Osteoid-Mimicking Dense Collagen/Chitosan Hybrid Gels
Bibliographic record
Abstract
Bone extracellular matrix (ECM) is a 3D network, composed of collagen type I and a number of other macromolecules, including glycosaminoglycans (GAGs), which stimulate signaling pathways that regulate osteoblast growth and differentiation. To model the ECM of bone for tissue regenerative approaches, dense collagen/chitosan (Coll/CTS) hybrid hydrogels were developed using different proportions of CTS to mimic GAG components of the ECM. MC3T3-E1 mouse calvaria preosteoblasts were seeded within plastically compressed Coll/CTS hydrogels with solid content approaching that of native bone osteoid. Dense, cellular Coll/CTS hybrids were maintained for up to 8 weeks under either basal or osteogenic conditions. Higher CTS content significantly increased gel resistance to collagenase degradation. The incorporation of CTS to collagen gels decreased the apparent tensile modulus from 1.82 to 0.33 MPa. In contrast, the compressive modulus of Coll/CTS hybrids increased in direct proportion to CTS content exhibiting an increase from 23.50 to 55.25 kPa. CTS incorporation also led to an increase in scaffold resistance to cell-induced contraction. MC3T3-E1 viability, proliferation, and matrix remodeling capability (via matrix metalloproteinase expression) were maintained. Alkaline phosphatase activity was increased up to two-fold, and quantification of phosphate mineral deposition was significantly increased with CTS incorporation. Thus, dense Coll/CTS scaffolds provide osteoid-like models for the study of osteoblast differentiation and bone tissue engineering.
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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) | 0.001 | 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".