Publications by authors named "Tan Hung Vo"

Cancer remains a formidable global health challenge, demanding the exploration of innovative treatment modalities with minimized side effects. One promising avenue involves the synergistic integration of targeted photothermal/photodynamic therapy (PTT/PDT), utilizing specially designed functional nanomaterials for precise cancer diagnosis and treatment. This study introduces a composite biomaterial, anti-epidermal growth factor receptor-conjugated manganese core phthalocyanine bismuth (anti-EGFR-MPB), synthesized for precise cancer imaging and treatment.

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A scanning acoustic microscopy (SAM) system is a common non-destructive instrument which is used to evaluate the material quality in scientific and industrial applications. Technically, the tested sample is immersed in water during the scanning process. Therefore, a robot arm is incorporated into the SAM system to transfer the sample for in-line inspection, which makes the system complex and increases time consumption.

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Introduction: The advanced features of plasmonic nanomaterials enable initial high accuracy detection with different therapeutic intervention. Computational simulations could estimate the plasmonic heat generation with a high accuracy and could be reliably compared to experimental results. This proposed combined theoretical-experimental strategy may help researchers to better understand other nanoparticles in terms of plasmonic efficiency and usability for future nano-theranostic research.

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Injectability and self-setting properties are important factors to increase the efficiency of bone regeneration and reconstruction, thereby reducing the invasiveness of hard tissue engineering procedures. In this study, 63S bioactive glass (BG), nano-hydroxyapatite (n-HAp), alumina, titanium dioxide, and methylene bis-acrylamide (MBAM)-mediated polymeric crosslinking composites were prepared for the formulation of an efficient self-setting bone cement. According to the cytocompatibility and physicochemical analyses, all the samples qualified the standard of the bio-composite materials.

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Article Synopsis
  • Photoacoustic (PA) microscopy is a technique used for imaging soft biological tissues by utilizing the contrast from optical absorption and ultrasound resolution, mainly focusing on microvasculature.
  • The challenge in PA imaging arises from strong signals from the skin that obscure the visualization of deeper blood vessels, necessitating the development of better imaging techniques.
  • This research introduces a modified U-Net deep learning model that effectively segments PA images, improving the clarity and resolution of in vivo imaging and demonstrating enhanced performance over previous methods.
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In low-level laser therapy, providing an optimal dosage and proposing a proper diagnosis before dermatological treatment are essential to reduce the side effects and potential dangers. In this article, a smart LED therapy system for automatic facial acne vulgaris diagnosis based on deep learning and Internet of Things application is proposed. The main goals of this study were to (1) develop an LED therapy device with different power densities and LED grid control; (2) propose a deep learning model based on modified ResNet50 and YOLOv2 for an automatic acne diagnosis; and (3) develop a smartphone application for facial photography image capture and LED therapy parameter configuration.

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The biological effects of a light-emitting diode (LED) light therapy device are determined by irradiation parameters, mainly wavelength and power density. However, using a battery to provide power causes a problem in the variation of LED power density during battery discharge. As a result, maintaining a stable LED power density, along with extending battery life and operating time, are the primary concerns in designing a LED light therapy device.

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Here, we report 16S rRNA amplicon sequence data from chicken cecal feces from Vietnam and Thailand. , , and were dominant in cecal feces microbiota.

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It is generally difficult to specify the sources of infection by which domestic animals may acquire pathogens. Through 16S rRNA gene amplicon sequencing, we compared the composition of microbiota in the saliva, vaginal mucus, and feces of pigs, and in swabs of feeder troughs and water dispensers collected from pig farms in Vietnam. The composition of the microbiota differed between samples in each sample group.

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