RESULTS: In this research, chili pest and disease features extracted using the traditional approach were compared with features extracted using a deep-learning-based approach. A total of 974 chili leaf images were collected, which consisted of five types of diseases, two types of pest infestations, and a healthy type. Six traditional feature-based approaches and six deep-learning feature-based approaches were used to extract significant pests and disease features from the chili leaf images. The extracted features were fed into three machine learning classifiers, namely a support vector machine (SVM), a random forest (RF), and an artificial neural network (ANN) for the identification task. The results showed that deep learning feature-based approaches performed better than the traditional feature-based approaches. The best accuracy of 92.10% was obtained with the SVM classifier.
CONCLUSION: A deep-learning feature-based approach could capture the details and characteristics between different types of chili pests and diseases even though they possessed similar visual patterns and symptoms. © 2020 Society of Chemical Industry.
METHOD: One hundred and twenty male C57BL/6 inbred mice were divided into three age groups: young (6 months old), middle-aged (12 months old), and old (18 months old). Each age group consisted of two control groups (distilled water and olive oil) and three treatment groups: Piper betle (50 mg/kg body weight), tocotrienol-rich fraction (30 mg/kg), and Chlorella vulgaris (50 mg/kg). The duration of treatment for all three age groups was two months. Blood was withdrawn from the orbital sinus to determine the antioxidant enzyme activity and the malondialdehyde level.
RESULTS: Piper betle increased the activities of catalase, glutathione peroxidase, and superoxide dismutase in the young, middle, and old age groups, respectively, when compared to control. The tocotrienol-rich fraction decreased the superoxide dismutase activity in the middle and the old age groups but had no effect on catalase or glutathione peroxidase activity for all age groups. Chlorella vulgaris had no effect on superoxide dismutase activity for all age groups but increased glutathione peroxidase and decreased catalase activity in the middle and the young age groups, respectively. Chlorella vulgaris reduced lipid peroxidation (malondialdehyde levels) in all age groups, but no significant changes were observed with the tocotrienol-rich fraction and the Piper betle treatments.
CONCLUSION: We found equivocal age-related changes in erythrocyte antioxidant enzyme activity when mice were treated with Piper betle, the tocotrienol-rich fraction, and Chlorella vulgaris. However, Piper betle treatment showed increased antioxidant enzymes activity during aging.
METHODS: The Mainstreaming Genetic Counselling for Ovarian Cancer Patients (MaGiC) study is a prospective, two-arm observational study comparing oncologist-led and genetics-led counselling. This study included 790 multiethnic patients with ovarian cancer from 23 sites in Malaysia. We compared the impact of different method of delivery of genetic counselling on the uptake of genetic testing and assessed the feasibility, knowledge and satisfaction of patients with ovarian cancer.
RESULTS: Oncologists were satisfied with the mainstreaming experience, with 95% indicating a desire to incorporate testing into their clinical practice. The uptake of genetic testing was similar in the mainstreaming and genetics arm (80% and 79%, respectively). Patient satisfaction was high, whereas decision conflict and psychological impact were low in both arms of the study. Notably, decisional conflict, although lower than threshold, was higher for the mainstreaming group compared with the genetics arm. Overall, 13.5% of patients had a pathogenic variant in BRCA1 or BRCA2, and there was no difference between psychosocial measures for carriers in both arms.
CONCLUSION: The MaGiC study demonstrates that mainstreaming cancer genetics is feasible in low-resource and middle-resource Asian setting and increased coverage for genetic testing.