Hypoxia-Inducible Factor -1 contributes to transcriptional regulation of Bcl2-adenovirus E1B 19KDa -interacting protein in hypoxic cortical neurons
Bibliographic record
Abstract
PARP-1 has been identified as a major player in apoptotic pathways. Its excessive activation causes mitochondrial dysfunction, permeability, and AIF mitochondrion-to-nucleus translocation. It has been suggested that PARP-1 interacts indirectly with Bnip3, a mitochondrial pro-apoptotic factor. However, the mechanistic linkage is still not well understood. Our lab has shown that cytosolic/nuclear NAD+ depletion is a hallmark for PARP-1 over activation and inhibition of sirtuin activity. Specifically in my project, we think that PARP-1 induced- NAD+ depletion and sirtuin inhibition causes hyperacetylation of the α subunit of the transcription factor HIF-1 allowing increased HIF-1 binding to Bnip3 upstream promoter, and increased Bnip3 expression. Indeed, our PARP-1 Knock out neurons, MNNG and PJ34 treatment, chromatin immunoprecipitation, and HIF-1α loss of function studies strongly confirmed the necessity of HIF-1 to increase Bnip3 expression in hypoxia. Overall, our research suggests a role for HIF-1 in increasing PARP-1 dependent Bnip3 expression in hypoxic models.
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 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) | 0.003 | 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".