RESULTS: This study sought to identify the QTLs associated with fatty acid composition and vegetative traits for compactness in the crop. It integrated two interspecific backcross two (BC2) mapping populations to improve the genetic resolution and evaluate the consistency of the QTLs identified. A total 1963 markers (1814 SNPs and 149 SSRs) spanning a total map length of 1793 cM were integrated into a consensus map. For the first time, some QTLs associated with vegetative parameters and carotene content were identified in interspecific hybrids, apart from those associated with fatty acid composition. The analysis identified 8, 3 and 8 genomic loci significantly associated with fatty acids, carotene content and compactness, respectively.
CONCLUSIONS: Major genomic region influencing the traits for compactness and fatty acid composition was identified in the same chromosomal region in the two populations using two methods for QTL detection. Several significant loci influencing compactness, carotene content and FAC were common to both populations, while others were specific to particular genetic backgrounds. It is hoped that the QTLs identified will be useful tools for marker-assisted selection and accelerate the identification of desirable genotypes for breeding.
METHOD: A prospective cross-sectional study was conducted using the validated Smartphone Addiction Scale-Malay version (SAS-M) questionnaire. One-way ANOVA was used to determine the correlation between the PSU among the students categorised by their ethnicity, hand dominance and by their field of study. MLR analysis was applied to predict PSU based on socio-demographic data, usage patterns, psychological factors and fields of study.
RESULTS: A total of 1060 students completed the questionnaire. Most students had some degree of problematic usage of the smartphone. Students used smartphones predominantly to access SNAs, namely Instagram. Longer duration on the smartphone per day, younger age at first using a smartphone and underlying depression carried higher risk of developing PSU, whereas the field of study (science vs. humanities based) did not contribute to an increased risk of developing PSU.
CONCLUSION: Findings from this study can help better inform university administrators about at- risk groups of undergraduate students who may benefit from targeted intervention designed to reduce their addictive behaviour patterns.
RESULTS: The lysis buffer 2 (LB2) has been shown to be the best lysis buffer for DNA extraction from both raw and processed meat samples comparing to other lysis buffers tested. Hence, the LB2 has been found to be ideal to detect meat and porcine DNAs by real-time PCR using pairs of porcine specific primers and universal primers which amplified at 119 bp fragment and 93 bp fragment, respectively. This assay allows detection as low as 0.0001 ng of DNA. Higher efficiency and sensitivity of real-time PCR via a simplified DNA extraction method using LB2 have been observed, as well as a reproducible and high correlation coefficient (R2 = 0.9979) based on the regression analysis of the standard curve have been obtained.
CONCLUSION: This study has established a fast, simple, inexpensive and efficient DNA extraction method that is feasible for raw and processed meat products. This extraction technique allows an accurate DNA detection by real-time PCR and can also be implemented to assist the halal authentication of various meat-based products available in the market. © 2019 Society of Chemical Industry.
Purpose: To determine the level of adherence to opioid analgesics in patients with cancer pain and to identify factors that may influence the adherence.
Patient and Methods: This was a cross-sectional study conducted from March to June 2018 at two tertiary care hospitals in Malaysia. Study instruments consisted of a set of validated questionnaires; the Medication Compliance Questionnaire, Brief Pain Inventory and Pain Opioid Analgesic Beliefs─Cancer scale.
Results: A total of 134 patients participated in this study. The patients' adherence scores ranged from 52-100%. Factors with a moderate, statistically significant negative correlation with adherence were negative effect beliefs (rs= -0.53, p<0.001), pain endurance beliefs (rs = -0.49, p<0.001) and the use of aqueous morphine (rs = -0.26, p=0.002). A multiple linear regression model on these predictors resulted in a final model which accounted for 47.0% of the total variance in adherence (R2 = 0.47, F (7, 126) = 15.75, p<0.001). After controlling for other variables, negative effect beliefs were the strongest contributor to the model (β = -0.39, p<0.001) and uniquely explained 12.3% of the total variance.
Conclusion: The overall adherence to opioid analgesics among Malaysian patients with cancer pain was good. Negative effects beliefs regarding cancer pain and opioids strongly predicted adherence.