Presenilin-1 regulates the neuronal threshold to excitotoxicity both physiologically and pathologically
Bibliographic record
Abstract
A direct pathophysiological role of Familial Alzheimer's Disease (FAD)-associated Presenilin 1 (PS1) mutations in neuronal vulnerability remains a controversial matter. We evaluated the relationship between PS1 and excitotoxicity in four different experimental models of neurotoxicity by using primary neurons from (i) transgenic (tg) mice overexpressing a human FAD-linked PS1 variant (L286V mutation), (ii) tg mice overexpressing human wild-type (wt) PS1, (iii) PS1 knockout mice, and (iv) wt mice in which PS1 gene expression was knocked down by antisense treatment. We found that primary neurons overexpressing mutated PS1 showed an increased vulnerability to both excitotoxic and hypoxic-hypoglycemic damage when compared with neurons obtained from either mice overexpressing human wt PS1 or in wt mice. In addition, reduced excitotoxic damage was obtained in neurons in which PS1 expression was absent or diminished. Data obtained in in vivo experimental models of excitotoxicity partially supported the in vitro observations. Accelerated neuronal death was demonstrated in the hippocampus of mice overexpressing mutated PS1 after peripheral administration of kainic acid in comparison with wt animals. However, measurement of the infarct volume after middle cerebral artery occlusion did not show significant difference between the two animal groups. The results altogether suggest that expression of FAD-linked PS1 variants increases the vulnerability of neurons to a specific type of damage in which excitotoxicity plays a relevant role. In addition, they support the view that reduction of endogenous PS1 expression results in neuroprotection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".