EXTRACELLULAR VESICLES RELEASED FROM ENHANCED ADIPOSE TISSUE-DERIVED MESENCHYMAL STROMAL CELLS POLARIZE MACROPHAGES TOWARDS A DISTINCT IMMUNOMODULATORY PROFILE
Bibliographic record
Abstract
Background & Aim Adipose tissue-derived mesenchymal stromal cells (MSC(AT)s possesses immunomodulatory capabilities that make them promising candidates for anti-inflammatory and regenerative applications. Their therapeutic effect is believed to be partially mediated by the release of small extracellular vesicles (sEVs). Previous work from our lab showed that MSC(AT)s treated under different non-genetic cell enhancement strategies significantly influenced their immunomodulatory fitness. This led us to hypothesize that enhanced MSC(AT)s would also produce sEVs with enhanced immunomodulatory activity. Furthermore, we investigated differences in the role of surface CD73-Ecto-5’-nucleotidase in sEV-mediated macrophage M2-like polarization between non-enhanced and enhanced MSC(AT)-sEVs. Methodology MSC(AT) grown to confluency were exposed to enhancement conditions: pro-inflammatory cytokine priming, 3D aggregation, and hypoxia. MSC(AT) conditioned media was collected and sEV fraction was isolated by differential ultracentrifugation. sEV was characterized by TEM and NTA. Protein count and identity were assessed by BCA and western blot, respectively. Peripheral blood-derived monocytes were differentiated to macrophages and treated with 10µg of non-enhanced or enhanced sEVs for 48 hours. Role of CD73 was assessed by incubating macrophages with CD73 inhibitor prior to sEV treatment. Macrophage polarization was assessed by TNFa secretion with ELISA, gene expression changes by RT-qPCR, and phagocytic ability by fluorescent bead uptake. Results There were no differences observed between non-enhanced and enhanced sEVs’ immunomodulatory activity. ELISA results showed that sEV conditions suppressed macrophage TNFa secretion to similar extents as M2 macrophage control. However, sEV conditions clustered together and distinctively from classical M1/M2 phenotypes, inducing a mixed pro- and anti-inflammatory profile. Lastly, ELISA results of CD73-inhibited macrophages showed significant reduction of TNFa suppression only for non-enhanced sEV and not for enhanced conditions. Conclusion While both sEV conditions can polarize macrophages towards an anti-inflammatory M2-like phenotype, non-genetic cell enhancement strategies could not produce sEVs with enhanced immunomodulatory capabilities. This likely implies that enhanced sEV are acting through different mechanisms of action than CD73-Ecto 5’-nucleotidase to achieve similar levels of polarization as non-enhanced sEV.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.001 | 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".