Prolonged Localized Mild Hypothermia Does Not Affect Seizure Activity After Intracerebral Hemorrhage in Rats
Bibliographic record
Abstract
Intracerebral hemorrhage (ICH) is a devastating stroke with high morbidity and mortality. Post-ICH seizures are a common complication, potentially increasing brain injury and the risk of delayed epilepsy. Mild therapeutic hypothermia (HYPO, ∼33°C) is neuroprotective against several brain insults, such as ischemia, while also mitigating seizure incidence and severity in some instances. Therefore, we tested whether brain-selective HYPO reduced electrographic seizure activity after a collagenase-induced striatal ICH in rats. Animals were injected unilaterally with 0.14 U of bacterial collagenase, implanted with a unilateral brain cooling device, and a probe to bilaterally record electroencephalographic (EEG) activity. Cooling began 6 hours after collagenase infusion and was maintained for 48 hours, followed by rewarming over 6 hours. Our protocol did not affect EEG activity in naïve rats, nor did it increase bleeding after ICH (∼50 μL). Epileptiform activity commonly occurred in untreated ICH rats (∼60% of animals), but HYPO did not affect the incidence, timing, total duration of seizures, or the peaks occurring during epileptiform activity. However, longer average duration was detected on the ipsilateral side to stroke in the HYPO group (p < 0.05). Cooling did not affect neurological deficits (e.g., circling), measured 7 and 14 days after ICH, or lesion volume (∼35 mm(3)). In addition, there was no relationship among endpoints (e.g., seizures and lesion size). In summary, HYPO failed to reduce seizure activity after ICH, which fits with our separate findings that cooling does not mitigate thrombin and iron-mediated secondary injury mechanisms thought to cause seizures after ICH. Additional research is needed to identify better HYPO protocols and the use of cotreatments to maximize the benefit of HYPO to ICH patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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 teacher head, 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".