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Suspected-target and non-targeted screenings of phosphodiesterase 5 inhibitors in herbal remedies using liquid chromatography-quadrupole time-of-flight-mass spectrometry

Mohd Yusop AY, Xiao L, Fu S

Drug Test Anal, 2021 May;13(5):965-976.
PMID: 32441056 DOI: 10.1002/dta.2861

The lucrative market of herbal remedies spurs rampant adulteration, particularly with pharmaceutical drugs and their unapproved analogues. A comprehensive screening strategy is, therefore, warranted to detect these adulterants and, accordingly, to safeguard public health. This study uses the data-dependent acquisition of liquid chromatography-quadrupole time-of-flight-mass spectrometry (LC-QTOF-MS) to screen phosphodiesterase 5 (PDE5) inhibitors in herbal remedies using suspected-target and non-targeted strategies. For the suspected-target screening, we used a library comprising 95 PDE5 inhibitors. For the non-targeted screening, we adopted top-down and bottom-up approaches to flag novel PDE5 inhibitor analogues based on common fragmentation patterns. LC-QTOF-MS was optimised and validated for capsule and tablet dosage forms using 23 target analytes, selected to represent different groups of PDE5 inhibitors. The method exhibited excellent specificity and linearity with limit of detection and limit of quantification of <40 and 80 ng/mL, respectively. The accuracy ranged from 79.0% to 124.7% with a precision of <14.9% relative standard deviation. The modified, quick, easy, cheap, effective, rugged, and safe extraction provided insignificant matrix effect within -9.1%-8.0% and satisfactory extraction recovery of 71.5%-105.8%. These strategies were used to screen 52 herbal remedy samples that claimed to enhance male sexual performance. The suspected-target screening resulted in 33 positive samples, revealing 10 target analytes and 2 suspected analytes. Systematic MS and tandem MS interrogations using the non-targeted screening returned insignificant signals, indicating the absence of potentially novel analogues. The target analytes were quantified from 0.03 to 121.31 mg per dose of each sample. The proposed strategies ensure that all PDE5 inhibitors are comprehensively screened, providing a useful tool to curb the widespread adulteration of herbal remedies.

Matched MeSH terms: Data Collection
International stroke genetics consortium recommendations for studies of genetics of stroke outcome and recovery

Lindgren AG, Braun RG, Juhl Majersik J, Clatworthy P, Mainali S, Derdeyn CP, et al.

Int J Stroke, 2021 Apr 26.
PMID: 33739214 DOI: 10.1177/17474930211007288

Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.

Matched MeSH terms: Data Collection
Fulltext Design of Experiment on Concrete Mechanical Properties Prediction: A Critical Review

Chong BW, Othman R, Putra Jaya R, Mohd Hasan MR, Sandu AV, Nabiałek M, et al.

Materials (Basel), 2021 Apr 09;14(8).
PMID: 33918757 DOI: 10.3390/ma14081866

Concrete mix design and the determination of concrete performance are not merely engineering studies, but also mathematical and statistical endeavors. The study of concrete mechanical properties involves a myriad of factors, including, but not limited to, the amount of each constituent material and its proportion, the type and dosage of chemical additives, and the inclusion of different waste materials. The number of factors and combinations make it difficult, or outright impossible, to formulate an expression of concrete performance through sheer experimentation. Hence, design of experiment has become a part of studies, involving concrete with material addition or replacement. This paper reviewed common design of experimental methods, implemented by past studies, which looked into the analysis of concrete performance. Several analysis methods were employed to optimize data collection and data analysis, such as analysis of variance (ANOVA), regression, Taguchi method, Response Surface Methodology, and Artificial Neural Network. It can be concluded that the use of statistical analysis is helpful for concrete material research, and all the reviewed designs of experimental methods are helpful in simplifying the work and saving time, while providing accurate prediction of concrete mechanical performance.

Matched MeSH terms: Data Collection
Fulltext Review of Recent Microwave Planar Resonator-Based Sensors: Techniques of Complex Permittivity Extraction, Applications, Open Challenges and Future Research Directions

Alahnomi RA, Zakaria Z, Yussof ZM, Althuwayb AA, Alhegazi A, Alsariera H, et al.

Sensors (Basel), 2021 Mar 24;21(7).
PMID: 33804904 DOI: 10.3390/s21072267

Recent developments in the field of microwave planar sensors have led to a renewed interest in industrial, chemical, biological and medical applications that are capable of performing real-time and non-invasive measurement of material properties. Among the plausible advantages of microwave planar sensors is that they have a compact size, a low cost and the ease of fabrication and integration compared to prevailing sensors. However, some of their main drawbacks can be considered that restrict their usage and limit the range of applications such as their sensitivity and selectivity. The development of high-sensitivity microwave planar sensors is required for highly accurate complex permittivity measurements to monitor the small variations among different material samples. Therefore, the purpose of this paper is to review recent research on the development of microwave planar sensors and further challenges of their sensitivity and selectivity. Furthermore, the techniques of the complex permittivity extraction (real and imaginary parts) are discussed based on the different approaches of mathematical models. The outcomes of this review may facilitate improvements of and an alternative solution for the enhancement of microwave planar sensors' normalized sensitivity for material characterization, especially in biochemical and beverage industry applications.

Matched MeSH terms: Data Collection
Advancements in the preparation and application of monolithic silica columns for efficient separation in liquid chromatography

Khoo HT, Leow CH

Talanta, 2021 Mar 01;224:121777.
PMID: 33379011 DOI: 10.1016/j.talanta.2020.121777

Fast and efficient separation remains a big challenge in high performance liquid chromatography (HPLC). The need for higher efficiency and resolution in separation is constantly in demand. To achieve that, columns developed are rapidly moving towards having smaller particle sizes and internal diameters (i.d.). However, these parameters will lead to high back-pressure in the system and will burden the pumps of the HPLC instrument. To address this limitation, monolithic columns, especially silica-based monolithic columns have been introduced. These columns are being widely investigated for fast and efficient separation of a wide range of molecules. The present article describes the current methods developed to enhance the column efficiency of particle packed columns and how silica monolithic columns can act as an alternative in overcoming the low permeability of particle packed columns. The fundamental processes behind the fabrication of the monolith including the starting materials and the silica sol-gel process will be discussed. Different monolith derivatization and end-capping processes will be further elaborated and followed by highlights of the performance such monolithic columns in key applications in different fields with various types of matrices.

Matched MeSH terms: Data Collection
A portable electrochemical sensor for detection of the veterinary drug xylazine in beverage samples

Saisahas K, Soleh A, Promsuwan K, Phonchai A, Mohamed Sadiq NS, Teoh WK, et al.

J Pharm Biomed Anal, 2021 Feb 08;198:113958.
PMID: 33662759 DOI: 10.1016/j.jpba.2021.113958

A portable electrochemical sensor was developed to determine xylazine in spiked beverages by adsorptive stripping voltammetry (AdSV). The sensor was based on a graphene nanoplatelets-modified screen-printed carbon electrode (GNPs/SPCE). The electrochemical behavior of xylazine at the GNPs/SPCE was an adsorption-controlled irreversible oxidation reaction. The loading of graphene nanoplatelets (GNPs) on the modified SPCE, electrolyte pH, and AdSV accumulation potential and time were optimized. Under optimal conditions, the GNPs/SPCE provided high sensitivity, linear ranges of 0.4-6.0 mg L-1 (r = 0.997) and 6.0-80.0 mg L-1 (r = 0.998) with a detection limit of 0.1 mg L-1 and a quantitation limit of 0.4 mg L-1. Repeatability was good. The accuracy of the proposed sensor was investigated by spiking six beverage samples at 1.0, 5.0, and 10.0 mg L-1. The recoveries from this method ranged from 80.8 ± 0.2-108.1 ± 0.3 %, indicating the good accuracy of the developed sensor. This portable electrochemical sensor can be used to screen for xylazine in beverage samples as evidence in cases of sexual assault or robbery.

Matched MeSH terms: Data Collection
Quantification of atovaquone from amorphous solid dispersion formulation using HPLC: An in vitro and ex vivo investigation

Teoh XY, Goh CF, Aminu N, Chan SY

J Pharm Biomed Anal, 2021 Jan 05;192:113631.
PMID: 33011581 DOI: 10.1016/j.jpba.2020.113631

Atovaquone (ATQ) is a poorly soluble drug. Therefore, formulating ATQ into its supersaturated state through solid dispersion for bioavailability enhancement can be of great value. However, due to fast crystallising properties of ATQ, the quantification of ATQ in a supersaturated solid dispersion system can be complicated. Therefore, in pursuit of accurate quantification of such sample, a simple HPLC analytical method utilising a C18 column (250 × 4.6 mm ID, 5 μm) for the quantitation of ATQ has been developed and validated. Atovaquone elution using the proposed method demonstrated a retention time around 7.6 min with good linearity (R2 > 0.999). The system suitability is also detailed with the tailing factor at 1.365 ± 0.002. The addition of solubilising agent as sample treatment step aided in ensuring the accurate quantitation of the fast crystallising ATQ. The developed HPLC quantitation method has been successfully employed in the analysis of ATQ from solid dispersion samples in in vitro dissolution as well as ex vivo permeation studies for formulation development.

Matched MeSH terms: Data Collection
Fulltext The Trend of Direct Medical Cost of Meliodiosis Patients in Kedah: A Retrospective Study from 2014 to 2017

Mardhiah K, Wan-Arfah N, Naing NN, Abu Hassan MR, Chan HK, Hasan H

Clinicoecon Outcomes Res, 2021;13:155-162.
PMID: 33732004 DOI: 10.2147/CEOR.S286283

Purpose: This study was conducted to determine the direct medical cost of treating melioidosis patients. The calculation was made according to the variables extracted from medical records.
Materials and Methods: Data collection was performed retrospectively on a total of 293 cases from Hospital Sultanah Bahiyah, Kedah, Malaysia. The data consisted of personal information, treatment history, and investigation findings, including blood results, USG abdomen results, and CT scan results. The site of culture and sensitivity were also obtained. The total direct medical cost was based on the antibiotics/treatments received by the patients, diagnostic test and investigations performed. The trend analysis used to see the pattern of costs from 2014 to 2017. All the costs were compared based on patients' status and duration of stay at the hospital using the independent t-test.
Results: The overall mean of direct medical cost for melioidosis amounted to US $233.61 (RM931.33). Overall, the finding confirms a huge reduction (44.7%) of direct medical cost from 2014 to 2017 (P = 0.001). From 2015 to 2016, there was a 19.1% reduction of direct medical cost (P>0.95), followed by a 38.8% reduction in costs from 2016 to 2017 (P = 0.019). In the case of the duration of stay, the mean of total direct medical cost among patients with ≥14 duration of stay was higher compared to those with <14 duration of stay (p < 0.001). There was no significant mean difference of direct medical cost between patients who were cured and died.
Conclusion: Despite the higher mortality of melioidosis cases compared to other infectious diseases, there is a limitation in the amount of published data on the management cost of melioidosis. The importance of cost in managing this disease should be underlined to perform a fully prepared management toward the disease.

Matched MeSH terms: Data Collection
RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI

Jing W, Tao H, Rahman MA, Kabir MN, Yafeng L, Zhang R, et al.

Work, 2021;68(3):923-934.
PMID: 33612534 DOI: 10.3233/WOR-203426

BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system.
OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.
RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.
CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate.

Matched MeSH terms: Data Collection
ADA-SR: Activity detection and analysis using security robots for reliable workplace safety

Zhang G, Jing W, Tao H, Rahman MA, Salih SQ, Al-Saffar A, et al.

Work, 2021;68(3):935-943.
PMID: 33612535 DOI: 10.3233/WOR-203427

BACKGROUND: Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.

Matched MeSH terms: Data Collection
Interaction modeling and classification scheme for augmenting the response accuracy of human-robot interaction systems

Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.

Work, 2021;68(3):903-912.
PMID: 33720867 DOI: 10.3233/WOR-203424

BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.
OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.
RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.
CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

Matched MeSH terms: Data Collection
Fulltext FNG-IE: an improved graph-based method for keyword extraction from scholarly big-data

Tahir N, Asif M, Ahmad S, Malik MSA, Aljuaid H, Butt MA, et al.

PeerJ Comput Sci, 2021;7:e389.
PMID: 33817035 DOI: 10.7717/peerj-cs.389

Keyword extraction is essential in determining influenced keywords from huge documents as the research repositories are becoming massive in volume day by day. The research community is drowning in data and starving for information. The keywords are the words that describe the theme of the whole document in a precise way by consisting of just a few words. Furthermore, many state-of-the-art approaches are available for keyword extraction from a huge collection of documents and are classified into three types, the statistical approaches, machine learning, and graph-based methods. The machine learning approaches require a large training dataset that needs to be developed manually by domain experts, which sometimes is difficult to produce while determining influenced keywords. However, this research focused on enhancing state-of-the-art graph-based methods to extract keywords when the training dataset is unavailable. This research first converted the handcrafted dataset, collected from impact factor journals into n-grams combinations, ranging from unigram to pentagram and also enhanced traditional graph-based approaches. The experiment was conducted on a handcrafted dataset, and all methods were applied on it. Domain experts performed the user study to evaluate the results. The results were observed from every method and were evaluated with the user study using precision, recall and f-measure as evaluation matrices. The results showed that the proposed method (FNG-IE) performed well and scored near the machine learning approaches score.

Matched MeSH terms: Data Collection
Fulltext Development of Automatic Reminder System for Geriatric Medicine Intake

Aisyah Rahimi, Hamimi Zakri, Azira Khalil

Malaysian Journal of Science, Health & Technology, 2021;7(1):8-14.
MyJurnal

The consumption of medicine is typical in geriatrics, having many problems related to medications. Geriatrics often forget to take their medicine, and this problem can be overcome by using an automatic reminder system. In this study, an automated reminder system is developed as an improved community element, acting as a system that can help geriatric in taking their medicine on time, thus, boosting their health condition. This reminder system also includes an interaction between the geriatrics and their caretakers. This reminder system includes Arduino UNO as the microcontroller, with the notification system, Blynk Application, a buzzer, and a light-emitting diode (LED) system. To make this reminder system more versatile, the buzzer will alarm during the medicine intake time, giving information to the elderly on which medicine to take. When the time has reached to take medication, the buzzer will produce a sound. Suppose the medicine box opens after the buzzer's sound and is detected by the passive infrared sensor (PIR sensor). In that case, the caretaker will receive a notification through the Blynk application that the geriatric already took medicine. On the contrary, if the medicine box is not open after 3 minutes following the buzzer's sound, which indicates that the geriatric did not take their medicine, the system will not send a notification to their caretakers on the status. This prototype is tested on ten users for its accuracy and effectiveness. It is believed that this system can provide geriatrics more alert in taking their medicine on time, enhancing their health status.

Matched MeSH terms: Data Collection
Fulltext Ph Monitoring for Liquid Fertilizer Management in Black Pepper Farming

Kedung Fletcher, Anding Nyuak, Tan Phei Yee

International Journal of Innovation and Industrial Revolution, 2021;3(6):1-12.
MyJurnal

There is lacking technology application in black pepper farming to automate daily routine activities in monitoring black pepper vines growth and nutrient need. With the revolution of Industry 4.0 (IR4.0), and tremendous improvement in the internet of things (IoT), the application of precision agriculture to pepper farming is a thing to consider for its benefit. This paper to explore the use of IoT to monitor fertilizer requirement for pepper vines using pH sensor. The pH sensor attached to Raspberry Pi 3 will be collecting the data and forwarding it to the cloud database for farmer reference and take decision based on data presented in form of a digital report from the database. The Python environment provides the space for coding in Raspberry Pi. SQL and PHP software is used to design the user interface and data management in the relational database management system. The information about pH provides a better understanding of how pH parameter affects the growth of pepper vines. The farmer will be able to access the information anywhere and anytime. Therefore, our proposed system will greatly help the pepper farmers in Sarawak in managing the usage of fertilizer as a way to minimize farm inputs, thus increase their profit.

Matched MeSH terms: Data Collection
Impact of Pharmacist-led Educational Intervention on Predictors of Diabetic Foot at Two Different Hospitals of Malaysia

Khan AH, Iqbal MZ, Syed Sulaiman SA, Ibrahim A, Azmi NSBY, Iqbal MS, et al.

J Pharm Bioallied Sci, 2020 12 21;13(1):108-115.
PMID: 34084056 DOI: 10.4103/jpbs.JPBS_475_20

Objective: Diabetes mellitus (DM) is a chronic metabolic disorder that can initiate organ damage inside the body if not treated appropriately. Apart from tight glycemic control, a suitable educational intervention is also needed from health-care providers to stop or decrease the progression of organ damage in diabetic patients. This study intended to measure the impact of pharmacist-led educational intervention on improvement in predictors of diabetic foot in two different hospitals in Malaysia.
Materials and Methods: In two tertiary care selected hospitals, the included diabetic patients were randomly divided into two study arms. In the control group, 200 patients who were receiving usual treatment from hospitals were included. However, in the intervention group, those 200 patients who were receiving usual treatment along with counseling sessions from pharmacists under the Diabetes Medication Therapy Adherence Clinic (DMTAC) program were included. The study continued for 1 year, and there were four follow-up visits for both study arms. A prevalidated data collection form was used to measure the improvement in predictors of diabetic foot in included patients. Data were analyzed by using the Statistical Package for the Social Sciences (SPSS) software program, version 24.0.
Results: With the average decrease of 1.97% of HbA1c values in the control group and 3.43% in the intervention group, the univariate and multivariate analysis showed a statistically significant difference between both of the study arms in the improvement of predictors belonging to the diabetic foot (P < 0.05). The proportion of patients without any signs and symptoms of the diabetic foot in the intervention group was 91.7%, which increased from 42.3% at baseline (P < 0.05). However, this proportion in the control group was 76.9% at the fourth follow-up, from 48.3% at baseline (P < 0.05).
Conclusion: A statistically significant reduction in the signs and symptoms of diabetic foot was observed in the intervention group at the end of 1 year. The progression of diabetic foot was significantly decreased in the pharmacist intervention group.

Matched MeSH terms: Data Collection
Fulltext A Multi-Sensor Comparative Analysis on the Suitability of Generated DEM from Sentinel-1 SAR Interferometry Using Statistical and Hydrological Models

Mohammadi A, Karimzadeh S, Jalal SJ, Kamran KV, Shahabi H, Homayouni S, et al.

Sensors (Basel), 2020 Dec 16;20(24).
PMID: 33339435 DOI: 10.3390/s20247214

Digital elevation model (DEM) plays a vital role in hydrological modelling and environmental studies. Many essential layers can be extracted from this land surface information, including slope, aspect, rivers, and curvature. Therefore, DEM quality and accuracy will affect the extracted features and the whole process of modeling. Despite freely available DEMs from various sources, many researchers generate this information for their areas from various observations. Sentinal-1 synthetic aperture radar (SAR) images are among the best Earth observations for DEM generation thanks to their availabilities, high-resolution, and C-band sensitivity to surface structure. This paper presents a comparative study, from a hydrological point of view, on the quality and reliability of the DEMs generated from Sentinel-1 data and DEMs from other sources such as AIRSAR, ALOS-PALSAR, TanDEM-X, and SRTM. To this end, pair of Sentinel-1 data were acquired and processed using the SAR interferometry technique to produce a DEM for two different study areas of a part of the Cameron Highlands, Pahang, Malaysia, a part of Sanandaj, Iran. Based on the estimated linear regression and standard errors, generating DEM from Sentinel-1 did not yield promising results. The river streams for all DEMs were extracted using geospatial analysis tool in a geographic information system (GIS) environment. The results indicated that because of the higher spatial resolution (compared to SRTM and TanDEM-X), more stream orders were delineated from AIRSAR and Sentinel-1 DEMs. Due to the shorter perpendicular baseline, the phase decorrelation in the created DEM resulted in a lot of noise. At the same time, results from ground control points (GCPs) showed that the created DEM from Sentinel-1 is not promising. Therefore, other DEMs' performance, such as 90-meters' TanDEM-X and 30-meters' SRTM, are better than Sentinel-1 DEM (with a better spatial resolution).

Matched MeSH terms: Data Collection
Breakfast consumption and mental health: a systematic review and meta-analysis of observational studies

Zahedi H, Djalalinia S, Sadeghi O, Zare Garizi F, Asayesh H, Payab M, et al.

Nutr Neurosci, 2020 Dec 14.
PMID: 33314992 DOI: 10.1080/1028415X.2020.1853411

OBJECTIVE: Several studies have been conducted on the relationship between breakfast consumption and mental health with conflicting results. Therefore, the present systematic review and meta-analysis was undertaken to summarize evidences on the association between skipping breakfast and mental health.
METHODS: We searched online databases for all related papers through the comprehensive international data bases of Institute of PubMed/ MEDLINE, ISI/WOS and Scopus up to December 2019, using relevant keywords. Overall, 14 studies were included in this systematic review and meta-analysis.
RESULTS: The total sample size of all selected studies was 399,550 individuals with age range of 6 to ≥65 years old. We found a significant positive association between skipping breakfast and Odds Ratio (OR) of depression (pooled OR: 1.39; 95% CI: 1.34-1.44), stress (pooled OR: 1.23; 95% CI: 1.04-1.43) and psychological distress (pooled OR: 1.55; 95% CI: 1.47-1.62). In contrast, there was no significant association between skipping breakfast and anxiety in all age cohort (pooled OR: 1.31; 95% CI: 0.97-1.65). However, subgroup analysis based on age stratification showed that there was a significant positive association between skipping breakfast and anxiety in adolescences (pooled OR: 1.51; 95% CI: 1.25-1.77).
CONCLUSION: In conclusion, skipping breakfast was positively associated with odds of depression, stress and psychological distress in all age groups and anxiety in adolescence, underlining impact of breakfast on mental health.

Matched MeSH terms: Data Collection
Fulltext Patients' Perception Towards Health Education Services Received at the Enhanced Primary Healthcare Facilities: A Qualitative Exploration

Jaafar N, Perialathan K, Zulkepli MZ, Mohd Zin Z, Jonoi PE, Johari MZ

J Prim Care Community Health, 2020 12 11;11:2150132720980629.
PMID: 33300405 DOI: 10.1177/2150132720980629

BACKGROUND: The present Malaysian healthcare system is burdened with increasing cases of non-communicable diseases (NCDs) and its risk factors. Health care providers (HCPs) have to provide both treatment and health education to ensure optimal outcome. Health education is a vital component in addressing and managing chronic diseases. This study intends to explore patient's perspective on health education services received from HCPs, focusing at the secondary triage in government primary healthcare facilities.
METHODS: This qualitative exploratory study focused on the health education component derived from a complex enhanced primary health care intervention. Participants were purposively selected from patients who attended regular NCD treatment at 8 primary healthcare facilities in rural and urban areas of Johor and Selangor. Data collection was conducted between April 2017 and April 2018. Individual semi-structured interviews were conducted on 4 to 5 patients at each intervention clinic. Interviews were transcribed verbatim, coded and analyzed using a thematic analysis approach.
RESULTS: A total of 35 patients participated. Through thematic analysis, 2 main themes emerged; Perceived Suitability and Preferred HCPs. Under Perceived Suitability theme, increased waiting time and unsuitable location emerged as sub-themes. Under Preferred HCPs, emerging sub-themes were professional credibility, continuity of care, message fatigue, and interpersonal relationship. There are both positive and adverse acceptances toward health education delivered by HCPs. It should be noted that acceptance level for health information received from doctors are much more positively accepted compared to other HCPs.
CONCLUSION: Patients are willing to engage with health educators when their needs are addressed. Revision of current location, process and policy of health education delivery is needed to capture patients' attention and increase awareness of healthy living with NCDs. HCPs should continuously enhance knowledge and skills, which are essential to improve development and progressively becoming the expert educator in their respective specialized field.

Matched MeSH terms: Data Collection
Fulltext Systematical study of multi-walled carbon nanotube nanofluids based disposed transformer oil

Suhaimi NS, Md Din MF, Ishak MT, Abdul Rahman AR, Mohd Ariffin M, Hashim N', et al.

Sci Rep, 2020 Dec 02;10(1):20984.
PMID: 33268816 DOI: 10.1038/s41598-020-77810-8

In this paper, the electrical, dielectric, Raman and small angle X-ray scattering (SAXS) structure behavior of disposed transformer oil in the presence of multi-walled carbon nanotube (MWCNT) were systematically tested to verify their versatility for preparing better alternative transformer oil in future. MWCNT nanofluids are prepared using a two-step method with concentrations ranging from 0.00 to 0.02 g/L. The test results reveal that 0.005 g/L concentration possesses the most optimum performance based on the electrical (AC breakdown and lightning impulse) and dielectric (permittivity, dissipation factor and resistivity) behavior. According to the trend of AC breakdown strength and lightning impulse pattern, there were 212.58% and 40.01% enhancement indicated for 0.005 g/L concentration compared to the disposed transformer oil. The presence of MWCNT also yielding to the decrement of dissipation factor, increased on permittivity and resistivity behavior of disposed transformer oil which reflected to the performance of electrical properties. Furthermore, it is found that these features correlated to the structural properties as systematically verify by Raman and SAXS analysis study.

Matched MeSH terms: Data Collection
Fulltext A Review on COVID-19 Mediated Impacts and Risk Mitigation Strategies for Dental Health Professionals

Sharma S, Parolia A, Kanagasingam S

Eur J Dent, 2020 Dec;14(S 01):S159-S164.
PMID: 33167046 DOI: 10.1055/s-0040-1718240

In the light of coronavirus disease 2019 (COVID-19), dentistry is facing unprecedented challenges. The closure of clinics has impacted dental health professionals (DHPs) not only financially but also psychologically. In this review, these consequences are discussed in detail to highlight the challenges that DHPs are facing thus far, in both developing and developed nations. Compromised mental health among DHPs is an important area that requires attention during this difficult period. Although, in previous pandemics, dentists have not worked on the frontline, the article discusses how their wide range of skillsets can be leveraged if another wave of COVID-19 pandemic appears. Finally, guidelines to reopen clinics and patient management have been discussed in detail that could serve as a quick reference guide for DHPs.

Matched MeSH terms: Data Collection

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