Attenuation of neurotoxicity in cortical cultures and hippocampal slices from E2F1 knockout mice
Bibliographic record
Abstract
The E2F1 transcription factor modulates neuronal apoptosis induced by staurosporine, DNA damage and beta-amyloid. We demonstrate E2F1 involvement in neuronal death induced by the more physiological oxygen-glucose deprivation (OGD) in mouse cortical cultures and by anoxia in mouse hippocampal slices. E2F1(+/+) and (-/-) cultures were comparable, in that they contained similar neuronal densities, responded with similar increases in intracellular calcium concentration ([Ca(2+)]i) to glutamate receptor agonists, and showed similar NMDA receptor subunit mRNA expression levels for NR1, NR2A and NR2B. Despite these similarities, E2F1(-/-) cultures were significantly less susceptible to neuronal death than E2F1(+/+) cultures 24 and 48 h following 120-180 min of OGD. Furthermore, the absence of E2F1 significantly improved the ability of CA1 neurons in hippocampal slices to recover synaptic transmission following a transient anoxic insult in vitro. These results, along with our finding that E2F1 mRNA levels are significantly increased following OGD, support a role for E2F1 in the modulation of OGD- and anoxia-induced neuronal death. These findings are consistent with studies showing that overexpression of E2F1 in postmitotic neurons causes neuronal degeneration and the absence of E2F1 decreases infarct volume following cerebral ischemia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".