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Background: A wide range of techniques has been developed over the past decades to characterize amyloid-β (Aβ) pathology in mice. Until now, no method has been established to quantify spatial changes in Aβ plaque deposition due to targeted delivery of substances using ALZET® pumps.Objective: Development of a methodology to quantify the local distribution of Aβ plaques after intracerebral infusion of compounds.Methods: We have developed a toolbox to quantify Aβ plaques in relation to intracerebral injection channels using Zeiss AxioVision® and Microsoft Excel® software. For the proof of concept, intracerebral stereotactic surgery was performed in 50-day-old APP-transgenic mice injected with PBS. At the age of 100 days, brains were collected for immunhistological analysis.Results: The toolbox can be used to analyze and evaluate Aβ plaques (number, size, and coverage) in specific brain areas based on their location relative to the point of the injection or the injection channel. The tool provides classification of Aβ plaques in pre-defined distance groups using two different approaches.Conclusion: This new analytic toolbox facilitates the analysis of long-term continuous intracerebral experimental compound infusions using ALZET® pumps. This method generates reliable data for Aβ deposition characterization in relation to the distribution of experimental compounds. [ABSTRACT FROM AUTHOR]

Background: Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automatic analysis of histological whole-slide images using machine learning/artificial intelligence.Objective: To evaluate and validate the use of DeePathology STUDIO for the analysis of histological slides at high resolution.Methods: We compared the DeePathology STUDIO and our current standard method using macros in AxioVision for the analysis of amyloid-β (Aβ) plaques and microglia in APP-transgenic mice at different ages. We analyzed density variables and total time invested with each approach. In addition, we correlated Aβ concentration in brain tissue measured by ELISA with the results of Aβ staining analysis.Results: DeePathology STUDIO showed a significant decrease of the time for establishing new analyses and the total analysis time by up to 90%. On the other hand, both approaches showed similar quantitative results in plaque and activated microglia density in the different experimental groups. DeePathology STUDIO showed higher sensitivity and accuracy for small-sized plaques. In addition, DeePathology STUDIO allowed the classification of plaques in diffuse- and dense-packed, which was not possible with our traditional analysis.Conclusion: DeePathology STUDIO substantially reduced the effort needed for a new analysis showing comparable quantitative results to the traditional approach. In addition, it allowed including different objects (categories) or cell types in a single analysis, which is not possible with conventional methods. [ABSTRACT FROM AUTHOR]

Background: The recent failure of clinical trials to treat Alzheimer's disease (AD) indicates that the current approach of modifying disease is either wrong or is too late to be efficient. Mild cognitive impairment (MCI) denotes the phase between the preclinical phase and clinical overt dementia. AD mouse models that overexpress human amyloid-β (Aβ) are used to study disease pathogenesis and to conduct drug development/testing. However, there is no direct correlation between the Aβ deposition, the age of onset, and the severity of cognitive dysfunction.Objective: To detect and predict MCI when Aβ plaques start to appear in the hippocampus of an AD mouse.Methods: We trained wild-type and AD mice in a Morris water maze (WM) task with different inter-trial intervals (ITI) at 3 months of age and assessed their WM performance. Additionally, we used a classification algorithm to predict the genotype (APPtg versus wild-type) of an individual mouse from their respective WM data.Results: MCI can be empirically detected using a short-ITI protocol. We show that the ITI modulates the spatial learning of AD mice without affecting the formation of spatial memory. Finally, a simple classification algorithm such as logistic regression on WM data can give an accurate prediction of the cognitive dysfunction of a specific mouse.Conclusion: MCI can be detected as well as predicted simultaneously with the onset of Aβ deposition in the hippocampus in AD mouse model. The mild cognitive impairment prediction can be used for assessing the efficacy of a treatment. [ABSTRACT FROM AUTHOR]

Purpose: Epileptogenesis, i.e., development of epilepsy, involves a number of processes that alter the brain function in the way that triggers spontaneous seizures. Kindling is one of the most used animal models of temporal lobe epilepsy (TLE) and epileptogenesis, although chemical kindling suffers from high inter-assay success unpredictability. This study was aimed to analyze the eventual regional brain metabolic changes during epileptogenesis in the pentylenetetrazole (PTZ) kindling model in order to obtain a predictive kindling outcome parameter.Procedures: In vivo longitudinal positron emission tomography (PET) scans with 2-deoxy-2-[(18)F]fluoro-D-glucose ([(18)F]FDG) along the PTZ kindling protocol (35 mg/kg intraperitoneally (i.p.), 18 sessions) in adult male rats were performed in order to evaluate the regional brain metabolism.Results: The half of the PTZ-injected rats reached the kindled state. In addition, a significant decrease of [(18)F]FDG uptake at the end of the protocol in most of the brain structures of kindled animals was found, reflecting the characteristic epilepsy-associated hypometabolism. However, PTZ-injected animals but not reaching the kindled state did not show this widespread brain hypometabolism. Retrospective analysis of the data revealed that hippocampal [(18)F]FDG uptake normalized to pons turned out to be a predictive index of the kindling outcome. Thus, a 19.06 % reduction (p = 0.008) of the above parameter was found in positively kindled rats compared to non-kindled ones just after the fifth PTZ session.Conclusion: Non-invasive PET neuroimaging was a useful tool for discerning epileptogenesis progression in this animal model. Particularly, the [(18)F]FDG uptake of the hippocampus proved to be an early predictive parameter to differentiate resistant and non-resistant animals to the PTZ kindling. [ABSTRACT FROM AUTHOR]