events. Despite extensive research, this disorder has no effective therapeutic strategies. In this study, we evaluated the therapeutic potential of silencing Sort (sortilin) expression in vivo using antisense oligonucleotide (ASO-Sort1) to reduce the development of atherosclerosis and associated calcification.

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Here, we report a rare example of an Fe-based MOF capable of accommodating K ions electrochemically within its layered framework, achieving low polarization, high capacity utilization (∼0.8 electrons exchanged per Fe), and stable cycling performance. Mössbauer spectroscopy and XRD analyses revealed that the observed electrochemical storage arises from the Fe/Fe redox couple with polyphasic transformations.

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Li substitution and its impact on the structures and ion transport of NaLiInCl polymorphs, synthesized ball-milling and further annealing, were investigated. Despite a solubility limit of = 0.6, Li incorporation seems to form a connected Li network to enhance the ionic conductivity of the resulting materials.

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This paper presents the molecular design of a rose-bengal-containing functional polymer for the encapsulation of carbon nanohorns (CNHs). The polymer chain consists of hydrophilic monomers and dangling oxirane moieties that tether the rose bengal units. It exhibits high biocompatibility with CNHs and excellent coating ability, resulting in a carbon-based nanoconjugate with a core-shell nanostructure.

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Objectives: This study describes the clinical and paraclinical features, antibiotic resistance levels, and treatment outcomes of septicemia acquired in the Vietnamese community.

Methods: A cross-sectional descriptive study was conducted on 102 patients with community-acquired sepsis caused by from July 2018 to July 2023.

Results: -induced community sepsis had a septic shock rate of 13.

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Nuclear medicine imaging (NMI) is essential for the diagnosis and sensing of various diseases; however, challenges persist regarding image quality and accessibility during NMI-based treatment. This paper reviews the use of deep learning methods for generating synthetic nuclear medicine images, aimed at improving the interpretability and utility of nuclear medicine protocols. We discuss advanced image generation algorithms designed to recover details from low-dose scans, uncover information hidden by specific radiopharmaceutical properties, and enhance the sensing of physiological processes.

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Polarization-sensitive optical coherence tomography (PS-OCT) measures the polarization state of backscattered light from tissues and provides valuable insights into the birefringence properties of biological tissues. Contrastive unpaired translation (CUT) was used in this study to generate a synthetic PS-OCT image from a single OCT image. The challenges related to extensive data requirements relying on labeled datasets using only pixel-wise correlations that make it difficult to efficiently regenerate the periodic patterns observed in PS-OCT images were addressed.

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In this study, we developed an endoscopic hyperspectral imaging (eHSI) system and evaluated its performance in analyzing tissues within tissue phantoms and orthotopic mouse pancreatic tumor models. Our custom-built eHSI system incorporated a liquid crystal tunable filter. To assess its tissue discrimination capabilities, we acquired images of tissue phantoms, distinguishing between fat and muscle regions.

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Article Synopsis
  • Acoustic-resolution photoacoustic microscopy (AR-PAM) provides deep visualization of biological tissues with good contrast, but its resolution and sensitivity are typically lower than that of optical-resolution PAM (OR-PAM).
  • A new computational method using two generative adversarial networks (GANs) has been developed to enhance the resolution and sensitivity of AR-PAM images while maintaining their depth imaging capabilities.
  • Testing on both phantom models and live mouse ear tissues showed that these GANs effectively improved image quality even without exact reference data for deep tissues.
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Atherosclerosis, the leading cause of death, is a vascular disease of chronic inflammation. We recently showed that angiopoietin-like 4 (ANGPTL4) promotes cardiac repair by suppressing pathological inflammation. Given the fundamental contribution of inflammation to atherosclerosis, we assessed the role of ANGPTL4 in the development of atherosclerosis and determined whether ANGPTL4 regulates atherosclerotic plaque stability.

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Background: Activated macrophages contribute to the pathogenesis of vascular disease. Vein graft failure is a major clinical problem with limited therapeutic options. PCSK9 (proprotein convertase subtilisin/kexin 9) increases low-density lipoprotein (LDL)-cholesterol levels via LDL receptor (LDLR) degradation.

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Photoacoustic microscopy has received great attention due to the benefits of the optical resolution contrast as well as its superior spatial resolution and relatively deep depth. Like other imaging modalities, photoacoustic images suffer from noise, and filtering techniques are required to remove them. To overcome the noise, we proposed a combination of filters, including an adaptive median filter, an effective filter for impulsive noise, and a nonlocal means filter, an effective filter for background noise, for noise removal and image quality enhancement.

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Mitral regurgitation (MR) is a major complication of the percutaneous mitral valvuloplasty (PMV). Despite high technical expertise and cumulative experience with the procedure, the incidence rate of severe MR has not decreased. Although some of MR can be anticipated by echocardiographic analysis; leaflet tearing, which leads to the most dreaded type of MR, remains unpredictable.

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