Poly( <scp>ADP</scp> ‐ribose) mediates bioenergetic defects and redox imbalance in neurons following oxygen and glucose deprivation
Bibliographic record
Abstract
PARP-1 over-activation results in cell death via excessive PAR generation in different cell types, including neurons following brain ischemia. Glycolysis, mitochondrial function, and redox balance are key cellular processes altered in brain ischemia. Studies show that PAR generated after PARP-1 over-activation can bind hexokinase-1 (HK-1) and result in glycolytic defects and subsequent mitochondrial dysfunction. HK-1 is the neuronal hexokinase and catalyzes the first reaction of glycolysis, converting glucose to glucose-6-phosphate (G6P), a common substrate for glycolysis, and the pentose phosphate pathway (PPP). PPP is critical in maintaining NADPH and GSH levels via G6P dehydrogenase activity. Therefore, defects in HK-1 will not only decrease cellular bioenergetics but will also cause redox imbalance due to the depletion of GSH. In brain ischemia, whether PAR-mediated inhibition of HK-1 results in bioenergetics defects and redox imbalance is not known. We used oxygen-glucose deprivation (OGD) in mouse cortical neurons to mimic brain ischemia in neuronal cultures and observed that PARP-1 activation via PAR formation alters glycolysis, mitochondrial function, and redox homeostasis in neurons. We used pharmacological inhibition of PARP-1 and adenoviral-mediated overexpression of wild-type HK-1 (wtHK-1) and PAR-binding mutant HK-1 (pbmHK-1). Our data show that PAR inhibition or overexpression of HK-1 significantly improves glycolysis, mitochondrial function, redox homeostasis, and cell survival in mouse cortical neurons exposed to OGD. These results suggest that PAR binding and inhibition of HK-1 during OGD drive bioenergetic defects in neurons due to inhibition of glycolysis and impairment of mitochondrial function.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".