Macrophages Alter the Differentiation‐Dependent Decreases in Fibronectin and Collagen I/III Protein Levels in Human Preadipocytes
Bibliographic record
Abstract
Adipose tissue of obese individuals is characterized by increased fibrosis and macrophage infiltration. Extensive remodeling of the extracellular matrix (ECM) that occurs during adipogenesis can be influenced by macrophages, but it remains unclear how macrophage-secreted factors alter preadipocyte ECM protein expression under non-adipogenic versus adipogenic conditions. Confluent human subcutaneous abdominal preadipocytes were cultured for 14 days, with or without adipogenic inducers, in either control medium, medium conditioned by THP-1 monocytes (THP-1-MonCM), or medium conditioned by THP-1 macrophages (THP-1-MacCM). Under non-adipogenic conditions in THP-1-MacCM, collagen I/III and fibronectin protein levels rose by 40 and 70 %, respectively (p < 0.05, n = 3; compared to control non-adipogenic medium). When preadipocytes were exposed to adipogenic inducers in THP-1-MacCM, collagen I/III levels increased by 50 %, but those of fibronectin fell by 48 %, both compared to non-adipogenic THP-1-MacCM conditions. The rise in collagen I/III levels contrasts with the 51 % decrease in collagen I/III that occurs with induction of differentiation in control medium, whereas, the decrease in fibronectin is more modest, but consistent in THP-1-MacCM (48 %) and control medium (92 %). A similar effect on fibronectin levels occurred using medium conditioned by LPS-treated human monocyte-derived macrophages (MD-MacCM). Our data indicate macrophage-derived factors regulate levels of collagen I/III and fibronectin in preadipocytes under non-adipogenic and adipogenic conditions. Further studies are needed to determine if these changes in these ECM proteins contribute to the anti-adipogenic action of MacCM.
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 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 | 0.000 | 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) | 0.000 | 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".