A microfluidic platform for probing small artery structure and function
Bibliographic record
Abstract
Although pathologic changes to the structure and function of small blood vessels are hallmarks of various cardiovascular diseases, limitations of conventional investigation methods (i.e. pressure myography) have prohibited a comprehensive understanding of the underlying mechanisms. We developed a microfluidic device to facilitate assessment of resistance artery structure and function under physiological conditions (37 degrees C, 45 mmHg transmural pressure). The platform allows for on-chip fixation, long-term culture and fully automated acquisition of up to ten dose-response sequences of intact mouse mesenteric artery segments (diameter approximately 250 micrometres and length approximately 1.5 mm) in a well-defined microenvironment. Even abluminal application of phenylephrine or acetylcholine (homogeneous condition) yielded dose-response relationships virtually identical to conventional myography. Unilateral application of phenylephrine (heterogeneous condition) limited constriction to the drug-exposed side, suggesting a lack of circumferential communication. The microfluidic platform allows us to address new fundamental biological questions, replaces a manually demanding procedure with a scalable approach and may enable organ-based screens to be routinely performed during drug development.
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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".