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During the Vietnam War, the United States military sprayed over 74 million litres of Agent Orange (AO) to destroy forest cover as a counterinsurgency tactic in Vietnam, Laos and Cambodia. The main ingredient was contaminated by 2,3,7,8-tetrachlorodibenzo-paradioxin (TCDD). DNA methylation (DNAm) differences are potential biomarker of environmental toxicants exposure. The aim of this study was to perform a preliminary investigation of the DNAm levels from peripheral blood of the present-day Vietnamese population, including individuals whose parents, according to historical data, were exposed to AO/TCDD during the war. 94 individuals from heavily sprayed areas (cases) and 94 individuals from non-sprayed areas (controls) were studied, and historical data on alleged exposure of parents collected. 94 cases were analysed considering those whose father/parents participated in the war (N = 29) and considering the place of residence of both parents (64 living in sprayed areas versus 30 in non-contaminated areas). DNAm levels in CYP1A1 and IGF2 genes were measured (MALDI-TOF technology). The analyses showed that: 1) one CpG site in the CYP1A1 and one in the IGF2 gene showed significant differences in DNAm levels between cases and controls; 2) the CYP1A1 region resulted to be hypomethylated (in 9 out of 16 sites/units; p-val<0.01) in 29 individuals whose father/parents participated in the war in the spray zones; 3) we showed that the place of residence of both parents influenced methylation levels of the CYP1A1 and IGF2 genes (p-val<0.05). In conclusion this study indicates that past environmental exposure to dioxin (AO/TCDD) shapes the DNAm profile of CYP1A1 and that the place of living for parents in former spray zones influences DNAm of CYP1A1 and IGF2 genes. These results open the way to new applications of DNAm as potential biomarker(s) of past human exposure to dioxin. [ABSTRACT FROM AUTHOR]

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available. [Display omitted] • An efficient vision-based framework to detect COVID-19 through cough sounds. • Combine EfficientNet-V2 with PANNs through two stages of inference. • Aggregate features of Log-Mel-Spectrogram and Wavegram. • Control different sampling rates efficiently. • Fruit-CoV achieves an AUC score of 92.8% and is flexible with sampling rates. [ABSTRACT FROM AUTHOR]

Objective: To evaluate medication adherence, associated factors, and the role of pharmacists in adherence and outcome treatments in outpatients with diabetes at Hue University Hospital. Type 2 diabetes (T2DM) is a chronic illness that requires daily treatment. Poor adherence to antidiabetic medication can have negative consequences for patients. Data on medication adherence and programs to improve adherence for patients with diabetes in Vietnam are lacking. Methods: A pre-post study was conducted on 354 outpatients diagnosed with T2DM at Hue University Hospital. Participants were interviewed, counseled, and educated by a pharmacist once. The researchers assessed medication adherence levels and glycemic outcomes before and around three months after the intervention. Results: The prevalence of achieving adherence before the intervention was 65.0%. Factors associated with achieving medication adherence were medication regimen ( P = 0.001) and controlled glycemic target ( P < 0.001). The most common nonadherence behavior was forgetting to take antidiabetic medication. After the intervention, the prevalence of achieving adherence rose to 74.6%, and patients reported that they were more likely to remember to take antidiabetic medications (with statistical significance). The prevalence of achieving the glycemic target (both glycated hemoglobin and fasting plasma glucose) rose from 21.8% (before the intervention) to 31.1% (after the intervention). Conclusions: A significant proportion of patients did not achieve medication adherence. Medication adherence is associated with better glycemic outcomes. The role of pharmacists in patient education, medication counseling, and reminding is beneficial in terms of improving adherence levels and glycemic outcomes.