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Objectives: This study aims to investigate the effect of coating time on the formation of hydroxyapatite (HA) coating layer on ZK60 substrate and understand the biodegradation behavior of the coated alloy for biodegradable implant applications. Methods: Biodegradable ZK60 alloy was coated by HA layer for different times of 0.5, 1, 2, and 4 h by chemical conversion method. After coating, all the coated specimens were used for immersion test in Hanks’ solution to understand the effect of coating time on the degradation behavior of the alloy. The degradation rate of the coated alloy was evaluated by Mg 2+ ion quantification and pH change during immersion test. The microstructure of the coating layer was examined by scanning electron microscope (SEM) equipped with an energy-dispersive X-ray spectroscopy (EDS) before and after immersion to understand the degradation behavior of the coated alloy. Results: HA coating layers were formed successfully on surface of ZK60 specimens after 0.5, 1, 2, and 4 h with different microstructure. Optimal coating quality was observed at 1 or 2 h, characterized by well-formed and uniform HA layers. However, extending the coating duration to 4 h led to the formation of cracks within the HA layer, accompanied by Mg(OH) 2 . Specimens coated for 1 and 2 h exhibited the lowest degradation rates, while specimens coated for 0.5 and 4 h showed the highest degradation rates. Furthermore, analysis of degradation products revealed the predominance of calcium phosphates formed on the surface of specimens coated for 1 and 2 h. Conversely, specimens coated for 0.5 and 4 h exhibited Mg(OH) 2 as the primary degradation product, suggesting a less effective corrosion barrier under these conditions. Conclusion: The HA layer formed after 2 h demonstrated as the most effective coating layer for enhancing the corrosion resistance of the ZK60 alloy for biomedical applications.

Background Smoking among adolescents in schools is a major global public health concern. There is limited evidence regarding prevalence and associated factors in Vietnam. Objective To compare the prevalence of smoking and associated factors among in-school adolescents aged 13–17 years in Vietnam between 2013 and 2019. Methods Data were collected from two rounds of the national representative Vietnam Global School-based Student Health Survey (GSHS) conducted in 2013 (n = 3,331) and 2019 (n = 7,690). Logistic regression was used to identify the factors associated with tobacco and electronic cigarette smoking among in-school adolescents. Results There was a significant reduction in the prevalence of current smoking (water pipes and cigarettes) from 5.4% (95% CI: 4.0–7.2) in 2013 to 2.8% (95% CI: 2.2–3.6) in 2019. In 2019, 2.6% of the in-school adolescents reported having used electronic cigarette products 30 days prior to the survey. Factors associated with a significantly higher likelihood of current smoking status included gender, loneliness, suicidal ideation, sexual activity, truancy, and alcohol consumption. Similar patterns were observed for e-cigarettes. Conclusion Smoking among in-school adolescents in Vietnam decreased between 2013 and 2019. Follow-up studies are needed to further investigate causal factors so that future policies and communication programmes can be more effectively targeted to reduce smoking in adolescents.

Background: Adolescence is a vulnerable period for many lifestyle risk behaviors. In this study, we aimed to 1) examine a clustering pattern of lifestyle risk behaviors; 2) investigate roles of the school health promotion programs on this pattern among adolescents in Vietnam. Methods: We analyzed data of 7,541 adolescents aged 13–17 years from the 2019 nationally representative Global School-based Student Health Survey, conducted in 20 provinces and cities in Vietnam. We applied the latent class analysis to identify groups of clustering and used Bayesian 2-level logistic regressions to evaluate the correlation of school health promotion programs on these clusters. We reassessed the school effect size by incorporating different informative priors to the Bayesian models. Findings: The most frequent lifestyle risk behavior among Vietnamese adolescents was physical inactivity, followed by unhealthy diet, and sedentary behavior. Most of students had a cluster of at least two risk factors and nearly a half with at least three risk factors. Latent class analysis detected 23% males and 18% females being at higher risk of lifestyle behaviors. Consistent through different priors, high quality of health promotion programs associated with lower the odds of lifestyle risk behaviors (highest quality schools vs. lowest quality schools; males: Odds ratio (OR) = 0·67, 95% Highest Density Interval (HDI): 0·46 – 0·93; females: OR = 0·69, 95% HDI: 0·47 – 0·98). Interpretation: Our findings demonstrated the clustering of specific lifestyle risk behaviors among Vietnamese in-school adolescents. School-based interventions separated for males and females might reduce multiple health risk behaviors in adolescence. Funding: The 2019 Global School-based Student Health Survey was conducted with financial support from the World Health Organization. The authors received no funding for the data analysis, data interpretation, manuscript writing, authorship, and/or publication of this article.

The paper deals with the problem of identification of linearly varying frequency of sinusoidal signal with unknown amplitude and phase. Identification task for linearly varying frequency occurs, for example, during telescope operation control and it is of practical interest. Existing synthesis methods for identification algorithms of linearly varying frequency of sinusoidal signal use unlimited functions of time that is not attractive from a technical point of view, since the measurement noise multiplied by an unlimited function tends to give extremely poor estimates of the tunable parameter. This paper proposes a new approach for identification of linearly varying frequency comprising iterative filtering of measured sinusoidal signal (with the use of linear first order stable components), which in turn gives the possibility to obtain a simple linear regression model with one unknown constant parameter. We present computer simulation results, illustrating the performance of the proposed identification algorithm. Computer modeling was performed both in the presence and absence of the measurement noise. Also, comparative analysis of the proposed approach with the previously obtained methods was carried out within the framework of computer simulation. It was shown that the presented solution provides a significant improvement in the accuracy of an unknown frequency identification in the noise presence.

In this report, we present the case of a 53-year-old man with rice body formation in the right knee caused by tuberculous arthritis (TB arthritis). The patient visited our hospital in January 2018 with a seven-month history of swelling and pain in the right knee. He had no previous history of tuberculosis, and the results of the routine laboratory tests were within normal limits; he also tested negative for rheumatoid factor. Magnetic resonance (MR) imaging revealed multiple rice bodies in the right knee, measuring 5-8 mm. He underwent an arthroscopic operation in the right knee in January 2018 and received antituberculosis polytherapy for 6 months. He was followed-up for more than 01 year. The patient regained good function of the operated knee with no evidence of recurrence during the last follow-up in February 2019. Conclusion. The biggest challenge in diagnosing tuberculosis arthritis is the consideration of its possibility in the differential diagnosis, not only in endemic countries where tuberculosis is frequent. A high level of suspicion for TB should be maintained for every infection of the knee joint, particularly in the case of intra-articular rice bodies.

A series of numerical experiments have been conducted to investigate the intermediate principal stress effects on rock failure behaviors. The numerical results show that the strength and deformation of the rock samples are significantly affected by the intermediate principal stress. The effects are inconsistent in different intervals. As intermediate principal stress ratio b increases, the rock strength increases initially and finally decreases. When b is approximately equal to 0.5, the strength of the rock sample reaches the maximum. In the microlevel, the intermediate principal stress affects the number and distribution of microcracks. The increase of the intermediate principal stress makes the projection of the microcracks on the loading plane change from uniform to uneven. On the one hand, the intermediate principal stress restricts the propagation of microcracks in the normal direction along the intermediate principal stress (or with a component in this direction), which will lead to an increase in the strength of the rock samples. On the other hand, the propagation of microcracks along the normal direction with small principal stress (or with a component in this direction) is promoted, which leads to a decrease in the strength of the rock sample. End friction can make the intermediate principal stress effect more significant because the friction of the loading end to the rock sample can result in stress deviation between the actual value and experimental value. Inhomogeneity of stress field induced by the change of stress states or end friction forces is the external factor of the intermediate principal stress effect. Also, the inhomogeneity of rock material itself is the internal factor. Intermediate principal stress will promote or restrict the failure of certain directions, thus affecting the overall strength of the rock samples. The numerical results can be very meaningful for stability analysis of rock masses in practical engineering.

The paper considers the problem of the frequency identification for a biased sinusoidal signal in the absence of measurement noise. It is assumed that the displacement and amplitude of the sinusoidal signal are unknown functions of time. It is accepted that the frequency of the sinusoidal signal is an unknown number, and the displacement and amplitude of the sinusoidal signal can be represented as piecewise linear in the time interval. To estimate the frequency of the sinusoidal signal, an original parametrization procedure was proposed, reducing the original nonlinear equation to the form of a standard linear regression model. After a number of special transformations, the simplest equation was obtained, containing one unknown parameter (the square of the sinusoidal signal frequency) multiplied by the known time function. To search for this parameter, we used the standard integrated algorithm of identification, which makes it possible to guarantee the robustness of estimates to external disturbances, and also to improve the quality of transients due to the tuning coefficient. The proposed frequency identification algorithm has technical attractiveness and can be used in problems of compensation or suppression of disturbances and/or measurement errors described by harmonic or polyharmonic signals, including for compensation of vertical inertial accelerations in estimating gravity anomalies at a mobile object. To illustrate the efficiency of the proposed identification algorithm, the paper presents the results of computer modeling demonstrating the achievement of the target goals.

Antioxidant proteins are involved importantly in many aspects of cellular life activities. They protect the cell and DNA from oxidative substances (such as peroxide, nitric oxide, oxygen-free radicals, etc.) which are known as reactive oxygen species (ROS). Free radical generation and antioxidant defenses are opposing factors in the human body and the balance between them is necessary to maintain a healthy body. An unhealthy routine or the degeneration of age can break the balance, leading to more ROS than antioxidants, causing damage to health. In general, the antioxidant mechanism is the combination of antioxidant molecules and ROS in a one-electron reaction. Creating computational models to promptly identify antioxidant candidates is essential in supporting antioxidant detection experiments in the laboratory. In this study, we proposed a machine learning-based model for this prediction purpose from a benchmark set of sequencing data. The experiments were conducted by using 10-fold cross-validation on the training process and validated by three different independent datasets. Different machine learning and deep learning algorithms have been evaluated on an optimal set of sequence features. Among them, Random Forest has been identified as the best model to identify antioxidant proteins with the highest performance. Our optimal model achieved high accuracy of 84.6%, as well as a balance in sensitivity (81.5%) and specificity (85.1%) for antioxidant protein identification on the training dataset. The performance results from different independent datasets also showed the significance in our model compared to previously published works on antioxidant protein identification.

To evaluate risk factors for human infection with influenza A subtype H5N1, we performed a matched case-control study in Vietnam. We enrolled 28 case-patients who had laboratory-confirmed H5N1 infection during 2004 and 106 age-, sex-, and location-matched control-respondents. Data were analyzed by matched-pair analysis and multivariate conditional logistic regression. Factors that were independently associated with H5N1 infection were preparing sick or dead poultry for consumption

Simple Summary: Recent research uncovered the BRAF mutation in papillary craniopharyngiomas, leading to new targeted treatments that may reduce the need for invasive procedures. A systematic review of 20 studies with 37 patients, treated mostly in the U.S., found that 18 patients received these drugs after surgery or radiation (adjuvant treatment), while 19 received them before surgery (neoadjuvant treatment). The common combination of a BRAF inhibitor with a MEK inhibitor significantly shrank tumours, with reductions of 70% to 100% in many cases, and up to 91% for those treated before surgery. Some patients required no further treatment afterward. However, questions remain about the optimal use of these drugs, including timing, combinations, and managing side effects. Despite these challenges, targeted therapies are promising in improving outcomes and quality of life for patients with this brain tumour, with future studies expected to refine their use. Background/Objectives: The recent discovery of BRAF mutation in papillary craniopharyngiomas opened new avenues for targeted therapies to control tumour growth, decreasing the need for invasive treatments and relative complications. The aim of this systematic review was to summarize the recent scientific data dealing with the use of targeted therapies in papillary craniopharyngiomas, as adjuvant and neoadjuvant treatments. Methods: The PRISMA guidelines were followed with searches performed in Scopus, MEDLINE, and Embase, following a dedicated PICO approach. Results: We included 21 pertinent studies encompassing 53 patients: 26 patients received BRAF inhibitors (BRAFi) as adjuvant treatment, while 25 received them as neoadjuvant treatment. In the adjuvant setting, BRAFi were used to treat recurrent tumours after surgery or adjuvant radiation therapy. The most common regimen combined dabrafenib (BRAFi) with trametinib (MEK1 and 2 inhibitor) in 81% of cases. The mean treatment length was 8.8 months (range 1.6 to 28 months) and 32% were continuing BRAFi. A reduction of tumour volume variable from 24% to 100% was observed at cerebral MRI during treatment and volumetric reduction ≥80% was described in 64% of cases. Once the treatment was stopped, adjuvant treatments were performed to stabilize patients in remission in 11 cases (65%) or when a progression was detected in three cases (12%). In four cases no further therapies were administered (16%). Mean follow-up after the end of targeted therapy was 17.1 months. As neoadjuvant regimen, 36% of patients were treated with dabrafenib and trametinib with a near complete radiological response in all the cases with a mean treatment of 5.7 months. The neoadjuvant use of verumafenib (BRAFi) and cometinib (MEK1 inhibitor) induced a near complete response in 15 patients (94%), with a median volumetric reduction between 85% and 91%. Ten patients did not receive further treatments. Side effects varied among studies. The optimal timing, sequencing, and duration of treatment of these new therapies should be established. Moreover, questions remain about the choice of specific BRAF/MEK inhibitors, the optimal protocol of treatment, and the strategies for managing adverse events. Conclusions: Treatment is shifting to a wider multidisciplinary management, where a key role is played by targeted therapies, to improve outcomes and quality of life for patients with BRAF-mutated craniopharyngiomas. Future, larger comparative trials will optimize their protocol of use and integration into multimodal strategies of treatment. [ABSTRACT FROM AUTHOR]

We report on numerical investigation of the electrocaloric effect, an important physical phenomenon in compositionally graded ferroelectric (CGFE) nanowires made of Pb (1 − x) Sr x TiO 3 whose material compositions spatially vary along the longitudinal direction of nanowires. In this study, all numerical evidences are demonstrated through the phase field model based on the Ginzburg–Landau theory. Here, the change of polarization with temperature can be tailored by controlling the gradient of material compositions in CGFE nanowires. The isothermal entropy and adiabatic temperature changes are enhanced with an increasing compositional gradient in CGFE nanowires. The electrocaloric effect is found to have high magnitude near room temperature in CGFE nanowires of PbTiO 3 (top surface)/ SrTiO 3 (bottom surface), which is much larger than that in homogeneous ferroelectric nanowire with the same average material composition. In addition, the high electrocaloric effect in CGFE nanowires of PbTiO 3 / SrTiO 3 is achieved in a wide range near room temperature. We also discuss the potential of CGFE nanowires for electrocaloric cooling applications, and more importantly, this work, in essence, opens a new route to enhance the electrocaloric properties of ferroelectric nanowires near room temperature by controlling the gradient of material compositions. [ABSTRACT FROM AUTHOR]