A DNA micro-optode for dengue virus detection was developed based on the sandwich hybridization strategy of DNAs on succinimide-functionalized poly(n-butyl acrylate) (poly(nBA-NAS)) microspheres. Gold nanoparticles (AuNPs) with an average diameter of ~20 nm were synthesized using a centrifugation-based method and adsorbed on the submicrometer-sized polyelectrolyte-coated poly(styrene-co-acrylic acid) (PSA) latex particles via an electrostatic method. The AuNP–latex spheres were attached to the thiolated reporter probe (rDNA) by Au–thiol binding to functionalize as an optical gold–latex–rDNA label. The one-step sandwich hybridization recognition involved a pair of a DNA probe, i.e., capture probe (pDNA), and AuNP–PSA reporter label that flanked the target DNA (complementary DNA (cDNA)). The concentration of dengue virus cDNA was optically transduced by immobilized AuNP–PSA–rDNA conjugates as the DNA micro-optode exhibited a violet hue upon the DNA sandwich hybridization reaction, which could be monitored by a fiber-optic reflectance spectrophotometer at 637 nm. The optical genosensor showed a linear reflectance response over a wide cDNA concentration range from 1.0 × 10−21 M to 1.0 × 10−12 M cDNA (R2 = 0.9807) with a limit of detection (LOD) of 1 × 10−29 M. The DNA biosensor was reusable for three consecutive applications after regeneration with mild sodium hydroxide. The sandwich-type optical biosensor was well validated with a molecular reverse transcription polymerase chain reaction (RT-PCR) technique for screening of dengue virus in clinical samples, e.g., serum, urine, and saliva from dengue virus-infected patients under informed consent.
An optical genosensor based on Schiff base complex (Zn2+ salphen) DNA label and acrylic microspheres (AMs) as polymer support of the capturing DNA probe (cpDNA) was developed for dengue virus serotype 2 (DEN-2) detection via reflectance spectrophotometric method. The solid-state optical DNA biosensor showed high selectivity and specificity up to one-base mismatch in the target DNA sequence owing to the salphen chemical structure that is rich in localized electrons, and allowed π-π stacking interaction between stacked base pairs of doublestranded DNA (dsDNA). The reflectometric DNA microsensor demonstrated a broad linear detection range towards DEN-2 DNA from 1 × 10-15 M to 1 × 10−3 M with a low limit of detection (LOD) obtained at 1.21 × 10-16 M. The DNA biosensor gave reproducible optical response with a satisfactory relative standard deviation (RSD) at 3.1%, (n = 3), and the reflectance response was stable even after four regeneration cycles of the DNA biosensor. The optical genosensor was proven comparable with standard reverse transcription polymerase chain reaction (RT-PCR) in detecting DEN-2 genome acquired from clinical samples of serum, urine and saliva of dengue virus infected patients under informed consent. The developed reflectometric DNA biosensor is advantageous in offering an early DEN-2 diagnosis, when fever symptom started to manifest in patient.
Dengue is the main health problem in Malaysia. One of the main causes of dengue is the lack of participation in combating dengue. To improve participation, stakeholder’s engagement is considered the best solution which promotes an effective way of forming good governance. Engagement involves a level of knowledge, awareness, and understanding through past intended behavior. The objective of this study is to assess and compare the level of engagement of stakeholders toward dengue control techniques. A survey was conducted on 399 stakeholders who were selected randomly in the Klang Valley region, Malaysia. Result of the study showed that the stakeholders have a moderate level of engagement on dengue control techniques. The scientists seemed (a) more knowledgeable (4.81) than the public (4.68), (b) more aware (4.80) than the public (4.55), and (c) more intended behavior (4.31) than the public (4.11) to behave accordingly in supporting the implementation of these techniques. This study also identified the level of engagement factor across gender, religion, education level, and age were moderate which were translated to a moderately attached in dengue control techniques. However, one-way multivariate analysis of variance (MANOVA) initially detected no significant differences across demographic factors except religion on stakeholder’s engagement. Therefore, these findings will serve as a benchmark to evaluate stakeholder’s engagement to understand their participation in the implementation of dengue control techniques. Good participation promotes good governance in sustaining healthy life without dengue.
The current study aims to provide a roadmap for future research by analyzing the research structures and trends in scholarly publications related to the status of zinc in public health. Only journal articles published between 1978 and 2022 are included in the refined bibliographical outputs retrieved from the Web of Science (WoS) database. The first section announces findings based on WoS categories, such as discipline heterogeneity, times cited and publications over time, and citation reports. The second section then employs VoSViewer software for bibliometric analysis, which includes a thorough examination of co-authorship among researchers, organizations, and countries and a count of all bibliographic databases among documents. The final section discusses the research’s weaknesses and strengths in zinc status, public health, and potential future directions; 7158 authors contributed to 1730 papers (including 339 with publications, more than three times). “Keen, C.L.” is a researcher with the most publications and a better understanding of zinc status in public health. Meanwhile, the USA has been the epicenter of research on the status of zinc in public health due to the highest percentage of publications with the most citations and collaboration with the rest of the world, with the top institution being the University of California, Davis. Future research can be organized collaboratively based on hot topics from co-occurrence network mapping and bibliographic couplings to improve zinc status and protect public health.
At present, COVID-19 is spreading widely around the world. It causes many health problems, namely, respiratory failure and acute respiratory distress syndrome. Wearable devices have gained popularity by allowing remote COVID-19 detection, contact tracing, and monitoring. In this study, the correlation of photoplethysmogram (PPG) morphology between patients with COVID-19 infection and healthy subjects was investigated. Then, machine learning was used to classify the extracted features between 43 cases and 43 control subjects. The PPG data were collected from 86 subjects based on inclusion and exclusion criteria. The systolic-onset amplitude was 3.72% higher for the case group. However, the time interval of systolic-systolic was 7.69% shorter in the case than in control subjects. In addition, 12 out of 20 features exhibited a significant difference. The top three features included dicrotic-systolic time interval, onset-dicrotic amplitude, and systolic-onset time interval. Nine features extracted by heatmap based on the correlation matrix were fed to discriminant analysis, k-nearest neighbor, decision tree, support vector machine, and artificial neural network (ANN). The ANN showed the best performance with 95.45% accuracy, 100% sensitivity, and 90.91% specificity by using six input features. In this study, a COVID-19 prediction model was developed using multiple PPG features extracted using a low-cost pulse oximeter.
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