Assessment of fibrin-collagen co-gels for generating microvessels <i>ex vivo</i> using endothelial cell-lined microfluidics and multipotent stromal cell (MSC)-induced capillary morphogenesis
Bibliographic record
Abstract
is the generation of perfusable microvessels of varying diameters. In this work, we take the approach of using hydrogel-based microfluidics seeded with endothelial cells (ECs) to form small artery/vein-like vessels, in conjunction with using the self-assembly behavior of ECs to form capillary-like vessels when co-cultured with multipotent stromal cells (MSCs). In exploring this approach, we focused on investigating collagen, fibrin, and various collagen-fibrin co-gel formulations for their potential suitability as serving as scaffold materials by surveying their angiogencity and mechanical properties. Fibrin and co-gels successfully facilitated multicellular EC sprouting, whereas collagen elicited a migration response of individual ECs, unless supplemented with the protein kinase C (PKC)-activator, phorbol 12-myristate 13-acetate. Collagen scaffolds were also found to severely contract when embedded with mesenchymal cells, but this contraction could be abrogated with the addition of fibrin. Increasing collagen content within co-gel formulations, however, imparted a higher compressive modulus and allowed for the reliable formation of intact hydrogel-based microchannels which could then be perfused. Given the bioactivity and mechanical benefits of fibrin and collagen, respectively, collagen-fibrin co-gels are a promising scaffold option for generating vascularized tissue constructs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".