Identification of depot-specific human fat cell progenitors through distinct expression profiles and developmental gene patterns
Bibliographic record
Abstract
Anatomically separate fat depots differ in size, function, and contribution to pathological states, such as the metabolic syndrome. We isolated preadipocytes from different human fat depots to determine whether the basis for this variation is partly attributable to differences in inherent properties of fat cell progenitors. We found that genome-wide expression profiles of primary preadipocytes cultured in parallel from abdominal subcutaneous, mesenteric, and omental fat depots were distinct. Interestingly, visceral fat was not homogeneous. Preadipocytes from one of the two main visceral depots, mesenteric fat, had an expression profile closer to that of subcutaneous than omental preadipocytes, the other main visceral depot. Expression of genes that regulate early development, including homeotic genes, differed extensively among undifferentiated preadipocytes isolated from different fat depots. These profiles were confirmed by real-time PCR analysis of preadipocytes from additional lean and obese male and female subjects. We made preadipocyte strains from single abdominal subcutaneous and omental preadipocytes by expressing telomerase. Depot-specific developmental gene expression profiles persisted for 40 population doublings in these strains. Thus, human fat cell progenitors from different regions are effectively distinct, consistent with different fat depots being separate mini-organs.
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 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 | 0.000 |
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".