Pathological Stages of Abnormally Processed Tau Protein During Its Aggregation into Fibrillary Structures in Alzheimer’s Disease
Notice bibliographique
Résumé
The description about the progression of the neurofibrillary pathology in AD has been proposed by Braak and Braak (Braak et al., 1993, 1996), which states that there is a stereotype in the appearance and distribution of NFTs along entorhinal, limbic and isocortical areas.It is well known that in AD, NFTs and dystrophic neurites (DNs) are mostly composed of tau protein which has undergone several posttranslational modifications such as abnormal phosphorylation, conformational changes and truncation (Du et al., 2007;Novak et al., 1991; Wischik et al., 1988a).In this regard, we have previously proposed that a continuous and specific pathway of conformational changes and truncation of tau protein is occurring during the maturation of NFTs (Binder et al., 2005;Guillozet-Bongaarts et al., 2005, Mondragon-Rodriguez et al., 2009).The sum of our data support that not only the number of NFTs defines the progression of AD, but also the state of proteolysis of the C-terminus which is associated with conformational changes, i.e. structural modification along the tau molecule (Garcia-Sierra, Mondragon-Rodriguez & Basurto-Islas, 2008).In distinct populations of NFTs, the occurrence of mutually exclusive truncations at either acid aspartic-421 (Asp 421 ) or glutamic acid-391 (Glu 391 ) correlated well with the evolution of the disease (Basurto-Islas et al., 2008).This cascade of pathological molecular events may give a better correlation with the neuropathological progression of the disease.In our model of pathologic processing of tau we pointed out the existence of chimeric NFTs which are composed of diverse molecules of tau characteristically in different stages of proteolysis. The neurofibrillary pathology of ADThe observed neuropathological changes in patients with AD are at least partly the result of the accumulation of NFTs (Fig. 1, arrows) and amyloid-β (Aβ) deposits (Aβ-plaques) (Fig. 1, asterisk) around the hippocampal area (Braak & Braak, 1994;Tseng, Kitazawa & LaFerla, 2004).However, the numeric correlation between Aβ-plaques and clinical symptoms in AD barely represents what is happening in the neurodegenerative process.Also the simple Aβaccumulation per se is not the only etiological factor to trigger AD abnormalities (Lee et al., 2005).Cited studies explain why many aged individuals, despite the presence of high numbers of senile plaques, show little or no cognitive decline (Lee et al., 2004).With these data in mind, the belief that the Aβ-accumulation is a consequence rather that a cause is gaining more support.However, the pathology of the NFTs, mainly composed of tau protein, remains as a relevant criterion for the diagnosis of AD after death, because of the spatial correlation, albeit not perfect, between the number of NFTs and the clinical symptoms of this disease (Braak & Braak, 1991;Murayama & Saito, 2004).The support for this asseveration is mainly based on Braak's study, in which the occurrence and progression of NFTs along allocortical and isocortical areas was described (Braak & Braak, 1991).This study evaluates the density and distribution of NFTs along the brain and classifies them into I, II, entorhinal; III, IV, limbic; and V, VI, neocortical stages.These three groups of stages correspond to normal cognition, cognitive impairment, and dementia (Braak & Braak, 1997).Note that this correlation is not sufficient to demonstrate a cause and effect relationship between NFTs and cognitive deficits.In this regard, the obvious question raised is why do brains of AD patients show the pathology of NFTs?Despite all the information available the answer is not even close to being addressed.However, a huge number of strategies focused on the mechanisms governing the aggregation of the tau protein into PHFs and NFTs (Kosik, Joachim & Selkoe, 1986) have attempted to address this.Those www.intechopen.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».