Publications by authors named "Eunseo Cho"

The aim of this study is to describe the general features and eco-friendly biosynthesis of silver nanoparticles (AgNPs) from the marine bacterium F202Z8. To the best of our knowledge, no previous study has reported the biosynthesis of AgNPs using this strain. The formation of AgNPs using F202Z8 was synthesized intracellularly without the addition of any disturbing factors, such as antibiotics, nutrient stress, or electron donors.

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A Gram-negative, pale yellow-pigmented, non-flagellated, motile, rod-shaped and aerobic bacterium, designated strain PG104, was isolated from red algae sp. collected from the coastal area of Pohang, Republic of Korea. Growth of strain PG104 was observed at 15-35 °C (optimum, 30 °C), pH 6.

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Article Synopsis
  • SUPPORT is a self-supervised learning method designed to effectively remove Poisson-Gaussian noise from voltage imaging data by leveraging the spatial and temporal relationships between pixel values.
  • The method utilizes a convolutional neural network that accounts for spatiotemporal dependencies, allowing it to denoise images even when adjacent frames lack useful predictive information.
  • Experimental results demonstrate that SUPPORT not only accurately denoises voltage imaging data but also preserves the essential dynamics of the imaged scene.
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As a vertebrate model animal, larval zebrafish are widely used in neuroscience and provide a unique opportunity to monitor whole-brain activity at the cellular resolution. Here, we provide an optimized protocol for performing whole-brain imaging of larval zebrafish using three-dimensional fluorescence microscopy, including sample preparation and immobilization, sample embedding, image acquisition, and visualization after imaging. The current protocol enables in vivo imaging of the structure and neuronal activity of a larval zebrafish brain at a cellular resolution for over 1 h using confocal microscopy and custom-designed fluorescence microscopy.

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Three-dimensional fluorescence microscopy has an intrinsic performance limit set by the number of photons that can be collected from the sample in a given time interval. Here, we extend our earlier work - a recursive light propagation network (RLP-Net) - which is a computational microscopy technique that overcomes such limitations through virtual refocusing that enables volume reconstruction from two adjacent 2-D wide-field fluorescence images. RLP-Net employs a recursive inference scheme in which the network progressively predicts the subsequent planes along the axial direction.

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Exciton-polaritons (EPs) can be formed in transition metal dichalcogenide (TMD) multilayers sustaining optical resonance modes without any external cavity. The self-hybridized EP modes are expected to depend on the TMD thickness, which directly determines the resonance wavelength. Exfoliated WS flakes were prepared on SiO/Si substrates and template-stripped ultraflat Au layers, and the thickness dependence of their EP modes was compared.

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Background: Previously, we found that the water extract of Artermisia scoparia Waldst. & Kit suppressed the cytokine production of lipopolysaccharide (LPS)-stimulated macrophages and alleviated carrageenan-induced acute inflammation in mice. Artemisia contains various sesquiterpene lactones and most of them exert immunomodulatory activity.

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We report the development of deep decomposition and deconvolution microscopy (3DM), a computational microscopy method for the volumetric imaging of neural activity. 3DM overcomes the major challenge of deconvolution microscopy, the ill-posed inverse problem. We take advantage of the temporal sparsity of neural activity to reformulate and solve the inverse problem using two neural networks which perform sparse decomposition and deconvolution.

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A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

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Our aims for this study were to investigate the relationship between diffusion weighted image (DWI) parameters of brain metastases (BMs) and biological markers of breast cancer, and moreover, to assess whether DWI parameters accurately predict patient outcomes. DWI data for 34 patients with BMs from breast cancer were retrospectively reviewed. Apparent diffusion coefficient (ADC) histogram parameters were calculated from all measurable BMs.

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