Effects of voluntary exercise on structure and function of cortical microvasculature
Bibliographic record
Abstract
Aerobic activity has been shown highly beneficial to brain health, yet much uncertainty still surrounds the effects of exercise on the functioning of cerebral microvasculature. This study used two-photon fluorescence microscopy to examine cerebral hemodynamic alterations as well as accompanying geometric changes in the cortical microvascular network following five weeks of voluntary exercise in transgenic mice endogenously expressing tdTomato in vascular endothelial cells to allow visualization of microvessels irrespective of their perfusion levels. We found a diminished microvascular response to a hypercapnic challenge (10% FiCO 2 ) in running mice when compared to that in nonrunning controls despite commensurate increases in transcutaneous CO 2 tension. The flow increase to hypercapnia in runners was 70% lower than that in nonrunners (p = 0.0070) and the runners’ arteriolar red blood cell speed changed by only half the amount seen in nonrunners (p = 0.0085). No changes were seen in resting hemodynamics or in the systemic physiological parameters measured. Although a few unperfused new vessels were observed on visual inspection, running did not produce significant morphological differences in the microvascular morphometric parameters, quantified following semiautomated tracking of the microvascular networks. We propose that voluntary running led to increased cortical microvascular efficiency and desensitization to CO 2 elevation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".