Cofunctionalization of Macroporous Dextran Hydrogels with Adhesive Peptides and Growth Factors Enables Vascular Spheroid Sprouting
Bibliographic record
Abstract
Ensuring good definition of scaffolds used for 3D cell culture is a prominent challenge that hampers the development of tissue engineering platforms. Since dextran repels cell adhesion, using dextran-based materials biofunctionalized through a bottom-up approach allows for precise control over material definition. Here, we report the design of dextran hydrogels displaying a fully interconnected macropore network for the culture of vascular spheroids in vitro . We biofunctionalized the hydrogels with the RGD peptide sequence to promote cell adhesion. We used an affinity peptide pair, the E/K coiled coil, to load the gels with epidermal growth factor (EGF) and vascular endothelial growth factor (VEGF). Dual functionalization with adhesive and proliferative cues allows vascular spheroids to colonize naturally cell-repellant dextran. In supplement-depleted medium, we report improved colonization of the macropores compared to that of unmodified dextran. Altogether, we propose a well-defined and highly versatile platform for tissue engineering and tissue vascularization 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".