Hyperthermia worsens ischaemic brain injury through destruction of microvessels in an embolic model in rats
Bibliographic record
Abstract
PURPOSE: Basal lamina is a major part of the microvascular wall and plays a critical role in the integrity of microvasculature. The aim of this study is to determine whether hyperthermia worsens the destruction of microvascular integrity in the ischaemic injured brain. MATERIALS AND METHODS: Focal cerebral ischaemia was induced by embolising a pre-formed clot into the middle cerebral artery (MCA). Rats received either normothermic or hyperthermic treatment. Neurological score and infarct size were evaluated at 24 h after the MCA occlusion. Microvascular collagen type IV and laminin were measured with fluorescence microscopy. The activities of matrix metalloproteinases (MMP-2 and MMP-9) and plasminogen activators (tPA and uPA) were determined by zymography. RESULTS: Treatment with hyperthermia significantly increased infarct volume (p<0.01), cortex swelling (p<0.01), striatum swelling (p<0.05) and neurologic score (p<0.01) at 24 h after the MCA occlusion. Compared to the normothermic groups, hyperthermia significantly worsened the losses of microvascular basal lamina structure proteins, collagen type IV and laminin, at 6 h (p<0.001) and 24 h (p<0.01) after MCA occlusion. Hyperthermia increased the MMP-9 activity at 6 and 24 h after MCA occlusion compared with normothermia (p<0.05), whereas increased the MMP-2 activity at 6 h only (p<0.05). Hyperthermia also elevated uPA activity significantly at 6 and 24 h after MCA occlusion compared to normothermia (p<0.05). CONCLUSIONS: These results demonstrate that hyperthermia exacerbates the destruction of microvascular integrity possibly by increasing the activities of MMP-2, MMP-9 and uPA in the ischaemic cerebral tissues.
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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 | 0.000 |
| 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".