Adipose-derived stem cells from the brown bear (Ursus arctos) spontaneously undergo chondrogenic and osteogenic differentiation in vitro
Bibliographic record
Abstract
In the den, hibernating brown bears do not develop tissue atrophy or organ damage, despite almost no physical activity. Mesenchymal stem cells could play an important role in tissue repair and regeneration in brown bears. Our objective was to determine if adipose tissue-derived stem cells (ASCs) can be recovered from wild Scandinavian brown bears and characterize their differentiation potential. Following immobilization of wild brown bears 7-10 days after leaving the den in mid-April, adipose tissue biopsies were obtained. ASCs were recovered from 6 bears, and shown to be able to undergo adipogenesis and osteogenesis in monolayer cultures and chondrogenesis in pellet cultures. Remarkably, when grown in standard cell culture medium in monolayer cultures, ASCs from yearlings spontaneously formed bone-like nodules surrounded by cartilaginous deposits, suggesting differentiation into osteogenic and chondrogenic lineages. This ability appears to be lost gradually with age. This is the first study to demonstrate stem cell recovery and growth from brown bears, and it is the first report of ASCs spontaneously forming extracellular matrix characteristic of bone and cartilage in the absence of specific inducers. These findings could have implications for the use of hibernating brown bears as a model to study disuse osteoporosis.
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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) | 0.000 | 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 | 0.001 |
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".