Methods: A cross-sectional analytical observational study was conducted among 380 secondary school teachers in Kelantan, Malaysia. A self-administered questionnaire addressing sociodemographic data and factors influencing CVD screening activities was administered. Descriptive analysis, simple and multiple logistic regression analyses were performed.
Results: A total of 348 teachers responded to the questionnaire, with a response rate of 91.6%. The prevalence of optimal CVD screening activities was 29.3% (95% CI: 24.52, 34.08). Age, knowledge of CVD screening, family history of CVD and availability of health facilities were significantly linked to CVD screening.
Conclusion: The prevalence of optimal screening activities was low. A great majority of the factors contributing to optimal screening were modifiable. Health care providers should widely implement global health-oriented rather than disease-orientated assessment in their daily practice.
METHODS: In this paper, we analyze four wide-spread deep learning models designed for the segmentation of three retinal fluids outputting dense predictions in the RETOUCH challenge data. We aim to demonstrate how a patch-based approach could push the performance for each method. Besides, we also evaluate the methods using the OPTIMA challenge dataset for generalizing network performance. The analysis is driven into two sections: the comparison between the four approaches and the significance of patching the images.
RESULTS: The performance of networks trained on the RETOUCH dataset is higher than human performance. The analysis further generalized the performance of the best network obtained by fine-tuning it and achieved a mean Dice similarity coefficient (DSC) of 0.85. Out of the three types of fluids, intraretinal fluid (IRF) is more recognized, and the highest DSC value of 0.922 is achieved using Spectralis dataset. Additionally, the highest average DSC score is 0.84, which is achieved by PaDeeplabv3+ model using Cirrus dataset.
CONCLUSIONS: The proposed method segments the three fluids in the retina with high DSC value. Fine-tuning the networks trained on the RETOUCH dataset makes the network perform better and faster than training from scratch. Enriching the networks with inputting a variety of shapes by extracting patches helped to segment the fluids better than using a full image.
RESULTS: All aqueous enzymatic extraction (AEE)-based methods generally resulted in oil with better oxidative properties and higher tocopherol retention than the use of solvent. Prior to AEE, boiling pre-treatment deactivated the hydrolytic enzymes and preserved the oil's quality. In contrast, high-pressure processing (HPP) pre-treatment accelerated hydrolytic reaction and resulted in an increase in free fatty acids after 140 days at all temperatures. No significant changes were detected in the oils' iodine values and fatty acid composition. The tocopherol content decreased significantly at both 13 and 25 °C after 60 days in the oil from SE method, and after 120 days in oils from AEE-based methods.
CONCLUSION: These findings are significant in highlighting the extraction methods resulting in crude MO kernel oil with greatest oxidative stability in the storage conditions tested. Subsequently, the suitable storage condition of the oil prior to refining can be determined. Further studies are recommended in determining the suitable refining processes and parameters for the MO kernel oil prior to application in variety food products. © 2019 Society of Chemical Industry.
METHODS: Clinical records of active opioid dependents who underwent MMT between 1 January 2007 and 31 March 2021 in Hospital Tuanku Fauziah, Perlis, Malaysia were retrospectively reviewed. Data collected included baseline demographics, history of illicit drug use, temporal trend in methadone dosage modulation, and co-use of illicit drugs during the MMT.
RESULTS: A total of 87 patients (mean age, 43.9 ± 8.33 years) were included. Their mean duration of involvement in MMT was 7.8 ± 3.69 years. The most commonly used drug was heroin (88.5%), followed by kratom (51.7%). Between 2019 and 2021, 61 (70.1%) patients had ceased abusing opioid, but 51 (58.6%) patients continued using any of the illicit drugs. Methamphetamine and amphetamine co-use was most common (n = 12, 37.5%). Hepatitis C status was not associated with the current methadone dose (U = 539.5, p = 0.186) or the highest dose required (t = -0.291, df = 74, p = 0.772). No predictor for illicit drug abstinence during MMT was identified. Methadone dose positively correlated with frequency of defaulting treatments (r = 0.22, p = 0.042).
CONCLUSION: Among our patients, MMT for opioid dependents cannot sufficiently curb illicit drug use, and there is a shift toward stimulants abuse.