| 1. |
- Tran, Ngoc Hieu, et al.
(författare)
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Genetic profiling of Vietnamese population from large-scale genomic analysis of non-invasive prenatal testing data
- 2020
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- The under-representation of several ethnic groups in existing genetic databases and studies have undermined our understanding of the genetic variations and associated traits or diseases in many populations. Cost and technology limitations remain the challenges in performing large-scale genome sequencing projects in many developing countries, including Vietnam. As one of the most rapidly adopted genetic tests, non-invasive prenatal testing (NIPT) data offers an alternative untapped resource for genetic studies. Here we performed a large-scale genomic analysis of 2683 pregnant Vietnamese women using their NIPT data and identified a comprehensive set of 8,054,515 single-nucleotide polymorphisms, among which 8.2% were new to the Vietnamese population. Our study also revealed 24,487 disease-associated genetic variants and their allele frequency distribution, especially 5 pathogenic variants for prevalent genetic disorders in Vietnam. We also observed major discrepancies in the allele frequency distribution of disease-associated genetic variants between the Vietnamese and other populations, thus highlighting a need for genome-wide association studies dedicated to the Vietnamese population. The resulted database of Vietnamese genetic variants, their allele frequency distribution, and their associated diseases presents a valuable resource for future genetic studies.
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| 2. |
- Pham, Thi Anh Mai, et al.
(författare)
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Evaluation of screening algorithms to detect rectal colonization with carbapenemase-producing Enterobacterales in a resource-limited setting
- 2024
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Ingår i: JAC - Antimicrobial Resistance. - : OXFORD UNIV PRESS. - 2632-1823. ; 6:3
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To improve and rationalize the detection of carbapenemase-producing Enterobacterales (CPE) in rectal swabs in a high-prevalence and resource-constrained setting, addressing surveillance challenges typically encountered in laboratories with limited resources.Methods A point prevalence survey (PPS) was conducted on 15 August 2022, in a provincial children's hospital in northern Vietnam. Rectal swab samples of all admitted children were collected and plated on a selective medium for carbapenem-resistant Enterobacterales (CRE). Species identification and antimicrobial susceptibility testing (AST) were performed by MALDI-TOF, and VITEK2 XL and interpreted according to CLSI breakpoints (2022). Carbapenemases were detected by the carbapenem inactivation method (CIM) and quantitative real-time PCR (qRT-PCR).Results Rectal swab samples were obtained from 376 patients. Of 178 isolates growing on the CRE screening agar, 140 isolates were confirmed as Enterobacterales of which 118 (84.3%) isolates were resistant to meropenem and/or ertapenem. CIM and PCR showed that 90/118 (76.3%) were carbapenemase producers. Overall, 83/367 (22.6%) were colonized by CPE. Klebsiella pneumoniae, Escherichia coli and Enterobacter cloacae complex were the most common CPE detected, with NDM as the predominant carbapenemase (78/90; 86.7%). Phenotypic resistance to meropenem was the best predictor of CPE production (sensitivity 85.6%, specificity 100%) compared with ertapenem resistance (95.6% sensitivity, 36% specificity). CIM was 100% concordant with PCR in detecting carbapenemases.Conclusions These findings underscore the effectiveness of meropenem resistance as a robust indicator of the production of carbapenemases and the reliability of the CIM method to detect such carbapenemases in resource-limited settings where the performance of molecular methods is not possible.
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| 3. |
- Nguyen, Thi Ngoc Phuong, 1993, et al.
(författare)
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Individual-, social- and policy- factors associated with smoking cessation among adult male cigarette smokers in Hanoi, Vietnam: a longitudinal study
- 2023
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Ingår i: BMC PUBLIC HEALTH. - : BioMed Central (BMC). - 1471-2458. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundNearly one-in-two Vietnamese men smoke cigarettes placing them among the highest tobacco consumers in the world. Despite the need for smoking cessation to curb the burden of tobacco-related diseases in Vietnam, this rate remains at less than 30%. Therefore, this study examines individual-, social- and policy factors associated with smoking cessation among adult male smokers in Vietnam.MethodsWe established a longitudinal International Tobacco Control study of male smokers in Hanoi, Vietnam, in September 2018. This paper analyses 1525 men who participated in baseline and one-year follow-up. We applied a weighted multivariable logistic regression to examine the association between smoking cessation and individual-, social- and policy predictors.ResultsAt follow-up, 14.8% of participants had quit smoking for at least 30 consecutive days during the last year. Among the persistent smokers, 56.6% expressed intention to quit smoking. Factors associated with smoking cessation included a lower number of cigarettes smoked per day (aOR = 0.96, 95% CI: 0.94, 0.99) and having several attempts to quit smoking (aOR = 2.16, 95% CI 1.13, 4.12). Intention to quit smoking was associated with multiple quit attempts, a chronic condition diagnosis, more tobacco-related knowledge, greater self-efficacy, and more worries about their future health. The perceived impact of smoke-free policy and health warning labels were positively associated with intention to quit at any stage.ConclusionsInterventions aimed at increasing smoking cessation should focus on all aspects of individual, social, and policy factors. Persistent smokers are more motivated to quit if they have made multiple quit attempts, more self-efficacy of quitting and worried about their future health, indicating that increasing smokers' beliefs and knowledge may be important for behavioural change. Health warning labels and tobacco taxation policies should be maintained and promoted as they are perceived to be particularly useful for persistent smokers' intention to quit.
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| 4. |
- Pham, Binh Thai, et al.
(författare)
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Performance Evaluation of Machine Learning Methods for Forest Fire Modeling and Prediction
- 2020
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Ingår i: Symmetry. - Switzerland : MDPI. - 2073-8994. ; 12:6
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Tidskriftsartikel (refereegranskat)abstract
- Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP) machine learning methods for the prediction and mapping fire susceptibility across the Pu Mat National Park, Nghe An Province, Vietnam. The modeling methodology was formulated based on processing the information from the 57 historical fires and a set of nine spatially explicit explanatory variables, namely elevation, slope degree, aspect, average annual temperate, drought index, river density, land cover, and distance from roads and residential areas. Using the area under the receiver operating characteristic curve (AUC) and seven other performance metrics, the models were validated in terms of their abilities to elucidate the general fire behaviors in the Pu Mat National Park and to predict future fires. Despite a few differences between the AUC values, the BN model with an AUC value of 0.96 was dominant over the other models in predicting future fires. The second best was the DT model (AUC = 0.94), followed by the NB (AUC = 0.939), and MLR (AUC = 0.937) models. Our robust analysis demonstrated that these models are sufficiently robust in response to the training and validation datasets change. Further, the results revealed that moderate to high levels of fire susceptibilities are associated with ~19% of the Pu Mat National Park where human activities are numerous. This study and the resultant susceptibility maps provide a basis for developing more efficient fire-fighting strategies and reorganizing policies in favor of sustainable management of forest resources.
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| 5. |
- Nguyen, Thanh N, et al.
(författare)
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Global Impact of the COVID-19 Pandemic on Stroke Volumes and Cerebrovascular Events: A 1-Year Follow-up.
- 2023
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Ingår i: Neurology. - 1526-632X. ; 100:4
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Tidskriftsartikel (refereegranskat)abstract
- Declines in stroke admission, IV thrombolysis (IVT), and mechanical thrombectomy volumes were reported during the first wave of the COVID-19 pandemic. There is a paucity of data on the longer-term effect of the pandemic on stroke volumes over the course of a year and through the second wave of the pandemic. We sought to measure the effect of the COVID-19 pandemic on the volumes of stroke admissions, intracranial hemorrhage (ICH), IVT, and mechanical thrombectomy over a 1-year period at the onset of the pandemic (March 1, 2020, to February 28, 2021) compared with the immediately preceding year (March 1, 2019, to February 29, 2020).We conducted a longitudinal retrospective study across 6 continents, 56 countries, and 275 stroke centers. We collected volume data for COVID-19 admissions and 4 stroke metrics: ischemic stroke admissions, ICH admissions, IVT treatments, and mechanical thrombectomy procedures. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.There were 148,895 stroke admissions in the 1 year immediately before compared with 138,453 admissions during the 1-year pandemic, representing a 7% decline (95% CI [95% CI 7.1-6.9]; p < 0.0001). ICH volumes declined from 29,585 to 28,156 (4.8% [5.1-4.6]; p < 0.0001) and IVT volume from 24,584 to 23,077 (6.1% [6.4-5.8]; p < 0.0001). Larger declines were observed at high-volume compared with low-volume centers (all p < 0.0001). There was no significant change in mechanical thrombectomy volumes (0.7% [0.6-0.9]; p = 0.49). Stroke was diagnosed in 1.3% [1.31-1.38] of 406,792 COVID-19 hospitalizations. SARS-CoV-2 infection was present in 2.9% ([2.82-2.97], 5,656/195,539) of all stroke hospitalizations.There was a global decline and shift to lower-volume centers of stroke admission volumes, ICH volumes, and IVT volumes during the 1st year of the COVID-19 pandemic compared with the prior year. Mechanical thrombectomy volumes were preserved. These results suggest preservation in the stroke care of higher severity of disease through the first pandemic year.This study is registered under NCT04934020.
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| 6. |
- Pham, Binh Thai, et al.
(författare)
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A Comparative Study of Kernel Logistic Regression, Radial Basis Function Classifier, Multinomial Naïve Bayes, and Logistic Model Tree for Flash Flood Susceptibility Mapping
- 2020
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Ingår i: Water. - Switzerland : MDPI. - 2073-4441. ; 12:1, s. 1-21
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Tidskriftsartikel (refereegranskat)abstract
- Risk of flash floods is currently an important problem in many parts of Vietnam. In this study, we used four machine-learning methods, namely Kernel Logistic Regression (KLR), Radial Basis Function Classifier (RBFC), Multinomial Naïve Bayes (NBM), and Logistic Model Tree (LMT) to generate flash flood susceptibility maps at the minor part of Nghe An province of the Center region (Vietnam) where recurrent flood problems are being experienced. Performance of these four methods was evaluated to select the best method for flash flood susceptibility mapping. In the model studies, ten flash flood conditioning factors, namely soil, slope, curvature, river density, flow direction, distance from rivers, elevation, aspect, land use, and geology, were chosen based on topography and geo-environmental conditions of the site. For the validation of models, the area under Receiver Operating Characteristic (ROC), Area Under Curve (AUC), and various statistical indices were used. The results indicated that performance of all the models is good for generating flash flood susceptibility maps (AUC = 0.983–0.988). However, performance of LMT model is the best among the four methods (LMT: AUC = 0.988; KLR: AUC = 0.985; RBFC: AUC = 0.984; and NBM: AUC = 0.983). The present study would be useful for the construction of accurate flash flood susceptibility maps with the objectives of identifying flood-susceptible areas/zones for proper flash flood risk management.
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| 7. |
- Phan Thi, Kim Chinh, et al.
(författare)
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On the Performance of Image Recovery in Massive MIMO Communications
- 2021
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Ingår i: IEEE ICCE 2020: 2020 IEEE EIGHTH INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND ELECTRONICS (ICCE). - : IEEE. - 9781728154718 ; , s. 487-491
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Konferensbidrag (refereegranskat)abstract
- Massive MIMO (Multiple Input Multiple Output) has demonstrated as a potential candidate for 5G-and-beyond wireless networks. Instead of using Gaussian signals as most of the previous works, this paper makes a novel contribution by investigating the transmission quality of image data by utilizing the Massive MIMO technology. We first construct a framework to decode the image signal from the noisy received data in the uplink Massive MIMO transmission by utilizing the alternating direction method of multipliers (ADMM) approach. Then, a low-pass filter is exploited to enhance the efficiency of the remaining noise and artifacts reduction in the recovered image. Numerical results demonstrate the necessity of a post-filtering process in enhancing the quality of image recovery.
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