The implementation of transcranial Doppler ultrasonography for preclinical study of migraine
Bibliographic record
Abstract
Transcranial Doppler ultrasonography is used to study intracranial blood flow changes associated with migraine in humans, but whether this method is helpful in preclinical settings is yet unknown. To identify changes in rat intracranial blood flow specific to trigeminovascular activation-a key process in migraine pathophysiology-we measured Doppler indices in the middle cerebral artery and basilar artery before, during, and after dural or somatosensory electrical stimulation. Hemodynamic changes specific to dural stimulation were tested further in separate experiments. After baseline recordings, the animals received cumulative infusions of valproate (100 mg/kg, trice), sumatriptan (0.3, 1, and 3 mg/kg), or saline, and dural stimulation with measurement of Doppler indices was repeated every 10 min for 1 h. Several parameters of blood flow in the rat middle cerebral artery underwent alterations specific to trigeminovascular activation. These changes, however, were insensitive to valproate and sumatriptan and diminished over time. These findings question the reliability of blood flow velocity variations in large intracranial vessels as biological markers of migraine-related processes and do not support the idea of using transcranial Doppler ultrasonography for preclinical screening of antimigraine treatments, at least in the model of acute trigeminovascular activation in rats.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".