Is Adipocyte Differentiation the Default Lineage for Mesenchymal Stem/Progenitor Cells after Loss of Mechanical Loading? A Perspective from Space Flight and Model Systems
Bibliographic record
Abstract
Mesenchymal stem/progenitor cells (MSC/MPC) are found in many tissues and fluids including bone marrow, adipose tissues, muscle, synovial membranes, synovial fluid, and blood. Such cells from different sources can proliferate and differentiate into different lineages (e.g. osteogenic, chondrogenic and adipogenic) after suitable stimulation. However, details regarding the regulation of MSC/MPC proliferation and differentiation status are still unclear and it is likely that regulation involves both biological and mechanical influences in the different environments. It has been noted that in humans and preclinical animal models that exposure to microgravity/space flight or prolonged bed rest (a surrogate for microgravity) can lead to infiltration of skeletal muscle and bone marrow with fat. Similarly, in preclinical models treated with multiple intramuscular injections of Botulinum Toxin A to induce muscle weakness and atrophy, there is also an infiltration of the muscle with fat. The origins and basis for these fat deposits are largely unknown, but there is a possibility that the altered mechanical and biological environments lead to dysregulation of MSC/MPC and progression to preferential differentiation towards the adipocyte lineage. Furthermore, loss of MSC regulatory control by either mechanical and/or biological factors may also contribute to their involvement in obesity development and progression. Thus, the utility of using MSC/MPC from some sources for tissue engineering purposes may be compromised and further research regarding optimal loading for tissue engineering purposes is likely warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".