COMMITTED ADIPOGENIC PROGENITORS ARE RESPONSIBLE FOR NOVEL ADIPOCYTE GENERATION IN RESPONSE TO DIETARY STIMULI
Bibliographic record
Abstract
During adult life white fat depots can expand via hyperplasia and adipocyte infiltration can appear in aging or disease of non-adipose tissues. These observations suggest that stem/progenitor cells exist that can respond to a variety of stimuli to generate new adipocytes. We used a combination of surface markers to prospectively identify a population of cells containing all adipogenic colony-forming potential in skeletal muscle, subcutaneous and perigonadal adipose depots (adipogenic progenitors, APs). We did not observe any generation of cartilage, bone or muscle from AP cultures, suggesting that APs are committed to the adipocyte lineage. Confocal- and immunoelectron- microscopy analysis on tissues from BrdU-treated high fat diet-fed animals confirms the production of new adipocytes during weight gain. APs appear to participate in this response in a depot- specific manner. Furthermore, we observed a significant correlation between the size of the fat pad and frequency of actively cycling AP cells. Taken together, we show that we have identified an abundant population of lineage-restricted adipogenic progenitors. Importantly, our data suggests that during weight gain, new adipose generation relies on proliferation of these cells. AJ is supported by a Vancouver Coastal Health–CIHR–UBC MD/PhD Studentship Award.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".