8 research outputs found

    Complete genome characterization of two wild-type measles viruses from Vietnamese infants during the 2014 outbreak

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    A large measles virus outbreak occurred across Vietnam in 2014. We identified and obtained complete measles virus genomes in stool samples collected from two diarrheal pediatric patients in Dong Thap Province. These are the first complete genome sequences of circulating measles viruses in Vietnam during the 2014 measles outbreak

    Genome sequences of a novel Vietnamese bat bunyavirus

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    To document the viral zoonotic risks in Vietnam, fecal samples were systematically collected from a number of mammals in southern Vietnam and subjected to agnostic deep sequencing. We describe here novel Vietnamese bunyavirus sequences detected in bat feces. The complete L and S segments from 14 viruses were determined

    Nông nghiệp ứng phó với biến đổi khí hậu - Tài liệu dùng cho cán bộ địa phương các cấp của Việt Nam

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    Climate smart agriculture concepts and principles must be simplified for local government officials and other technical officer to be able to operationalize key elements into local development programs in Vietnam. Climate smart agriculture needs to be simplified and often demystified in order to enhance its wider up take at regional and local levels. The brochure is written in Vietnamese for the benefit local partners and technical persons who speak and read Vietnamese language only

    Biến đổi khí hậu và ảnh hưởng của biến đổi khí hậu tới nông nghiệp - Tài liệu dùng cho cán bộ địa phương các cấp của Việt Nam

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    Understanding the impacts of climate change on agriculture, associated landscapes and natural resources in general is crucial if local development efforts are to be tailored towards addressing the impacts of climate change. Simplification of scientific concepts can help local planners at different level to introduce and then mainstream strategies that have factored in the impacts from climate change. The brochure is written in Vietnamese for the benefit local partners and technical persons who speak and read Vietnamese language only

    Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models.

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    Multiphase CT scanning of the liver is performed for several clinical applications; however, radiation exposure from CT scanning poses a nontrivial cancer risk to the patients. The radiation dose may be reduced by determining the scan range of the subsequent scans by the location of the target of interest in the first scan phase. The purpose of this study is to present and assess an automatic method for determining the scan range for multiphase CT scans. Our strategy is to first apply a CNN-based method for detecting the liver in 2D slices, and to use a liver range search algorithm for detecting the liver range in the scout volume. The target liver scan range for subsequent scans can be obtained by adding safety margins achieved from Gaussian liver motion models to the scan range determined from the scout. Experiments were performed on 657 multiphase CT volumes obtained from multiple hospitals. The experiment shows that the proposed liver detection method can detect the liver in 223 out of a total of 224 3D volumes on average within one second, with mean intersection of union, wall distance and centroid distance of 85.5%, 5.7 mm and 9.7 mm, respectively. In addition, the performance of the proposed liver detection method is comparable to the best of the state-of-the-art 3D liver detectors in the liver detection accuracy while it requires less processing time. Furthermore, we apply the liver scan range generation method on the liver CT images acquired from radiofrequency ablation and Y-90 transarterial radioembolization (selective internal radiation therapy) interventions of 46 patients from two hospitals. The result shows that the automatic scan range generation can significantly reduce the effective radiation dose by an average of 14.5% (2.56 mSv) compared to manual performance by the radiographer from Y-90 transarterial radioembolization, while no statistically significant difference in performance was found with the CT images from intra RFA intervention (p = 0.81). Finally, three radiologists assess both the original and the range-reduced images for evaluating the effect of the range reduction method on their clinical decisions. We conclude that the automatic liver scan range generation method is able to reduce excess radiation compared to the manual performance with a high accuracy and without penalizing the clinical decision

    Identification and characterization of Coronaviridae genomes from Vietnamese bats and rats based on conserved protein domains

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    The Coronaviridae family of viruses encompasses a group of pathogens with a zoonotic potential as observed from previous outbreaks of the severe acute respiratory syndrome coronavirus and Middle East respiratory syndrome coronavirus. Accordingly, it seems important to identify and document the coronaviruses in animal reservoirs, many of which are uncharacterized and potentially missed by more standard diagnostic assays. A combination of sensitive deep sequencing technology and computational algorithms is essential for virus surveillance, especially for characterizing novel- or distantly related virus strains. Here, we explore the use of profile Hidden Markov Model-defined Pfam protein domains (Pfam domains) encoded by new sequences as a Coronaviridae sequence classification tool. The encoded domains are used first in a triage to identify potential Coronaviridae sequences and then processed using a Random Forest method to classify the sequences to the Coronaviridae genus level. The application of this algorithm on Coronaviridae genomes assembled from agnostic deep sequencing data from surveillance of bats and rats in Dong Thap province (Vietnam) identified thirty-four Alphacoronavirus and eleven Betacoronavirus genomes. This collection of bat and rat coronaviruses genomes provided essential information on the local diversity of coronaviruses and substantially expanded the number of coronavirus full genomes available from bat and rats and may facilitate further molecular studies on this group of viruses
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