Differential effects of uniaxial and biaxial strain on U937 macrophage‐like cell morphology: Influence of extracellular matrix type proteins
Bibliographic record
Abstract
Tissue engineering concepts have expanded in the last decade to consider the importance of biochemical signaling from extracellular matrix (ECM) proteins adhered to substrates such as polymeric and ceramic scaffolds. This study investigated combined ECM/mechanical factors on the key signaling cells (macrophages) for wound healing, since previously, mechanical strain and ECM proteins have only been considered separately for their effects on macrophage morphology. Human U937 macrophage-like cells were cultured on a model elastomeric membrane, coated with either collagen type I or poly-RGD peptide (ProNectin). The cells were subjected to cyclic uniform uniaxial or nonuniform biaxial strain with the Flexercell Tension Plus system to simulate strains that various soft tissue implants may undergo during the critical tissue-implant integration period. The surface coatings affected total cellular protein, which was significantly higher in cells on collagen than ProNectin coated surfaces after biaxial, but not uniaxial strain, whereas ProNectin coated surfaces caused a decrease in DNA following uniaxial, but not biaxial strain. Adding the protein coatings that relate to the wound healing process during tissue regeneration, elicited effects specific to the strain type imposed. The combination of these parameters caused changes in U937 macrophage-like cells that should be considered in the outcome of the desired performance in the tissue-material 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".