Regional Adipose Tissue Immune Cell Profiles in Childhood‐Onset and Adult‐Onset Obesity
Bibliographic record
Abstract
Background We do not understand why individuals who have had obesity since childhood are at greater risk of metabolic disease. Objective To examine the effects of obesity onset and adipose tissue region (upper vs. lower body) on the proportion of adipose tissue immune cells. Methods We used flow cytometry to quantify the proportion of immune cells in the stromovascular fraction of abdominal (AB) and femoral (TH) subcutaneous adipose tissue from adults with childhood‐onset (n = 16) or adult‐onset (n = 22) obesity. Results The proportion of CD8+CD3+ T‐cells was greater in AB than TH in childhood‐onset obesity, while greater in TH than AB in adult‐onset obesity. There was no effect of obesity onset on other immune cell types. However, there was an overall effect of region where the proportion of CD45RA+CD8+CD3+ T‐cells was greater in TH than AB, and the proportion of CD206+CD68+ M2‐like macrophages was greater in AB than TH. Conclusion Our results show that there are regional differences in the adipose tissue immune cell profiles between childhood‐onset and adult‐onset obesity. It remains to be seen whether these differences are implicated in increasing the risk of metabolic disease. Support or Funding Information This research was funded by NSERC and the Heart and Stroke Foundation of Canada This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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 | 0.001 | 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) | 0.002 | 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".