Fibronectin, Vitronectin, and Collagen I Induce Chemotaxis and Haptotaxis of Human and Rabbit Mesenchymal Stem Cells in a Standardized Transmembrane Assay
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The mesenchymal stem cell (MSC) is a critical element in tissue repair and regeneration. Its ability to differentiate into multiple connective tissue cell types and to self-renew has made it a prime candidate in regenerative medicine strategies. Currently, the environmental cues responsible for in situ recruitment and control of MSC distribution at repair sites are not entirely revealed and in particular the role of extracellular matrix (ECM) proteins as motogenic factors has not been studied. Here we have used a standardized transmembrane chemotaxis assay to assess the chemotactic and haptotactic potential of fibronectin, vitronectin, and collagen type 1 on MSCs from both rabbit and human origin. The use of both cell types was based in part on the widespread use of rabbit models for musculoskeletal-related tissue engineering and repair models and their unknown correspondence to human in terms of MSC migration. The optimized assay yielded a greatly increased chemotactic response toward known factors such as platelet-derived growth factor-BB (PDGF)-BB compared to previous studies. Our primary finding was that all three ECM proteins tested (fibronectin, vitronectin, and collagen I) induced significant motogenic activity, in both soluble and insoluble forms, for both rabbit and human MSCs. These results suggest that ECM proteins could play roles as significant as cytokines in the recruitment of pluripotential repair cells wound and tissue repair sites. Furthermore, designed ECM coatings of scaffolds or implants could provide a new tool to control both cell influx and outflux from the scaffold post-implantation. Finally, the similarity of motogenic behavior of both rabbit and human cells suggests the rabbit is a reliable model for assessing MSC recruitment in repair and regeneration strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 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 it