Growth of Bone Marrow Stromal Cells on RGD‐Grafted Thermoreversible (NiPAM) Polymers
Bibliographic record
Abstract
Abstract Thermoreversible polymers based on N‐isopropylacrylamide (NiPAM) are being explored for tissue engineering applications. The polymers exhibit a solubility change as a function of temperature, which could be utilized for convenient delivery of proteins and cells. Being synthetic, however, the polymer does not allow direct cell attachment. To overcome this limitation, Arginine‐Glycine‐Aspartic Acid (RGD)‐containing peptides were grafted to the polymers in this study. Attachment of rat bone marrow stromal cells (BMSC) on NiPAM‐based polymers was increased by RGD‐grafting, but long‐term cell growth was not as robust as the BMSC grown on tissue culture polystyrene. However, the expression of specific alkaline phosphate activity (ALP/cell; an osteogenic marker) was elevated for cells grown on polymer films and RGD‐grafting was not beneficial in this regard. Whereas basic Fibroblast Growth Factor suppressed the ALP/cell activity, Bone Morphogenetic Protein‐2 stimulated ALP/cells activity for cells grown on polymer films. These results were in line with our previous studies on the osteogenic response of a cell line (C2C12) and stressed the need to improve cell proliferation on NiPAM surfaces, while preserving the beneficial effect of the polymer on osteogenic markers.
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.
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".