Investigating the early role of oxidative stress in Alzheimer’s disease: Insights from a transgenic model of the amyloid pathology and fluorescence imaging methods
Notice bibliographique
Résumé
With an aging population, the negative impact of age-related diseases such as Alzheimer’s disease (AD) will only grow. Alzheimer’s disease (AD) is the leading cause of dementia in the elderly and there are no cures nor preventative treatments. AD has an extended pre-symptomatic stage spanning decades which offers a promising therapeutic window. However, it is presently impossible to unquestionably diagnose AD during this early stage in the general population. Consequently, basic science research on pathological mechanisms that initiate and exacerbate disease progression during the earliest, pre-plaque stage would be insightful for biomarker development and disease-modifying therapies. Studies from our laboratory using a transgenic rat model of the AD-like amyloid pathology and post-mortem human brain material, demonstrated that neurons burdened with Aβ exhibited increased gene and protein expression of inflammatory markers. This early neuroinflammation, which vastly differs from the classical inflammatory process during late, post-plaque stages, motivated our investigation of oxidative stress, which can be a cause and consequence of inflammation. Oxidative stress is elevated during post-plaque stages of AD, but its earliest role in AD remains uncharacterized. As such, Chapter 2 investigates neuron-specific gene and protein expression of oxidative stress-related targets in our rat model during a pre-plaque stage when neuroinflammation is incipient. We show that intraneuronal Aβ- (iAβ) burdened neurons exhibited evidence of DNA damage and had upregulated DNA repair and antioxidant genes and proteins, while oxidative damage trended to increase, suggesting this timepoint preceded a fully realized redox imbalance. Our findings reveal that inflamed iAβ-burdened neurons increase expression of oxidative stress-related genes, likely in response to elevated reactive oxygen species (ROS). Importantly, ROS production is upstream of oxidative stress responses including modulation of gene expression. Therefore, our next goal was to develop methodologies for reliably studying ROS. Quantifying ROS is technically challenging since they are short-lived and include diverse chemical species. Therefore, detection methods must be specific to the ROS of interest. With this in mind, we utilized the fluorogenic probe, H4BPMHC (developed by the McGill Cosa laboratory), that quantifies lipid peroxyl radicals, a form of lipid-associated ROS which neurons are vulnerable to. After optimizing culturing and imaging conditions in primary neurons, we validated in vitro sensitivity of this method by subjecting neurons to varying antioxidant loads over time then imaging them under stressed and non-stressed conditions. In sum, H4BPMHC was sensitive enough to detect differences between our experimental conditions. Chapter 3 presents the proof-of-concept for using H4BPMHC to study lipid peroxyl radicals in neurodegenerative disease models. Finally, building on our expertise from live cell imaging, Chapter 4 outlines the development of a methodology for studying ROS in ex vivo hippocampal slices using two-photon microscopy. Existing ROS detection methods have limited spatial and temporal resolution that real-time in situ imaging would overcome. Towards this goal, this chapter provides key considerations, limitations, and potential pitfalls when quantifying ROS in complicated but biologically relevant systems. Overall, we show that a neuronal oxidative stress response occurs during the early, pre-plaque amyloid pathology and demonstrate the rigor necessary for developing methods of ROS quantification in disease-relevant models. This interdisciplinary work will provide a solid foundation and path forward for future studies investigating the earliest AD pathology as well as the role of oxidative stress in health and disease
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».