Explore the vast range of titles available.

Background De novo variations are a primary cause of Rett syndrome and Tubulinopathy, accounting for over 90% of cases. Some studies have identified and documented parental inheritance by mosaicism in these two disorders, albeit with limited data. Methods Clinical characteristics and diagnosis, including genetic tests of members of two families, were obtained from medical reports. Results The first family with Rett syndrome (RTT) presented with two offspring carrying FOXG1 c.460dup. Both affected RTT pregnancies did not show anomalies within the first trimester, preventing prenatal recognition at an early stage. The second family had two of three offspring confirmed with TUBA1A c.172G>A related to Tubulinopathy. Both young couples from the two families harbored none of the variants correlating to their children's conditions. Diagnosis of parental mosaics with higher rates of recurrence was reasonably determined, and genetic counseling played a major role in guiding and managing their subsequent pregnancies. Conclusion In genetic disorders with a high penetration of de novo variants, the risk of having a recurrent baby is an important topic to discuss with affected families. By examining variants that siblings share, clinical diagnosis can offer valuable information about the presence of mosaic inheritance. To effectively manage in the long term, adequate genetic counseling and strategic planning for future pregnancies should be emphasized to mitigate the risk of recurrent offspring.

The air quality index (AQI) forecast in big cities is an exciting study area in smart cities and healthcare on the Internet of Things. In recent years, a large number of empirical, academic, and review papers using machine learning (ML) for air quality analysis have been published. However, most of those studies focused on traditional centralized processing on a single machine, and there had been few surveys of federated learning (FL) in this field. This overview aims to fill this gap and provide newcomers with a broader perspective to inform future research on this topic, especially for the multi-model approach. In this survey, we went over the works that previous scholars have conducted in AQI forecast both in traditional ML approaches and FL mechanisms. Our objective is to comprehend previous research on AQI prediction including methods, models, data sources, achievements, challenges, and solutions applied in the past. We also convey a new path of using multi-model FL, which has piqued the computer science community’s interest recently.

The development of new algorithms can aid researchers and professionals in resolving problems that were once unsolvable or discovering superior solutions to problems that were already settled. By recognizing the importance of continuous research on creating novel algorithms, this paper introduced a hybrid metaheuristic algorithm-h-PSOGNDO, which is a combination of Particle Swarm Optimization (PSO) and Generalized Normal Distribution Optimization (GNDO). The proposed algorithm utilizes the Particle Swarm Optimization’s strategy for exploitation and the Generalized Normal Distribution Optimization’s global search strategy for exploration. Through this combination, h-PSOGNDO is believed to be an effective algorithm that can promote the advantages of its parents’ algorithms. Different assessment methods are used to assess the proposed novel algorithm. First, the h-PSOGNDO is set to conduct experiments on two sets of mathematical functions, including twenty-eight IEEE CEC2017 and ten IEEE CEC2019 benchmark test functions, respectively. Then, the h-PSOGNDO algorithm is applied to a case study on the prediction of antimicrobial peptides’ toxicity to evaluate its performance on real-life problems. The statistical findings collected from both the test function sets and the case study show that the h-PSOGNDO algorithm works effectively, proving its astonishing ability to yield highly competitive outcomes for complex problems.

Background Self-care behaviors during pregnancy significantly impacts mother and children's health. This study aimed to explore the self-care behaviors and the associations of these behaviors with the psychological well-being of women during pregnancy, as well as the mediating effects of different social support with these associations. Methods A cross-sectional data of 562 pregnant women at Hanoi Obstetrics & Gynecology Hospital and Ca Mau Obstetrics & Pediatrics in Vietnam were analyzed. Questions about self-care behaviors, pregnancy characteristics, social support, and psychological well-being were asked. Multivariate regression models were performed. Structural Equation Modeling (SEM) was employed to test the mediating effects of different social support with the association between self-care behaviors and psychological well-being. Findings Only 13% of pregnant women often or always did physical exercise at least three times a week, and 40% consumed enough fiber and five servings of vegetables a day. Only 78.7% always avoided alcohol drinking, and 53.9% of pregnant women avoided being exposed to second-hand smoking and 71,7% avoided using traditional medicine without physicians’ prescriptions. Around 66% of pregnant women always or often had prenatal care checkups as scheduled. Information sources, social support and childbirth expectation were major drivers for self-care practices. SEM model showed that social support mediated the relationship between maternal health behaviors and mental well-being. Conclusion This study highlighted the remarkable gaps in self-care practices among our pregnant women, which were significantly associated with their mental well-being. Social support-oriented consultancy and interventions should be warranted for improving behaviors and the mental well-being of pregnant women in Vietnam.

ObjectivesThis study aimed to determine doctors’ level of adherence to the natriuretic peptide testing guideline and to identify the factors influencing their adherence.DesignCross-sectional study.SettingWeb-based survey.ParticipantsFull-time doctors involved in heart failure (HF) treatment in Vietnam.Primary and secondary outcome measuresDoctors using natriuretic peptide testing for diagnosis, differential diagnosis, treatment assessment and prognosis of patients with HF were classified as adhering to the guidelines. We assessed the practice of natriuretic peptide testing and stratified the doctors based on their professional qualifications. Univariate and multivariate logistic regression analyses were used to estimate the Odds Ratio (ORs) and 95% CIs for associations between guideline adherence and selected covariates.ResultsOver half of the participants adhered to the natriuretic peptide testing guidelines (57.4%). Cardiologists adhered more closely to the guidelines than other professionals; they had approximately four times higher odds of adherence than other doctors (univariate model, OR: 3.88, 95% CI: 2.56 to 5.89, p<0.001; multivariate model, OR: 4.24, 95% CI: 2.64 to 6.82, p<0.001). Cardiologists also had significantly higher rates of using natriuretic peptide testing for diagnosis (93.8% vs 84.1%, p<0.002), differential diagnosis (71.4% vs 53.5%, p<0.001), treatment assessment (87% vs 64.2%, p<0.001) and prognosis (68.2% vs 50.4%, p<0.001) than other professionals. More years of professional experience correlated with higher guideline adherence (<2 years was used as a reference point; >5 to <10 years, OR: 2.59, 95% CI: 1.45 to 4.60, p<0.001; ≥10 years, OR: 2.30, 95% CI: 1.30 to 4.09, p<0.004).ConclusionThe level of adherence to natriuretic peptide testing guidelines among doctors treating patients with HF varies across Vietnam. Targeted interventions are needed to enhance understanding and proficiency, especially among non-cardiologists and those with limited experience. A dedicated fact sheet focusing on natriuretic peptide testing in HF management, separate from the existing guidelines, could bridge this gap.

Background Gender-biased discrimination and preferences are global phenomena, particularly son preferences. However, updated evidence about this issue in Vietnam has not yet been provided. Therefore, this study aimed to examine the gender preferences among pregnant women and identify associated factors of such preferences. Methods A cross-sectional survey was conducted in two hospitals in Vietnam with 732 pregnant women. Gender preferences for their child were asked, along with socio-demographic (e.g., education, occupation) and pregnancy characteristics (e.g., pressure to have a son, gender of first child, the importance to have a son of family members, and information sources on pregnancy care) by using face-to-face interviews and a structured questionnaire. Multinomial logistic regression was performed to determine factors associated with gender preferences. Results About 51.9% of the participants had no gender preference, while, among those who had a gender preference, 26.5% preferred sons, and 21.6% preferred daughters. Only 6.2% had pressure to have a son. Having the first child who was female (OR = 4.16, 95%CI = 1.54–11.25), having the pressure to have a son (OR = 6.77, 95%CI = 2.06–22.26), and higher self-perceived importance to have a son (OR = 3.05, 95%CI = 1.85–5.02) were positively associated with son preference. Otherwise, women having partners with high school education or above (OR = 2.04, 95%CI = 1.06–3.91), living with parents-in-law (OR = 2.33; 95%CI = 1.25–4.34), the higher number of pregnancies, and a higher degree of importance in having a son regarding parents-in-law (OR = 2.15, 95%CI = 1.38–3.35) associated with higher odds of preferring daughter. Conclusion This study showed that gender preference was common among pregnant women, but the pressure to have a son was low. Further education programs and legal institutions should be implemented to improve gender inequality and gender preference in society.

In this study, nanocatalyst NiPd was synthesized via a successful two-stage reduction process with NaBH 4 and PVP. More specifically, the first stage involves NaBH 4 reduction of Ni 2+ ion to metallic Ni. Afterwards, Pd would be coated on the surface of the aformentioned Ni particles by reducing Pd 2+ using the remaining NaBH 4 . The effect of experimental parameters on the synthesis and catalytic activity of the nanocatalysts, such as reaction temperature (30, 40, 50, 60, 70 °C), reaction time (60, 90, 120, 150, 180 minutes), Pd:Ni mole ratio (1:10, 3:10, 5:10, 7:10, 9:10). were investigated by X-ray diffraction (XRD), Energy dispersive spectroscopy (EDX), and transmission electron microscopy (TEM) were used to analyse the surface structure, composition and morphology of the catalyst samples. The catalytic activity and stability of the resulting NiPd/C catalysts were investigated towards the methanol oxidation reaction (MOR) in alkaline environment by cyclic voltammetry (CV) and chronoamperometry (CA) techniques. The results showed that the highest catalytic activity was found for the sample synthesized at 50 °C with 120-minute reaction time and the Pd:Ni molar ratio of 5:10. The influence of KOH and methanol concentrations on the catalytic activity of NiPd/C for methanol oxidation reaction in alkaline medium was also investigated. The results demonstrated the promising potential of NiPd/C nanomaterials as catalyst materials for the anodic layer in direct methanol fuel cells (DMFCs).

Surface modification of metal oxide nanoparticles can enhance their dispersibility in polymer matrix. In this study, the zinc oxide (ZnO) nanoparticles (NPs) were organically modified by coupling agent as isopropyl tri (dioctyl phosphate) titanate (KR-12) with the initial content of 3 wt.% (in comparison with ZnO NPs weight). The characteristics of modified ZnO (m-ZnO) NPs, namely chemical changes, zeta potential, morphology, and thermal behavior, were evaluated using IR spectroscopy, DLS, SEM, and TGA methods, respectively. The obtained results suggested that ZnO NPs were modified successfully with KR-12 coupling agent. In comparison with the unmodified ZnO (u-ZnO) NPs, the m-ZnO NPs had additional functional groups and there were changes of some properties such as hydrophobic property, surface charge, and thermal stability of m-ZnO NPs. The m-ZnO NPs could disperse in epoxy resin better than the u-ZnO NPs. Therefore, the m-ZnO NPs improved the mechanical properties, chemical resistance, thermal stability, and anticorrosion protection ability of epoxy resin coating. The abrasion resistance and the adhesion of epoxy coating containing 2 wt.% m-ZnO NPs were increased about 40% and 54%, respectively. The bending resistance of epoxy resin was also enhanced, and the anticorrosion resistance of coatings was improved in the presence of m-ZnO nanoparticles.

Combination of waning immunity and lower effectiveness against new SARS-CoV-2 variants of approved COVID-19 vaccines necessitates new vaccines. We evaluated two doses, 28 days apart, of ARCT-154, a self-amplifying mRNA COVID-19 vaccine, compared with saline placebo in an integrated phase 1/2/3a/3b controlled, observer-blind trial in Vietnamese adults (ClinicalTrial.gov identifier: NCT05012943). Primary safety and reactogenicity outcomes were unsolicited adverse events (AE) 28 days after each dose, solicited local and systemic AE 7 days after each dose, and serious AEs throughout the study. Primary immunogenicity outcome was the immune response as neutralizing antibodies 28 days after the second dose. Efficacy against COVID-19 was assessed as primary and secondary outcomes in phase 3b. ARCT-154 was well tolerated with generally mild–moderate transient AEs. Four weeks after the second dose 94.1% (95% CI: 92.1–95.8) of vaccinees seroconverted for neutralizing antibodies, with a geometric mean-fold rise from baseline of 14.5 (95% CI: 13.6–15.5). Of 640 cases of confirmed COVID-19 eligible for efficacy analysis most were due to the Delta (B.1.617.2) variant. Efficacy of ARCT-154 was 56.6% (95% CI: 48.7– 63.3) against any COVID-19, and 95.3% (80.5–98.9) against severe COVID-19. ARCT-154 vaccination is well tolerated, immunogenic and efficacious, particularly against severe COVID-19 disease. In this randomized, controlled integrated phase 1/2/3a/3b clinical trial, the authors show that the self-amplifying mRNA COVID-19 vaccine ARCT-154 shows good immunogenicity and is safe and efficient against COVID-19 (57% against any COVID-19, and 95% against severe COVID-19).