Protective effect of nitronyl nitroxide against hypoxia-induced damage in PC12 cells
Bibliographic record
Abstract
Hypoxia induces cellular oxidative stress that is associated with neurodegenerative diseases. HPN (4′-hydroxyl-2-substituted phenyl nitronyl nitroxide), a stable nitronyl nitroxide, has excellent free radical scavenging properties. The purpose of this study was to investigate the protective effects of HPN on hypoxia-induced damage in PC12 cells. It was shown that HPN significantly attenuated hypoxia-induced loss of cell viability, release of lactate dehydrogenase (LDH), and morphological changes in PC12 cells. Moreover, hypoxic PC12 cells had increased levels of reactive oxygen species (ROS), malondialdehyde (MDA), and expression of HIF-1α and VEGF, but had reduced levels of superoxide dismutase (SOD) and catalase (CAT), and HPN reversed these changes. HPN also inhibited hypoxia-induced cell apoptosis via suppressing the expression of Bax, cytochrome c, and caspase-3, and inducing the expression of Bcl-2. These results indicate that the protective effects of HPN on hypoxia-induced damage in PC12 cells is associated with the suppression of hypoxia-induced oxidative stress and cell apoptosis. HPN could be a promising candidate for the development of a novel neuroprotective agent.
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) | 0.001 | 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 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".