Determination of critical shear stress for maturation of human pluripotent stem cell‐derived endothelial cells towards an arterial subtype
Bibliographic record
Abstract
Abstract Human pluripotent stem cell‐derived endothelial cells (hPSC‐ECs) present an attractive alternative to primary EC sources for vascular grafting. However, there is a need to mature them towards either an arterial or venous subtype. A vital environmental factor involved in the arteriovenous specification of ECs during early embryonic development is fluid shear stress; therefore, there have been attempts to employ adult arterial shear stress conditions to mature hPSC‐ECs. However, hPSC‐ECs are naïve to fluid shear stress, and their shear responses are still not well understood. Here, we used a multiplex microfluidic platform to systematically investigate the dose‐time shear responses on hPSC‐EC morphology and arterial‐venous phenotypes over a range of magnitudes coincidental with physiological levels of embryonic and adult vasculatures. The device comprised of six parallel cell culture chambers that were individually linked to flow‐setting resistance channels, allowing us to simultaneously apply shear stress ranging from 0.4 to 15 dyne/cm 2. We found that hPSC‐ECs required up to 40 hr of shear exposure to elicit a stable phenotypic change. Cell alignment was visible at shear stress <1 dyne/cm 2, which was independent of shear stress magnitude and duration of exposure. We discovered that the arterial markers NOTCH1 and EphrinB2 exhibited a dose‐dependent increase in a similar manner beyond a threshold level of 3.8 dyne/cm 2, whereas the venous markers COUP‐TFII and EphB4 expression remained relatively constant across different magnitudes. These findings indicated that hPSC‐ECs were sensitive to relatively low magnitudes of shear stress, and a critical level of ~4 dyne/cm 2 was sufficient to preferentially enhance their maturation into an arterial phenotype for future vascular tissue engineering applications.
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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".