Subacute metformin treatment reduces inflammation and improves functional outcome following neonatal hypoxia ischemia
Bibliographic record
Abstract
Hypoxia-ischemia (HI) injury is a leading cause of neonatal death and long-term disability, and existing treatment options for HI offer only modest benefit. Early intervention with the drug metformin has been shown to promote functional improvement in numerous rodent models of injury and has pleiotropic cellular effects in the brain. We have previously shown that 1 week of metformin treatment initiated 24 h after HI in neonatal mice resulted in improved motor and cognitive performance, activation of endogenous neural precursor cells (NPCs), and increased oligodendrogenesis. While promising, a limitation to this work is that immediate pharmacological intervention is not always possible in the clinic. Herein, we investigated whether delaying metformin treatment to begin in the subacute phase post-HI would still effectively promote recovery. Male and female C57/BL6 mice received HI injury postnatally, and metformin treatment began 7 days post-HI for up to 4 weeks. Motor and cognitive performance was assessed across time using behavioural tests (cylinder, foot fault, puzzle box). We found that metformin improved motor and cognitive behaviour, decreased inflammation, and increased oligodendrocytes in the motor cortex. Our present findings demonstrate that a clinically relevant subacute metformin treatment paradigm affords the potential to treat neonatal HI, and that improved outcomes occur through modulation of the inflammatory response and oligodendrogenesis.
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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) | 0.001 | 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) | 0.001 | 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".