Failure of bumetanide to improve outcome after intracerebral hemorrhage in rat
Bibliographic record
Abstract
After intracerebral hemorrhage (ICH), brain edema commonly occurs and can cause death. Along with edema, there are significant alterations in the concentrations of key ions such as sodium, potassium, and chloride, which are essential to brain function. NKCC1, a cation-chloride cotransporter, is upregulated after brain damage, such as traumatic injury and ischemic stroke. NKCC1 brings sodium and chloride into the cell, possibly worsening ion dyshomeostasis. Bumetanide, a specific NKCC1 antagonist, blocks the transport of chloride into cells, and thus should attenuate the increases in chloride, which should lessen brain edema and improve neuronal functioning post-ICH, as with other injuries. We used the collagenase model of ICH to test whether bumetanide treatment for three days (vs. vehicle) would improve outcome. We gave bumetanide beginning at two hours or seven days post-ICH and measured behavioural outcome, edema, and brain ion content after treatment. There was some evidence for a minor reduction in edema after early dosing, but this did not improve behaviour or lessen injury. Contrary to our hypothesis, bumetanide did not normalize ion concentrations after late dosing. Bumetanide did not improve behavioural outcome or affect lesion volume. After ICH, bumetanide is safe to use in rats but does not improve functional outcome in the majority of animals.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".