Amelioration of hypoperfusion after traumatic brain injury by in vivo endothelin-1 knockout
Bibliographic record
Abstract
Endothelin 1 (ET-1) is one of the most powerful vasoconstrictors in the brain. Its expression is upregulated after traumatic brain injury (TBI) and is a major factor in the ensuing hypoperfusion. Attenuation of ET-1 effects has been mainly achieved by blockade of its receptors. The result of a direct blockade of ET-1 mRNA synthesis is not known. We used the Marmarou's model to inflict injury to male Sprague-Dawley rats injected with antisense ET-1 oligodeoxynucleotides (ODNs) before injury. Laser Doppler flowmetry in noninjured rats (2 groups, i.e., untreated and animals that received cODNs) revealed a constant cerebral blood flow of approximately 14 mL.min-1.100 g-1, whereas the values from injured animals pretreated with control ODNs (cODNs) or from animals subjected to TBI alone were approximately 8.0 mL.min-1.100 g-1 during the 18-48 h time period post-TBI. After antisense ET-1 ODNs pretreatment, however, cerebral blood flow in injured animals was approximately 17 mL.min-1.100 g-1 during the 6-48 h time period. Antisense ET-1 ODNs-treated animals also had 19%-29% larger microvessel cross-sectional area and approximately one-third less ET-1 immunoreactivity in the 50-75% range after injury than did cODNs-treated animals after TBI. The results indicate that this direct in vivo approach is an effective therapeutic intervention for the restoration of cerebral blood flow after TBI.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".