Tauopathies are a heterogeneous mixture of neurodegenerative disorders, including Alzheimer's disease and frontotemporal dementia (FTD), characterised by the accumulation of tau filaments in brain tissue. Tau protein aggregation is inhibited by hydromethylthionine (HMT), an effect that appeared to be prevented in clinical trials for subjects already receiving acetylcholinesterase inhibitors or memantine. Since neuroinflammatory responses are associated with tauopathies, we investigated the effect of HMT on the brain immune response and inflammatory status in line 66 (L66) mice, an FTD-like model overexpressing human tau, in the presence of memantine.
View Article and Find Full Text PDFThe negative interference of treatments between the acetylcholinesterase inhibitor rivastigmine and the tau aggregation inhibitor hydromethylthionine mesylate (HMTM) has been reported in Line 1 tau-transgenic mice, which overexpress a truncated species of tau protein that is found in the core of paired helical filaments in Alzheimer´s disease (AD). However, little is known about whether such interactions could affect synapses in mice overexpressing tau carrying pathogenic mutations. Here, we have used Line 66 (L66) mice which overexpress full-length human tau carrying the P301S mutation as a model in which tau accumulates in synapses.
View Article and Find Full Text PDFRecent clinical trials targeting tau protein aggregation have heightened interest in tau-based therapies for dementia. Success of such treatments depends crucially on translation from non-clinical animal models. Here, we present the age profile of the PLB2 knock-in model of fronto-temporal dementia in terms of cognition, and by utilising a directly translatable magnetic resonance imaging approach.
View Article and Find Full Text PDFThe European Quality In Preclinical Data (EQIPD) consortium was born from the fact that publications report challenges with the robustness, rigor, and/or validity of research data, which may impact decisions about whether to proceed with further preclinical testing or to advance to clinical testing, as well as draw conclusions on the predictability of preclinical models. To address this, a consortium including multiple research laboratories from academia and industry participated in a series of electroencephalography (EEG) experiments in mice aimed to detect sources of variance and to gauge how protocol harmonisation and data analytics impact such variance. Ultimately, the goal of this first ever between-laboratory comparison of EEG recordings and analyses was to validate the principles that supposedly increase data quality, robustness, and comparability.
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