Quantitative lipidomic analysis reveals distinct metabolic traits between stromal cell subpopulations in human orbital adipose tissue
Bibliographic record
Abstract
Adipose tissue, a pivotal metabolic regulator, houses diverse stromal cell populations influencing its dynamic functions. Recent omics studies, including transcriptomics and proteomics, have revealed intricate cellular heterogeneity, yet comprehensive metabolic profiling remains limited. Leveraging fluorescence-activated cell sorting (FACS), we isolated PDGFRα+ DPP4+ and PDGFRα+ DPP4- adipose stromal cells (ASCs) from human orbital adipose tissue (OAT). Integrating gene expression analysis, in vitro adipogenesis assays, and quantitative lipidomics, we characterized their functional and metabolic distinctions. DPP4- ASCs exhibited enhanced adipogenic potential and distinct lipidomic profiles, featuring elevated ceramides and triacylglycerols compared to DPP4+ ASCs. Differential gene expression highlighted metabolic and adipogenic gene signatures reflective of their functional roles in adipose tissue remodeling. Our findings underscore the metabolic heterogeneity within OAT stromal fibroblasts, implicating DPP4- ASCs as potent regulators of adipogenesis and metabolic homeostasis. These insights enhance our understanding of adipose tissue plasticity and may inform therapeutic strategies for conditions like thyroid-associated ophthalmopathy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".