Molecular Characterization of Dengue Virus Strains from the 2019-2020 Epidemic in Hanoi, Vietnam.

Dengue virus (DENV), which has circulated in Vietnam for several decades, has multiple serotypes and genotypes. A 2019 dengue outbreak resulted in a larger number of cases than any other outbreak. We conducted a molecular characterization using samples collected in 2019-2020 from dengue patients in Hanoi and nearby cities located in northern Vietnam. The circulating serotypes were DENV-1 (25%, n = 22) and DENV-2 (73%, n = 64). Phylogenetic analyses revealed that all DENV-1 (n = 13) were genotype I and clustered to local strains circulating during the previous outbreak in the 2017, whereas DENV-2 consisted of two genotypes: Asian-I (n = 5), related to local strains from 2006-2022, and cosmopolitan (n = 18), the predominant genotype in this epidemic. The current cosmopolitan virus was identified as having an Asian-Pacific lineage. The virus was closely related to strains in other recent outbreaks in Southeast Asian countries and China. Multiple introductions occurred in 2016-2017, which were possibly from maritime Southeast Asia (Indonesia, Singapore, and Malaysia), mainland Southeast Asia (Cambodia and Thailand), or China, rather than from an expansion of localized Vietnamese cosmopolitan strains that were previously detected in the 2000s. We also analyzed the genetic relationship between Vietnam's cosmopolitan strain and recent global strains reported from Asia, Oceania, Africa, and South America. This analysis revealed that viruses of Asian-Pacific lineage are not restricted to Asia but have spread to Peru and Brazil in South America.

Knowledge and attitudes toward complete diagnostic autopsy and minimally invasive autopsy: A cross-sectional survey in Hanoi, Vietnam.

Knowing the cause of death (CoD) plays an important role in developing strategies and interventions to prevent early mortality. In Vietnam, the CoD of the majority of patients who acquired infectious diseases remains unknown. While there are challenges that hinder the use of complete diagnostic autopsy (CDA) in practice, minimally invasive autopsy (MIA) might be a promising alternative to establish CoD in Vietnam. The current study aims to explore knowledge of and attitudes toward CDA and MIA in the wider population in Vietnam. The study was cross-sectional, using structured questionnaires that were disseminated electronically via several websites and as paper-based forms in a national level hospital in Vietnam. Descriptive analyses were performed and where appropriate, comparisons between the healthcare workers and the general public were performed. We included 394 questionnaires in the analysis. The majority of participants were under age 40, living in major cities and currently practicing no religion. 76.6% of respondents were aware of CDA and among them, 98% acknowledged its importance in medicine. However, most participants thought that CDA should only be performed when the CoD was suspicious or unconfirmed because of its the invasive nature. For MIA, only 22% were aware of the method and there was no difference in knowledge of MIA between healthcare workers and the wider public. The questionnaire results showed that there are socio-cultural barriers that hinder the implementation of CDA in practice. While the awareness of MIA among participants was low, the minimally invasive nature of the method is promising for implementation in Vietnam. A qualitative study is needed to further explore the ethical, socio-cultural and/or religious barriers that might hinder the implementation of MIA in Vietnam.

Comparison of machine learning and deep learning-based methods for locomotion mode recognition using a single inertial measurement unit.

Locomotion mode recognition provides the prosthesis control with the information on when to switch between different walking modes, whereas the gait phase detection indicates where we are in the gait cycle. But powered prostheses often implement a different control strategy for each locomotion mode to improve the functionality of the prosthesis. Existing studies employed several classical machine learning methods for locomotion mode recognition. However, these methods were less effective for data with complex decision boundaries and resulted in misclassifications of motion recognition. Deep learning-based methods potentially resolve these limitations as it is a special type of machine learning method with more sophistication. Therefore, this study evaluated three deep learning-based models for locomotion mode recognition, namely recurrent neural network (RNN), long short-term memory (LSTM) neural network, and convolutional neural network (CNN), and compared the recognition performance of deep learning models to the machine learning model with random forest classifier (RFC). The models are trained from data of one inertial measurement unit (IMU) placed on the lower shanks of four able-bodied subjects to perform four walking modes, including level ground walking (LW), standing (ST), and stair ascent/stair descent (SA/SD). The results indicated that CNN and LSTM models outperformed other models, and these models were promising for applying locomotion mode recognition in real-time for robotic prostheses.

Assessment of COVID-19 Preventive Practice and Associated Factors Among Educators in Vietnam.

BACKGROUND: Educators play a critical role in offering knowledge that is vital to preventing the spread of the COVID-19 in educational settings. This study aims to assess the proportion of preventive practices towards COVID-19 and associated factors among educators in Vietnam. METHODS: A cross-sectional study was conducted on educators at the University of Medicine and Pharmacy at Ho Chi Minh City (UMP) using a self-administered questionnaire between June and August 2020. Online surveys and a multivariable logistic regression analysis were used to determine factors associated with practices. Adjusted odds ratio (AOR) and 95% confidence interval (95% CI) were performed using Stata 14. RESULTS: A total of 779 eligible participants were approached, most of them under 50 years (84.1%), around three-fifth were female (61.0%) and lecturers (61.1%), with only 38.1% of them working at hospitals. Overall, the majority of participants had good preventive practices towards COVID-19 (88.6%). Factors identified as being associated with good practices included participants who are lecturers (AOR 1.8, 95% CI: 1.05-2.97), attending training courses related to COVID-19 (AOR 1.7, 95% CI: 1.05-2.87), working at hospitals (AOR 2.5, 95% CI: 1.28-4.76) and having a higher level of knowledge and attitude relating to COVID-19 (AOR 2.8, 95% CI: 1.52-5.17; AOR 2.8, 95% CI: 1.70-4.48, respectively) (all p < 0.05). CONCLUSION: These findings revealed that most educators reported a good level of preventive practices towards COVID-19. However, lower levels of practices still exist towards COVID-19 among participants who were administrative staff and have less access to training courses related to COVID-19, who reported that they did not work at the hospital and had a lower level of knowledge and attitude related to COVID-19. Because of the important role of educators in the education system, this study is expected to help education and health authorities implement suitable interventions to fill the gaps in practices between educators.

A Review of Gait Phase Detection Algorithms for Lower Limb Prostheses.

Fast and accurate gait phase detection is essential to achieve effective powered lower-limb prostheses and exoskeletons. As the versatility but also the complexity of these robotic devices increases, the research on how to make gait detection algorithms more performant and their sensing devices smaller and more wearable gains interest. A functional gait detection algorithm will improve the precision, stability, and safety of prostheses, and other rehabilitation devices. In the past years the state-of-the-art has advanced significantly in terms of sensors, signal processing, and gait detection algorithms. In this review, we investigate studies and developments in the field of gait event detection methods, more precisely applied to prosthetic devices. We compared advantages and limitations between all the proposed methods and extracted the relevant questions and recommendations about gait detection methods for future developments.

An alarmingly high nasal carriage rate of Streptococcus pneumoniae serotype 19F non-susceptible to multiple beta-lactam antimicrobials among Vietnamese children.

BACKGROUND: Understanding the relationship between serotype epidemiology and antimicrobial susceptibility of Streptococcus pneumoniae is essential for the effective introduction of pneumococcal conjugate vaccines (PCVs) and control of antimicrobial-resistant pneumococci. METHODS: We conducted a community-based study in Nha Trang, central Vietnam, to clarify the serotype distribution and pattern of S. pneumoniae antimicrobial susceptibility in children under 5 years of age and to identify risk factors for carrying antimicrobial-resistant strains. Nasopharyngeal swabs collected from children with acute respiratory infections (ARIs) hospitalized between April 7, 2008, and March 30, 2009, and from healthy children randomly selected in July 2008 were subjected to bacterial culture. Minimum inhibitory concentrations (MICs) against S. pneumoniae were determined, and multiplex-polymerase chain reaction (PCR) serotyping assays were performed. Logistic regression was applied to identify risk factors. RESULTS: We collected 883 samples from 331 healthy children and 552 ARI cases; S. pneumoniae was isolated from 95 (28.7%) healthy children and 202 (36.6%) ARI cases. Age and daycare attendance were significantly associated with pneumococcal carriage. In total, 18.0, 25.8 and 75.6% of the isolates had high MICs for penicillin (≥4 µg/ml), cefotaxime (≥2 µg/ml) and meropenem (≥0.5 µg/ml), respectively. The presence of pneumococci non-susceptible to multiple beta-lactams was significantly associated with serotype 19F (Odds Ratio: 4.23) and daycare attendance (Odds Ratio: 2.56) but not ARIs, age or prior antimicrobial use. The majority of isolates non-susceptible to multiple beta-lactams (90%) were PCV13 vaccine serotypes. CONCLUSIONS: S. pneumoniae serotype 19F isolates non-susceptible to multiple beta-lactams are widely prevalent among Vietnamese children. Vaccine introduction is expected to significantly increase drug susceptibility.

Comparison of the microdrop and minimum volume cooling methods for vitrification of porcine in vitro-produced zygotes and blastocysts after equilibration in low concentrations of cryoprotectant agents.

We compared the efficacy of the microdrop and minimum volume cooling (MVC) methods for the vitrification of in vitro-produced porcine zygotes and blastocysts after equilibration in low concentrations of cryoprotectant agents. Zygotes and blastocysts were equilibrated in 2% (v/v) ethylene glycol and 2% (v/v) propylene glycol for 13-15 min. Then, they were vitrified in a medium comprised of 17.5% ethylene glycol, 17.5% propylene glycol, 0.3 M sucrose, and 50 mg/ml polyvinylpyrrolidone either by either dropping them directly into liquid nitrogen (microdrop method) or placing them on Cryotop sheets in a minimum volume of medium and plunging into liquid nitrogen (MVC method). Both zygotes and blastocysts were successfully vitrified. For the vitrification of zygotes, the MVC and microdrop methods were equally effective; however, for blastocyst vitrification, MVC was superior. For both methods, the vitrification of zygotes produced higher-quality embryos than the vitrification of blastocysts.

ED-FNN: A New Deep Learning Algorithm to Detect Percentage of the Gait Cycle for Powered Prostheses.

Throughout the last decade, a whole new generation of powered transtibial prostheses and exoskeletons has been developed. However, these technologies are limited by a gait phase detection which controls the wearable device as a function of the activities of the wearer. Consequently, gait phase detection is considered to be of great importance, as achieving high detection accuracy will produce a more precise, stable, and safe rehabilitation device. In this paper, we propose a novel gait percent detection algorithm that can predict a full gait cycle discretised within a 1% interval. We called this algorithm an exponentially delayed fully connected neural network (ED-FNN). A dataset was obtained from seven healthy subjects that performed daily walking activities on the flat ground and a 15-degree slope. The signals were taken from only one inertial measurement unit (IMU) attached to the lower shank. The dataset was divided into training and validation datasets for every subject, and the mean square error (MSE) error between the model prediction and the real percentage of the gait was computed. An average MSE of 0.00522 was obtained for every subject in both training and validation sets, and an average MSE of 0.006 for the training set and 0.0116 for the validation set was obtained when combining all subjects' signals together. Although our experiments were conducted in an offline setting, due to the forecasting capabilities of the ED-FNN, our system provides an opportunity to eliminate detection delays for real-time applications.

Association between nasopharyngeal load of Streptococcus pneumoniae, viral coinfection, and radiologically confirmed pneumonia in Vietnamese children.

BACKGROUND: The interplay between nasopharyngeal bacterial carriage, viral coinfection, and lower respiratory tract infections (LRTIs) is poorly understood. We explored this association in Vietnamese children aged less than 5 years. METHODS: A hospital-based case-control study of pediatric LRTIs was conducted in Nha Trang, Vietnam. A total of 550 hospitalized children (274 radiologically confirmed pneumonia [RCP] and 276 other LRTIs) were enrolled and 350 healthy controls were randomly selected from the community. Polymerase chain reaction-based methods were used to measure bacterial loads of Streptococcus pneumoniae (SP), Haemophilus influenzae, and Moraxella catarrhalis and to detect 13 respiratory viruses and bacterial serotypes in nasopharyngeal samples of study participants. RESULTS: The median nasopharyngeal bacterial load of SP was substantially higher in children with RCP compared with healthy controls or children with other LRTIs (P < 0.001). SP load was 15-fold higher in pneumonia children with viral coinfection compared with those children without viral coinfection (1.4 x 107/mL vs. 9.1 x 105/mL; P 0.0001). SP load was over 200-fold higher in serotypeable SP compared with nontypeable SP (2.5 x 106/mL vs. 1 x 104/mL; P < 0.0001). These associations were independent of potential confounders in multiple regression models. No clear association was found between nasopharyngeal load of Haemophilus influenzae or Moraxella catarrhalis and viral coinfection in either RCP or other LRTIs groups. CONCLUSIONS: An increased load of SP in the nasopharynx was associated with RCP, viral coinfection, and presence of pneumococcal capsule.