Neuroprotective Effect of Moderate Epidural Hypothermia After Spinal Cord Injury in Rats
Bibliographic record
Abstract
In Brief Study Design. An animal experimental study on hypothermia after spinal cord injury(SCI). Objective. To investigate the neuroprotective effect of moderate epidural hypothermia (MEH) on SCI in rats and evaluate the antiapoptotic and anti-inflammatory effect of hypothermia. Summary of Background Data. Experimental systemic or local hypothermia has been tried for neuroprotection after ischemic or traumatic SCI. However, its clinical application is limited due to its technical difficulties. If hypothermia is to be considered in the future for treating SCI, then alternative approaches and further studies on the advantages and disadvantages of hypothermia will be mandatory. Methods. Author’s designed MEH (30°C for 48 hours) was tried as a neuroprotector after traumatic SCI. The functional recovery and histopathological changes were assessed. A spinal cord contusion (25 g-cm at T-9) was produced in all 16 rats, and these rats were randomly divided into 2 groups; (1) the control group (spinal cord contusion only), (2) the hypothermia group (spinal cord contusion followed by MEH). Results. MEH significantly reduced the apoptosis of neurons and glial cells when compared with the control group (P < 0.05). Furthermore, MEH significantly inhibited the activation of the microglia and it improved functional recovery after SCI (P < 0.05). Conclusion. These results suggest that MEH may be a possible therapeutic candidate when combined with clinically proven surgical and medical methods for SCI. Moderate epidural hypothermia (30°C for 48 hours) was tried for experimental spinal cord injury in rats. It improved the functional recovery, alleviated the apoptosis of neuron and glial cells, and mitigated the activation of microglia. Moderate epidural hypothermia might be another neuroprotective modality for traumatic spinal cord injury.
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 | 0.001 | 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) | 0.002 | 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".