The spatial patterning of RGD and BMP‐2 mimetic peptides at the subcellular scale modulates human mesenchymal stem cells osteogenesis
Bibliographic record
Abstract
Engineering artificial extracellular matrices, based on the biomimicry of the spatial distribution of proteins and growth factors within their native microenvironment, is of great importance for understanding mechanisms of bone tissue regeneration. Herein, photolithography is used to decorate glass surfaces with subcellular patterns of RGD and BMP-2 ligands; two mimetic peptides recognized to be involved in stem cells osteogenesis. The biological relevance of well-defined RGD and BMP-2 patterned surfaces is evaluated by investigating the differentiation of human mesenchymal stem cells (hMSCs) into osteoblasts, in the absence of induction media. The extent of hMSCs differentiation is revealed to be dependent on both the pattern shape and the ligand type. Indeed, the spatial patterning of BMP-2, but not RGD peptide, significantly enhances the extent of hMSCs differentiation, suggesting that geometric cues guide stem cells specification into specialized cells in a ligand type dependent manner. Such cell culture models provide an interesting tool to investigate how stem cells perceive and respond to their microenvironment and may contribute to the development of next-generation biomaterials capable of producing clinically relevant volume of bone tissue. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 959-970, 2018.
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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 | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".