540 Chemie und zugeordnete Wissenschaften
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Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses significant health risks to middle-aged and elderly people. Brain magnetic resonance imaging (MRI) is the most widely used diagnostic method for AD. However, it is challenging to collect sufficient brain imaging data with high-quality annotations. Weakly supervised learning (WSL) is a machine learning technique aimed at learning effective feature representation from limited or low-quality annotations. In this paper, we propose a WSL-based deep learning (DL) framework (ADGNET) consisting of a backbone network with an attention mechanism and a task network for simultaneous image classification and image reconstruction to identify and classify AD using limited annotations. The ADGNET achieves excellent performance based on six evaluation metrics (Kappa, sensitivity, specificity, precision, accuracy, F1-score) on two brain MRI datasets (2D MRI and 3D MRI data) using fine-tuning with only 20% of the labels from both datasets. The ADGNET has an F1-score of 99.61% and sensitivity is 99.69%, outperforming two state-of-the-art models (ResNext WSL and SimCLR). The proposed method represents a potential WSL-based computer-aided diagnosis method for AD in clinical practice.
The prevention of tau protein aggregations is a therapeutic goal for the treatment of Alzheimer's disease (AD), and hydromethylthionine (HMT) (also known as leucomethylthioninium-mesylate [LMTM]), is a potent inhibitor of tau aggregation in vitro and in vivo. In two Phase 3 clinical trials in AD, HMT had greater pharmacological activity on clinical endpoints in patients not receiving approved symptomatic treatments for AD (acetylcholinesterase (AChE) inhibitors and/or memantine) despite different mechanisms of action. To investigate this drug interaction in an animal model, we used tau-transgenic L1 and wild-type NMRI mice treated with rivastigmine or memantine prior to adding HMT, and measured changes in hippocampal acetylcholine (ACh) by microdialysis. HMT given alone doubled hippocampal ACh levels in both mouse lines and increased stimulated ACh release induced by exploration of the open field or by infusion of scopolamine. Rivastigmine increased ACh release in both mouse lines, whereas memantine was more active in tau-transgenic L1 mice. Importantly, our study revealed a negative interaction between HMT and symptomatic AD drugs: the HMT effect was completely eliminated in mice that had been pre-treated with either rivastigmine or memantine. Rivastigmine was found to inhibit AChE, whereas HMT and memantine had no effects on AChE or on choline acetyltransferase (ChAT). The interactions observed in this study demonstrate that HMT enhances cholinergic activity in mouse brain by a mechanism of action unrelated to AChE inhibition. Our findings establish that the drug interaction that was first observed clinically has a neuropharmacological basis and is not restricted to animals with tau aggregation pathology. Given the importance of the cholinergic system for memory function, the potential for commonly used AD drugs to interfere with the treatment effects of disease-modifying drugs needs to be taken into account in the design of clinical trials.