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Record W2234274384 · doi:10.1007/978-1-60761-602-3_21

Free Radical–Mediated Damage to Brain in Alzheimer’s Disease: Role of Acrolein and Preclinical Promise of Antioxidant Polyphenols

2010· book-chapter· en· W2234274384 on OpenAlexaff
Charles Ramassamy, Madeleine Arseneault, Dang Thanh Nam

Bibliographic record

VenueHumana Press eBooks · 2010
Typebook-chapter
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsUniversité LavalInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsOxidative stressLipid peroxidationNeuroprotectionReactive oxygen speciesAntioxidantAcroleinChemistryGlutathioneIntracellularBiochemistryPharmacologyBiologyEnzyme

Abstract

fetched live from OpenAlex

Brain aging is associated with accumulation of oxidation-induced damage, likely due to the imbalance between antioxidant defenses and intracellular generation of reactive oxygen species (ROS). Alzheimer’s disease (AD) is the most frequent neurodegenerative disease with multiple causes, and aging is considered as the major risk factor for the development of this disease. From early stages, oxidative damage is strongly implicated in the pathophysiology of this disorder. Lipid peroxidation generates various by-products such as F2α-isoprostane, 4-hydroxynonenal, malondialdehyde, and acrolein with the latter being the most reactive. In the neuroblastoma SK-N-SH cell line, our results show that acrolein can induce cell toxicity through a nonapoptotic pathway. Moreover, acrolein can alter the redox state by depleting glutathione levels. Considering the role of oxidative stress and the toxic effect of by-products of lipid oxidation, intake of compounds with antioxidant activities such as polyphenolic compounds may be beneficial in the prevention of AD. In this chapter, we will review the role of free radical–mediated damage in AD and in transgenic mouse models and present the main intracellular target of polyphenolic compounds underlying their potential neuroprotective effect.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.056
GPT teacher head0.314
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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