177 MRI monitoring of osteogenesis of human bone marrow stromal cell-based tissue engineering constructs
Bibliographic record
Abstract
Bone marrow stromal cells (MSCs) are a promising cell resource of osteoprogenitor cells for bone tissue engineering. However, the diverse characteristics of osteoprogenitor cells within the bone marrow of individual subjects require varying treatments to stimulate osteogenic differentiation. Thus, an effective monitoring system is needed to identify the progression of osteogenesis. Magnetic resonance (MR) microscopy was used in the present study to monitor osteogenesis of tissue engineering (TE) constructs prepared by human bone MSCs seeded on scaffolds of gelatin sponges. The characteristics of MR images and parameters corresponded to osteogenic progression of TE constructs exposed to differentiation medium, significantly differing from control groups exposed to basic medium. Upon quantification, MR image and parameters correlated well to cell seeding densities and alkaline phosphatase activities of various TE constructs. In conclusion, MR can effectively detect the biochemical cascades of osteogenic differentiation of TE constructs and may be a promising, noninvasive monitoring system to provide three-dimensional information for bone tissue engineering.
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 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 | 0.000 | 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) | 0.000 | 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".