Adipocyte-fibroblast bidirectional crosstalk promotes features of fibrosis
Bibliographic record
Abstract
Asthma remains a global disease with rising incidence. It is associated with multiple co-morbidities, where obesity is the most coupled co-morbidity and an important risk factor to severe asthma development. Recently, adipocytes were found to be present in the airway walls, positively correlating with their body mass index (BMI). However, their role in the airway remains unknown. This raises the question about their contribution to asthma airway remodeling, a major pathological feature constituting structural, cellular and extracellular matrix changes in the airways, including fibrosis, a highly progressive form of the disease. To our knowledge, this is the first study that aims to evaluate the influence of obesity on asthma remodeling via adipocyte-fibroblast bidirectional crosstalk. Using an in vitro co-culture model of fibroblasts (normal and asthmatic) and adipocytes (lean and obese), our preliminary data displayed a significant increase in the fibrogenic marker (α-SMA) in normal- fibroblasts co-cultured with lean- and obese- adipocytes; but not in the asthmatic counterpart. On the other hand, a notable increase in α-SMA expression was detected in adipocytes from obese subjects upon co-culturing with asthma- fibroblasts. This was accompanied with a significant reduction in the expression of adipogenic markers (PPARγ, leptin, and adiponectin), thus proposing the loss of their adipogenicity which may influence the pathogenesis of fibrosis. Taken together, this study will provide novel insights into the role of adiposity in the development of airway remodeling, particularly fibrosis. Moreover, it will advance our understanding in developing novel therapeutic strategies for obese asthmatic patients.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".