Automated MRI-Based Deep Learning Model for Detection of Alzheimer's Disease Process.

In the context of neuro-pathological disorders, neuroimaging has been widely accepted as a clinical tool for diagnosing patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). The advanced deep learning method, a novel brain imaging technique, was applied in this study to evaluate its contribution to improving the diagnostic accuracy of AD. Three-dimensional convolutional neural networks (3D-CNNs) were applied with magnetic resonance imaging (MRI) to execute binary and ternary disease classification models. The dataset from the Alzheimer's disease neuroimaging initiative (ADNI) was used to compare the deep learning performances across 3D-CNN, 3D-CNN-support vector machine (SVM) and two-dimensional (2D)-CNN models. The outcomes of accuracy with ternary classification for 2D-CNN, 3D-CNN and 3D-CNN-SVM were [Formula: see text]%, [Formula: see text]% and [Formula: see text]% respectively. The 3D-CNN-SVM yielded a ternary classification accuracy of 93.71%, 96.82% and 96.73% for NC, MCI and AD diagnoses, respectively. Furthermore, 3D-CNN-SVM showed the best performance for binary classification. Our study indicated that 'NC versus MCI' showed accuracy, sensitivity and specificity of 98.90%, 98.90% and 98.80%; 'NC versus AD' showed accuracy, sensitivity and specificity of 99.10%, 99.80% and 98.40%; and 'MCI versus AD' showed accuracy, sensitivity and specificity of 89.40%, 86.70% and 84.00%, respectively. This study clearly demonstrates that 3D-CNN-SVM yields better performance with MRI compared to currently utilized deep learning methods. In addition, 3D-CNN-SVM proved to be efficient without having to manually perform any prior feature extraction and is totally independent of the variability of imaging protocols and scanners. This suggests that it can potentially be exploited by untrained operators and extended to virtual patient imaging data. Furthermore, owing to the safety, noninvasiveness and nonirradiative properties of the MRI modality, 3D-CNN-SMV may serve as an effective screening option for AD in the general population. This study holds value in distinguishing AD and MCI subjects from normal controls and to improve value-based care of patients in clinical practice.

Vegetable and fruit juice enhances antioxidant capacity and regulates antioxidant gene expression in rat liver, brain and colon.

To explore the effect of fruit and vegetable (FV) juice on biomarkers of oxidative damage and antioxidant gene expression in rats, 36 adult male Wistar rats were randomly divided into control, low FV juice dosage or high FV juice dosage treatment groups. The rats were given freshly extracted FV juice or the same volume of saline water daily for five weeks. After intervention, serum and tissues specimens were collected for biomarker and gene expression measurement. FV juice intervention increased total antioxidant capacity, glutathione, vitamin C, ß-carotene, total polyphenols, flavonoids levels andglutathione peroxidaseenzyme activity in rat serum or tissues (p < 0.05). FV juice intervention caused reduction of malondialdehyde levels in rat liver (p < 0.05) and significantly modulated transcript levels of glutamate cysteine ligase catalytic subunit (GCLC) and NAD(P)H:quinone oxidoreductase l (NQO1)in rat liver and brain (p < 0.05). The results underline the potential of FV juice to improve the antioxidant capacity and to prevent the oxidative damage in liver, brain and colon.

Vegetable and fruit juice enhances antioxidant capacity and regulates antioxidant gene expression in rat liver, brain and colon

Abstract To explore the effect of fruit and vegetable (FV) juice on biomarkers of oxidative damage and antioxidant gene expression in rats, 36 adult male Wistar rats were randomly divided into control, low FV juice dosage or high FV juice dosage treatment groups. The rats were given freshly extracted FV juice or the same volume of saline water daily for five weeks. After intervention, serum and tissues specimens were collected for biomarker and gene expression measurement. FV juice intervention increased total antioxidant capacity, glutathione, vitamin C, β-carotene, total polyphenols, flavonoids levels andglutathione peroxidaseenzyme activity in rat serum or tissues (p < 0.05). FV juice intervention caused reduction of malondialdehyde levels in rat liver (p < 0.05) and significantly modulated transcript levels of glutamate cysteine ligase catalytic subunit (GCLC) and NAD(P)H:quinone oxidoreductase l (NQO1)in rat liver and brain (p < 0.05). The results underline the potential of FV juice to improve the antioxidant capacity and to prevent the oxidative damage in liver, brain and colon.