Prolonged Therapeutic Hypothermia does not Adversely Impact Neuroplasticity after Global Ischemia in Rats
Bibliographic record
Abstract
Hypothermia improves clinical outcome after cardiac arrest in adults. Animal data show that a day or more of cooling optimally reduces edema and tissue injury after cerebral ischemia, especially after longer intervention delays. Lengthy treatments, however, may inhibit repair processes (e.g., synaptogenesis). Thus, we evaluated whether unilateral brain hypothermia (∼33°C) affects neuroplasticity in the rat 2-vessel occlusion model. In the first experiment, we cooled starting 1 hour after ischemia for 2, 4, or 7 days. Another group was cooled for 2 days starting 48 hours after ischemia. One group remained normothermic throughout. All hypothermia treatments started 1 hour after ischemia equally reduced hippocampal CA1 injury in the cooled hemisphere compared with the normothermic side and the normothermic group. Cooling only on days 3 and 4 was not beneficial. Importantly, no treatment influenced neurogenesis (Ki67/Doublecortin (DCX) staining), synapse formation (synaptophysin), or brain-derived neurotropic factor (BDNF) immunohistochemistry. A second experiment confirmed that BDNF levels (ELISA) were equivalent in normothermic and 7-day cooled rats. Last, we measured zinc (Zn), which is important in plasticity, with X-ray fluorescence imaging in normothermic and 7-day cooled rats. Hypothermia did not alter the postischemic distribution of Zn within the hippocampus. In summary, cooling significantly mitigates injury without compromising neuroplasticity.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".