A Micro-Delivery Approach for Studying Microvascular Responses to Localized Oxygen Delivery
Bibliographic record
Abstract
BACKGROUND: In vivo video microscopy has been used to study blood flow regulation as a function of varying oxygen concentration in microcirculatory networks. However, previous studies have measured the collective response of stimulating large areas of the microvascular network at the tissue surface. OBJECTIVE: We aimed to limit the area being stimulated by controlling oxygen availability to highly localized regions of the microvascular bed within intact muscle. DESIGN AND METHOD: Gas of varying O(2) levels was delivered to specific locations on the surface of the Extensor Digitorum Longus muscle of rat through a set of micro-outlets (100 μm diameter) patterned in ultrathin glass using state-of-the-art microfabrication techniques. O(2) levels were oscillated and digitized video sequences were processed for changes in capillary hemodynamics and erythrocyte O(2) saturation. RESULTS AND CONCLUSIONS: Oxygen saturations in capillaries positioned directly above the micro-outlets were closely associated with the controlled local O(2) oscillations. Radial diffusion from the micro-outlet is limited to ~75 μm from the center as predicted by computational modeling and as measured in vivo. These results delineate a key step in the design of a novel micro-delivery device for controlled oxygen delivery to the microvasculature to understand the fundamental mechanisms of microvascular regulation of O(2) supply.
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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 | 0.001 |
| 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".