METHODOLOGY: This study was approved by the institutional Joint Research and Ethics Committee, International Medical University, Malaysia (number 373/2016); consisted of 180 eligible pre-school children from a private school. Study tools included demographic, clinical oral health data form, the Early Childhood Oral Health Impact Scale (ECOHIS) and family functioning-12-item general functioning subscale. Written consent was sought prior to data collection. Data were analysed by SPSS v.22.0; descriptive statistics for socio-demographic details, clinical information, HRQoL and FAD scores. The parametric tests included independent sample t test and ANOVA to evaluate the associations between the dependent variable. Binary logistic regression models were applied to assess the impacts on OHRQoL (P value
METHODS: A modified Students Motivation towards Science Learning (SMTSL) was used to assess the digital learning usage and learning motivation among 150 UKM and 147 SUMS medical students throughout Year 1 to 5.
RESULTS: The frequency of digital learning usage and learning motivation among UKM medical students was significantly higher as compared to SUMS (p
OBJECTIVE: Investigate the literature available in the use of DL technology to support dealing with the COVID-19 crisis. We summarize the literature that uses DL features to analyze datasets for the purpose of a quick COVID-19 detection.
METHODS: This review follows PRISMA Extension for Scoping Reviews (PRISMA-ScR). We have scanned the most two commonly used databases (IEEE, ACM). Search terms were identified based on the target intervention (DL) and the target population (COVID-19). Two authors independently handled study selection and one author assigned for data extraction. A narrative approach is used to synthesize the extracted data.
RESULTS: We retrieved 53 studies and after passing through PRISMA excluding criteria, only 17 studies are considered in this review. All studies used deep learning for detection of COVID-19 cases in early stage based on different diagnostic modalities. Convolutional Neural Network (CNN) and Transfer Learning (TL) were the most commonly used techniques.
CONCLUSION: The included studies showed that DL techniques has significant impact on early detection of COVID-19 with high accuracy rate. However, most of the proposed methods are still in development and not tested in a clinical setting. Further investigation and collaboration are required from the research community and healthcare professionals in order to develop and standardize guidelines for use of DL in the healthcare domain.
METHODS: Thirty-two adult cadaveric legs were disarticulated at the knee and unpaired. STA was performed on each specimen. The anatomy and distribution of the sural nerve and its branches were identified in relation to the incision. Three surgical windows were identified and selected. Kirshner wires were inserted in pairs via each of the windows towards the center of the sustentaculum tali. The safe angle for wire insertion in relation to the SN or its branches was then measured as well as the appropriate intraoperative drilling angle.
RESULTS: The plantar branch presented in the distal window in none of the samples, while the dorsal branches presented in 37.5% and the main SN presented in only 6.25%. In the middle window, the dorsal branch presented most often (43.75%) followed by the plantar branch (25.00%) and the SN (21.88%). In the proximal window, the SN presented in 100% of the samples, while the dorsal branch presented in none and the plantar branch presented in about 15.63% of the specimens. All three windows had their own acceptable average angle for screw insertion towards the sustentaculum tali.
CONCLUSIONS: The distal window is the safest for surgical approach and for calcaneal surgery screw fixation in terms of avoiding sural nerve injury. In addition, that window provides a wide working angle for screw fixation.
OBJECTIVE: This study investigates the antidiabetic and antioxidant effects of M. latifolia bark extracts, fractions, and isolated constituents.
MATERIALS AND METHODS: Melicope latifolia extracts (hexane, chloroform, and methanol), fractions, and isolated constituents with varying concentrations (0.078-10 mg/mL) were subjected to in vitro α-amylase and dipeptidyl peptidase-4 (DPP-4) inhibitory assay. Molecular docking was performed to study the binding mechanism of active compounds towards α-amylase and DPP-4 enzymes. The antioxidant activity of M. latifolia fractions and compounds were determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging and β-carotene bleaching assays.
RESULTS: Melicope latifolia chloroform extract showed the highest antidiabetic activity (α-amylase IC50: 1464.32 μg/mL; DPP-4 IC50: 221.58 μg/mL). Fractionation of chloroform extract yielded four major fractions (CF1-CF4) whereby CF3 showed the highest antidiabetic activity (α-amylase IC50: 397.68 μg/mL; DPP-4 IC50: 37.16 μg/mL) and resulted in β-sitosterol (1), halfordin (2), methyl p-coumarate (3), and protocatechuic acid (4). Isolation of compounds 2-4 from the species and their DPP-4 inhibitory were reported for the first time. Compound 2 showed the highest α-amylase (IC50: 197.53 μM) and β-carotene (88.48%) inhibition, and formed the highest number of molecular interactions with critical amino acid residues of α-amylase. The highest DPP-4 inhibition was exhibited by compound 3 (IC50: 911.44 μM).
DISCUSSION AND CONCLUSIONS: The in vitro and in silico analyses indicated the potential of M. latifolia as an alternative source of α-amylase and DPP-4 inhibitors. Further pharmacological studies on the compounds are recommended.