Functional coordination of the spread of vasodilations through skeletal muscle microvasculature: implications for blood flow control
Bibliographic record
Abstract
AIM: We sought to understand the integrated vascular response to muscle contraction by determining how different branch orders of the terminal microvascular network respond to stimulation using a K(ATP) channel opener pinacidil (PIN) as a muscle contraction mimetic. METHODS: Using the blood perfused, hamster cremaster preparation in situ, we locally micropipette-applied 10(-5) M PIN on the capillaries, Branch arteriole (third order, two branch orders up from the capillaries) and transverse arterioles (TA) (second order, three branch orders up from the capillaries) and observed different branch orders of the microvasculature to determine where the localized vasodilation spread throughout the terminal microvascular network. RESULTS: We observed that PIN stimulation of capillaries caused associated upstream vasodilation of the module inflow arteriole (MI) (fourth order, the terminal arteriole) (2.1 ± 0.4 μm), the associate Branch (1.4 ± 0.5 μm) and in the upstream direction on the TA (2.1 ± 0.5 μm). Vasodilation did not occur in all MIs (-0.2 ± 0.2 μm) from the vasodilated branch and did not go downstream on the TA (0.7 ± 0.4 μm). Branch stimulation caused upstream TA (3.3 ± 1.0 μm) and upstream Branch (1.7 ± 0.3 μm) vasodilation but not downstream TA (1.5 ± 0.6 μm) or downstream Branch (0.2 ± 0.3 μm) vasodilation. TA stimulation caused conducted responses in both directions and into all associated arteriolar Branches and MIs. CONCLUSIONS: The spread of the conducted response is dependent on the vascular branch order stimulated: capillary stimulation was most specific in its direction and TA stimulation was the least specific. Our data indicate that vascular branch order is important in determining the vascular response needed to direct blood flow to contracting skeletal muscle cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".