METHODS: In contrast, ViTs have demonstrated proficiency in capturing global signal patterns. In light of these observations, we propose a novel approach to enhance AD risk assessment. Our proposition involves a hybrid architecture, merging the strengths of CNNs and ViTs to compensate for their respective feature extraction limitations. Our proposed Dual-Branch Feature Fusion Network (DBN) leverages both CNN and ViT components to acquire texture features and global semantic information from EEG signals. These elements are pivotal in capturing dynamic electrical signal changes in the cerebral cortex. Additionally, we introduce Spatial Attention (SA) and Channel Attention (CA) blocks within the network architecture. These attention mechanisms bolster the model's capacity to discern abnormal EEG signal patterns from the amalgamated features. To make well-informed predictions, we employ a two-factor decision-making mechanism. Specifically, we conduct correlation analysis on predicted EEG signals from the same subject to establish consistency.
RESULTS: This is then combined with results from the Clinical Neuropsychological Scale (MMSE) assessment to comprehensively evaluate the subject's susceptibility to AD. Our experimental validation on the publicly available OpenNeuro database underscores the efficacy of our approach. Notably, our proposed method attains an impressive 80.23% classification accuracy in distinguishing between AD, Frontotemporal dementia (FTD), and Normal Control (NC) subjects.
DISCUSSION: This outcome outperforms prevailing state-of-the-art methodologies in EEG-based AD prediction. Furthermore, our methodology enables the visualization of salient regions within pathological images, providing invaluable insights for interpreting and analyzing AD predictions.
Methods: The cytotoxicity of FD extract was assessed by MTS solution. BV2 cells were divided into 5 experimental groups, intervened, respectively, by FD (4 mg/mL) and LPS + FD (0, 1, 2, and 4 mg/mL). Besides, a blank control group was set up without any intervention. TNF-α release was assessed by enzyme linked immunosorbent assay (ELISA). The expression of CD40 was examined by flow cytometry. Immunocytochemical staining was used to show the morphology of BV2 cells.
Results: FD extract of different concentrations (1, 2, and 4 mg/mL) had no significant toxic effects on the BV2 cells. FD suppressed the activation of microglia in morphology and reduced TNF-α production and expression of CD40 induced by LPS.
Conclusion: FD extract has a therapeutic potential against neuroinflammatory diseases.
METHODS: miR-3191 expression is determined via quantitative real-time polymerase chain reaction. Knockdown and overexpression of miR-3191 influence the proliferation and metastasis of HCC cells, which is measured by Cell Counting Kit-8 assay, Colony Formation assay and Cell metastasis assay. Protein expression is estimated by Western blot. The interplay between miR-3191 and target is validated by dual-luciferase reporter assay.
RESULTS: Here, we show that miR-3191 is upregulated in HCC tissues and associated with poor prognosis of HCC patients. Mechanistically, p21-activated protein kinase 6 (PAK6) was identified as a direct target of miR‑3191 in HCC. PAK6 knockdown partially recovered interference of miR‑3191‑induced decrease in cell proliferation and invasion. The accuracy of HCC patient prognosis could be improved by employing a combination of miR-3191 and PAK6 values.
CONCLUSIONS: miR-3191 promotes the proliferation and metastasis of HCC cells via targeting PAK6 and may serve as a prognostic biomarker and potential therapeutic target.