Neuropilin-1 Is a Direct Target of the Transcription Factor E2F1 during Cerebral Ischemia-Induced Neuronal Death In Vivo
Bibliographic record
Abstract
The nuclear transcription factor E2F1 plays an important role in modulating neuronal death in response to excitotoxicity and cerebral ischemia. Here, by comparing gene expression in brain cortices from E2F1(+/+) and E2F1(-/-) mice using a custom high-density DNA microarray, we identified a group of putative E2F1 target genes that might be responsible for ischemia-induced E2F1-dependent neuronal death. Neuropilin 1 (NRP-1), a receptor for semaphorin 3A-mediated axon growth cone collapse and retraction, was confirmed to be a direct target of E2F1 based on (i) the fact that the NRP-1 promoter sequence contains an E2F1 binding site, (ii) reactivation of NRP-1 expression in E2F1(-/-) neurons when the E2F1 gene was replaced, (iii) activation of the NRP-1 promoter by E2F1 in a luciferase reporter assay, (iv) electrophoretic mobility gel shift analysis confirmation of the presence of an E2F binding sequence in the NRP-1 promoter, and (v) the fact that a chromatin immunoprecipitation assay showed that E2F1 binds directly to the endogenous NRP-1 promoter. Interestingly, the temporal induction in cerebral ischemia-induced E2F1 binding to the NRP-1 promoter correlated with the temporal-induction profile of NRP-1 mRNA, confirming that E2F1 positively regulates NRP-1 during cerebral ischemia. Functional analysis also showed that NRP-1 receptor expression was extremely low in E2F1(-/-) neurons, which led to the diminished response to semaphorin 3A-induced axonal shortening and neuronal death. An NRP-1 selective peptide inhibitor provided neuroprotection against oxygen-glucose deprivation. Taken together, these findings support a model in which E2F1 targets NRP-1 to modulate axonal damage and neuronal death in response to cerebral ischemia.
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 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".