The PPARβ/delta-induced mesenchymal stromal cell secretome has cytoprotective effects via ANGPTL4 in a pre-clinical model of acute lung inflammation
Bibliographic record
Abstract
ABSTRACT Rationale Human bone marrow-derived mesenchymal stromal cells (hBM-MSCs) are known to exert immunomodulatory and pro-reparative effects in vivo . This makes hBM-MSCs an enticing therapeutic candidate for inflammatory diseases, such as acute respiratory distress syndrome (ARDS). The ARDS microenvironment is complex and contains an abundance of free fatty acids (FFAs); which are known to differentially impact MSC functionality. PPARβ/ δ is a ubiquitously expressed nuclear receptor that is activated in response to FFA-binding. PPARβ/ δ has been shown to impact the therapeutic efficacy of mouse MSCs. Objective This study sought to investigate the impact of PPARβ/ δ -modulation on human MSC functionality in vitro and in vivo . Methods hBM-MSCs were exposed to a synthetic PPARβ/ δ agonist/antagonist in the presence or absence of ARDS patient serum and the immunomodulatory and pro-reparative capacity of the MSC secretome was investigated using in vitro assays and a pre-clinical model of LPS-induced acute lung inflammation (ALI). Results Our results highlighted enhanced pro-reparative capacity of PPARβ/ δ -agonised hBM-MSCs secretome in CALU-3 lung epithelial cells, mediated by MSC derived angiopoietin-like 4 (ANGPTL4). PPARβ/ δ -induced ANGPTL4-high MSC secretome facilitated enhanced endothelial barrier integrity in the lungs of ALI mice. Therapeutic effects of PPARβ/ δ -agonised hBM-MSCs secretome were further enhanced by licensing MSCs with human ARDS patient serum. ARDS-licensed PPARβ/ δ -induced ANGPTL4-high MSC secretome had reduced clinical score and weight loss. The role ANGPL4 in these protective effects was confirmed using an anti-ANGPTL4 antibody. Conclusion These findings conclude that the MSC secretome therapeutic effects can be enhanced both in vitro and in vivo through licensing strategies that upregulate the angiogenic factor ANGPTL4. Graphical Abstract
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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".