72 research outputs found

    CSA: Thực hành nông nghiệp thông minh với khí hậu ở Việt Nam

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    During the last five years, Vietnam has been one of the countries most affected by climate change. Severe typhoons, flooding, cold spells, salinity intrusion, and drought have affected agriculture production across the country, from upland to lowland regions. Fortunately for Vietnam, continuous work in developing climate-smart agriculture has been occurring in research organizations and among innovative farmers and entrepreneurs. Application of various CSA practices and technologies to adapt to the impact of climate change in agriculture production have been expanding. However, there is a need to accelerate the scaling process of these practices and technologies in order to ensure growth of agriculture production and food security, increase income of farmers, make farming climate resilient, and contribute to global climate change mitigation. This book aims to provide basic information to researchers, managers, and technicians and extentionists at different levels on what CSA practices and technologies can be up scaled in different locations in Vietnam

    Risk Factors of Streptococcus suis Infection in Vietnam. A Case-Control Study

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    Background: Streptococcus suis infection, an emerging zoonosis, is an increasing public health problem across South East Asia and the most common cause of acute bacterial meningitis in adults in Vietnam. Little is known of the risk factors underlying the disease. Methods and Findings: A case-control study with appropriate hospital and matched community controls for each patient was conducted between May 2006 and June 2009. Potential risk factors were assessed using a standardized questionnaire and investigation of throat and rectal S. suis carriage in cases, controls and their pigs, using real-time PCR and culture of swab samples. We recruited 101 cases of S. suis meningitis, 303 hospital controls and 300 community controls. By multivariate analysis, risk factors identified for S. suis infection as compared to either control group included eating "high risk" dishes, including such dishes as undercooked pig blood and pig intestine (OR1 = 2.22; 95% CI = [1.15-4.28] and OR2 = 4.44; 95% CI = [2.15-9.15]), occupations related to pigs (OR1 = 3.84; 95% CI = [1.32-11.11] and OR2 = 5.52; 95% CI = [1.49-20.39]), and exposures to pigs or pork in the presence of skin injuries (OR1 = 7.48; 95% CI = [1.97-28.44] and OR2 = 15.96; 95% CI = [2.97-85.72]). S. suis specific DNA was detected in rectal and throat swabs of 6 patients and was cultured from 2 rectal samples, but was not detected in such samples of 1522 healthy individuals or patients without S. suis infection. Conclusions: This case control study, the largest prospective epidemiological assessment of this disease, has identified the most important risk factors associated with S. suis bacterial meningitis to be eating 'high risk' dishes popular in parts of Asia, occupational exposure to pigs and pig products, and preparation of pork in the presence of skin lesions. These risk factors can be addressed in public health campaigns aimed at preventing S. suis infectio

    Adjunctive dexamethasone for the treatment of HIV-uninfected adults with tuberculous meningitis stratified by Leukotriene A4 hydrolase genotype (LAST ACT): Study protocol for a randomised double blind placebo controlled non-inferiority trial [version 1; referees: 2 approved]

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    Background: Tuberculosis kills more people than any other bacterial infection worldwide. In tuberculous meningitis (TBM), a common functional promoter variant (C/T transition) in the gene encoding leukotriene A4 hydrolase (LTA4H), predicts pre-treatment inflammatory phenotype and response to dexamethasone in HIV-uninfected individuals. The primary aim of this study is to determine whether LTA4H genotype determines benefit or harm from adjunctive dexamethasone in HIV-uninfected Vietnamese adults with TBM. The secondary aim is to investigate alternative management strategies in individuals who develop drug induced liver injury (DILI) that will enable the safe continuation of rifampicin and isoniazid therapy.  Methods: We will perform a parallel group, randomised (1:1), double blind, placebo-controlled,  multi-centre Phase III non-inferiority trial, comparing dexamethasone versus placebo for 6-8 weeks in addition to standard anti-tuberculosis treatment in HIV-uninfected patients with TBM stratified by LTA4H genotype. The primary endpoint will be death or new neurological event. The trial will enrol approximately 720 HIV-uninfected adults with a clinical diagnosis of TBM, from two hospitals in Ho Chi Minh City, Vietnam. 640 participants with CC or CT- LTA4H genotype will be randomised to either dexamethasone or placebo, and the remaining TT- genotype participants will be treated with standard-of-care dexamethasone. We will also perform a randomised comparison of three management strategies for anti-tuberculosis DILI. An identical ancillary study will also be perfomed in the linked randomised controlled trial of dexamethasone in HIV-infected adults with TBM (ACT HIV).  Discussion: Previous data have shown that LTA4H genotype may be a critical determinant of inflammation and consequently of adjunctive anti-inflammatory treatment response in TBM. We will stratify dexamethasone therapy according to LTA4H genotype in HIV-uninfected adults, which may indicate a role for targeted anti-inflammatory therapy according to variation in LTA4H C/T transition. A comparison of DILI management strategies may allow the safe continuation of rifampicin and isoniazid

    Prognostic models for 9 month mortality in tuberculous meningitis

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    Background: Tuberculous meningitis (TBM) is the most severe form of extra-pulmonary tuberculosis. We developed and validated prognostic models for 9-month mortality in HIV-uninfected and HIV-infected adults with TBM. Methods: We included 1699 subjects from four randomized clinical trials and one prospective observational study conducted at two major referral hospitals in Southern Vietnam from 2001-2015. Modelling was based on multivariable Cox proportional hazards regression. The final prognostic models were validated internally and temporally, and displayed using nomograms and a web-based app (https://thaole.shinyapps.io/tbmapp/). Results: A total of 951 HIV-uninfected and 748 HIV-infected subjects with TBM were included, of whom 219/951 (23.0%) and 384/748 (51.3%) died during 9-month follow-up. Common predictors for increased mortality in both populations were higher Medical Research Council (MRC) disease severity grade and lower cerebrospinal fluid lymphocyte cells count. In HIV-uninfected subjects, older age, previous tuberculosis, not receiving adjunctive dexamethasone, and focal neurological signs were additional risk factors; in HIV-infected subjects, lower weight, lower peripheral blood CD4 cell count, and abnormal plasma sodium were additional risk factors. The areas under the receiver operating characteristic curves (AUCs) for the final prognostic models were 0.77 (HIV-uninfected population) and 0.78 (HIV-infected population), demonstrating markedly better discrimination than the MRC grade (AUC 0.66 and 0.70) or the Glasgow Coma Score (AUC 0.68 and 0.71) alone. Conclusions: The developed models showed good performance and could be used in clinical practice to assist doctors in identifying TBM patients at high risk of death and at increased need of supportive care.This work was supported by the Academy of Medical Sciences and the Health Foundation (Clinician Scientist Fellowship to M. E. T.), the National Institute of Health Research Cambridge Biomedical Research Centre (M. E. T), and a Wellcome Trust Intermediate Fellowship (grant number WT097147MA) to J.D

    Ventilator-associated respiratory infection in a resource-restricted setting: impact and etiology.

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    BACKGROUND: Ventilator-associated respiratory infection (VARI) is a significant problem in resource-restricted intensive care units (ICUs), but differences in casemix and etiology means VARI in resource-restricted ICUs may be different from that found in resource-rich units. Data from these settings are vital to plan preventative interventions and assess their cost-effectiveness, but few are available. METHODS: We conducted a prospective observational study in four Vietnamese ICUs to assess the incidence and impact of VARI. Patients ≥ 16 years old and expected to be mechanically ventilated > 48 h were enrolled in the study and followed daily for 28 days following ICU admission. RESULTS: Four hundred fifty eligible patients were enrolled over 24 months, and after exclusions, 374 patients' data were analyzed. A total of 92/374 cases of VARI (21.7/1000 ventilator days) were diagnosed; 37 (9.9%) of these met ventilator-associated pneumonia (VAP) criteria (8.7/1000 ventilator days). Patients with any VARI, VAP, or VARI without VAP experienced increased hospital and ICU stay, ICU cost, and antibiotic use (p < 0.01 for all). This was also true for all VARI (p < 0.01 for all) with/without tetanus. There was no increased risk of in-hospital death in patients with VARI compared to those without (VAP HR 1.58, 95% CI 0.75-3.33, p = 0.23; VARI without VAP HR 0.40, 95% CI 0.14-1.17, p = 0.09). In patients with positive endotracheal aspirate cultures, most VARI was caused by Gram-negative organisms; the most frequent were Acinetobacter baumannii (32/73, 43.8%) Klebsiella pneumoniae (26/73, 35.6%), and Pseudomonas aeruginosa (24/73, 32.9%). 40/68 (58.8%) patients with positive cultures for these had carbapenem-resistant isolates. Patients with carbapenem-resistant VARI had significantly greater ICU costs than patients with carbapenem-susceptible isolates (6053 USD (IQR 3806-7824) vs 3131 USD (IQR 2108-7551), p = 0.04) and after correction for adequacy of initial antibiotics and APACHE II score, showed a trend towards increased risk of in-hospital death (HR 2.82, 95% CI 0.75-6.75, p = 0.15). CONCLUSIONS: VARI in a resource-restricted setting has limited impact on mortality, but shows significant association with increased patient costs, length of stay, and antibiotic use, particularly when caused by carbapenem-resistant bacteria. Evidence-based interventions to reduce VARI in these settings are urgently needed

    Finishing the euchromatic sequence of the human genome

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    The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

    Integrate deep neural network and support vector machine to improve the quality of voice processing in Internet of Things devices

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    Along with the development of science and technology, especially internet of things (IOT), IOT-related products increasingly contribute to improving people’s life. Among those products, it is impossible not to mention smarts city, internet of Vehicle devices and especially smart home, which are usually voice controlled. Therefore, voice processing technology is also in need of improvement. The article mainly focuses on processing human voice independently of text. In particular, Convolutional network (CNN) and Support Vector Machine (SVM) will be integrated to create Feature Building Machine. SVMs are often used in voice and image classification, which accordingly is a critical and swift data sorter. The article analyzes the advantages of the combination Deep Neural Network (DNN) and SVMs in voice recognition and is the foundation to develop devices for smart home. The experimental results, which was used in the standard Voxceleb database, demonstrate the superiority in sound recognition compared to traditional i-vector methods or other CNN methods
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