Neuroprotective Effects of PARP Inhibitors in Drosophila Models of Alzheimer’s Disease
Bibliographic record
Abstract
Alzheimer’s disease (AD) is an irreversible age-related neurodegenerative disorder clinically characterized by severe memory impairment, language deficits and cognitive decline. The major neuropathological hallmarks of AD include extracellular deposits of the β-amyloid (Aβ) peptides and cytoplasmic neurofibrillary tangles (NFTs) of hyperphosphorylated tau protein. The accumulation of plaques and tangles in the brain triggers a cascade of molecular events that culminate in neuronal damage and cell death. Despite extensive research, our understanding of the molecular basis of AD pathogenesis remains incomplete and a cure for this devastating disease is still not available. A growing body of evidence in different experimental models suggests that poly(ADP-ribose) polymerase-1 (PARP-1) overactivation might be a crucial component of the molecular network of interactions responsible for AD pathogenesis. In this work, we combined genetic, molecular and biochemical approaches to investigate the effects of two different PARP-1 inhibitors (olaparib and MC2050) in Drosophila models of Alzheimer’s disease by exploring their neuroprotective and therapeutic potential in vivo. We found that both pharmacological inhibition and genetic inactivation of PARP-1 significantly extend lifespan and improve the climbing ability of transgenic AD flies. Consistently, PARP-1 inhibitors lead to a significant decrease of Aβ42 aggregates and partially rescue the epigenetic alterations associated with AD in the brain. Interestingly, olaparib and MC2050 also suppress the AD-associated aberrant activation of transposable elements in neuronal tissues of AD flies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".