Abstract TP108: 2,2 Dipyridyl, An Iron Chelator, Does Not Reduce Intracerebral Iron Toxicity Or Improve Outcome After Intracerebral Hemorrhagic Stroke In Rats
Bibliographic record
Abstract
Background — After an intracerebral hemorrhage (ICH) iron is released from degrading erythrocytes over days, which causes secondary damage by increasing free radicals. Many studies show that iron chelators, such as deferoxamine, lessen injury, but not all studies support this. Hypothesis — The ferrous iron chelator, 2,2 Dipyridyl (DP), will decrease injury after ICH or intraparenchymal FeCl 2 infusion in rats. Experiment 1— Rats were given a collagenase-induced striatal ICH. In experiments 1 and 3, we tested whether behavior was improved (e.g., walking) from administering DP (25mg/kg/day, 12 hours after surgery for 3 days). They were euthanized after 7 days to determine non-heme iron levels in the brain. Experiment 2— Rats were injected with DP (20mg/kg) 6 hours after collagenase infusion and every 24 hours till euthanasia at 3 days for measuring edema. Experiment 3— After injecting FeCl 2 in the striatum rats were given DP (25mg/kg every 12 hr starting 2 hours prior to surgery for 3 days). The volume of tissue loss and Fluoro-jade staining (degenerating neurons) was measured. Results — DP did not improve behavioral or histological outcome or reduce edema in either the collagenase ICH or FeCl 2 model. DP also did not affect parenchymal non-heme iron level. Conclusion — Our data suggests that DP on its own is not an effective strategy for ICH.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".