Unveiling the Cutting-Edge Impact of Polarized Macrophage-Derived Extracellular Vesicles and MiRNA Signatures on TGF-β Regulation within Lung Fibroblasts
Bibliographic record
Abstract
Depending on local cues, macrophages can polarize into classically activated (M1) or alternatively activated (M2) phenotypes. This study investigates the impact of polarized macrophage-derived Extracellular Vesicles (EVs) (M1 and M2) and their cargo of miRNA-19a-3p and miRNA-425-5p on TGF-β production in lung fibroblasts. EVs were isolated from supernatants of M0, M1, and M2 macrophages and quantified using nanoscale flow cytometry prior to fibroblast stimulation. The concentration of TGF-β in fibroblast supernatants was measured using ELISA assays. The expression levels of miRNA-19a-3p and miRNA-425-5p were assessed via TaqMan-qPCR. TGF-β production after stimulation with M0-derived EVs and with M1-derived EVs increased significantly compared to untreated fibroblasts. miRNA-425-5p, but not miRNA-19a-3p, was significantly upregulated in M2-derived EVs compared to M0- and M1-derived EVs. This study demonstrates that EVs derived from both M0 and M1 polarized macrophages induce the production of TGF-β in fibroblasts, with potential regulation by miRNA-425-5p.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".