Selective cytotoxicity of intracellular amyloid β peptide1–42 through p53 and Bax in cultured primary human neurons
Bibliographic record
Abstract
Extracellular amyloid beta peptides (Abetas) have long been thought to be a primary cause of Alzheimer's disease (AD). Now, detection of intracellular neuronal Abeta1--42 accumulation before extracellular Abeta deposits questions the relevance of intracellular peptides in AD. In the present study, we directly address whether intracellular Abeta is toxic to human neurons. Microinjections of Abeta1--42 peptide or a cDNA-expressing cytosolic Abeta1--42 rapidly induces cell death of primary human neurons. In contrast, Abeta1--40, Abeta40--1, or Abeta42--1 peptides, and cDNAs expressing cytosolic Abeta1--40 or secreted Abeta1--42 and Abeta1--40, are not toxic. As little as a 1-pM concentration or 1500 molecules/cell of Abeta1--42 peptides is neurotoxic. The nonfibrillized and fibrillized Abeta1--42 peptides are equally toxic. In contrast, Abeta1--42 peptides are not toxic to human primary astrocytes, neuronal, and nonneuronal cell lines. Inhibition of de novo protein synthesis protects against Abeta1--42 toxicity, indicating that programmed cell death is involved. Bcl-2, Bax-neutralizing antibodies, cDNA expression of a p53R273H dominant negative mutant, and caspase inhibitors prevent Abeta1--42-mediated human neuronal cell death. Taken together, our data directly demonstrate that intracellular Abeta1--42 is selectively cytotoxic to human neurons through the p53--Bax cell death pathway.
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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) | 0.001 | 0.001 |
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".