Regulation of Cerebral Microcirculation. Update.
Bibliographic record
Abstract
The present symposium during Brain 99 was convened to explore the current aspects of the neural (extrinsic and intrinsic) and chemical control of the microvasculature in the brain with specific relevance to stimuli and rapid flow responses. N. Suzuki demonstrated the presence of neurokinin-1 receptors along the axons of vasoactive intestinal polypeptide-containing cerebrovascular parasympathetic nerves. Since the receptors were activated by substance P, calcitonin gene-related peptide and neurokinin released from coexisting sensory nerve fibers, the parasympathetic (vasodilating) fibers could effect rapid local flow increases. N. Suzuki, however, considered this as part of an elaborate defensive network protecting the brain from invasions by noxious substances. E. Hamel discussed the responses of the microvessels to neurotransmitters and suggested that nitric oxide (NO) released from intrinsic neurons may serve as a relay in the flow activation responses by intracerebral cholinergic fibers originating in the basal forebrain nuclei. D. Busija summarized a vasodilating system of activated N-methyl-D-asparate receptors located on neurons involving Ca influx-NO production, and activated ATP-sensitive potassium channels located in the vascular system. According to Busija, such interactions were disrupted during hypoxia and ischemia due to cyclooxygenase-derived superoxide anion. M. Lauritzen observed a 10 times larger increase in blood flow on stimulation of the climbing nerve as compared with that following the parallel nerve stimulation. The former transmitters are considered by him to be NO and K, and the latter NO and adenosine. Each speaker singled out NO as a common mediator for the microvasculature in the rapid local flow increases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".