Innate Immunity in the Therapeutic Actions of Endothelial Progenitor Cells in Pulmonary Hypertension
Bibliographic record
Abstract
Direct injection of endothelial progenitor cells (EPCs) into the circulation has shown therapeutic benefit in both experimental models and clinical studies of pulmonary arterial hypertension (PAH). Using the monocrotaline (MCT)-induced rat model of PAH, we investigated the role of innate immunity in the therapeutic activity of two types of putative EPCs derived from human peripheral blood mononuclear cells: an early population of endothelial-like, culture-modified monocytes (E-CMMs) and late-outgrowth EPCs (L-EPCs), which exhibit a strong endothelial phenotype. In the athymic nude rat, E-CMMs prevented MCT-induced increases in right ventricular systolic pressure (P < 0.001) and right ventricular hypertrophy (P < 0.01) when administered 3 days after MCT challenge, whereas L-EPCs were ineffective. However, in both cases, there was a lack of cell persistence within the lungs at 24 hours after injection, likely due to residual natural killer (NK) cell activity in the model. Although ablation of NK and NK-T cells with anti-asialo-GM-1 antiserum enhanced the retention of both E-CMMs and L-EPCs, still no benefit was seen with L-EPCs, and the efficacy of E-CMMs was lost. In vitro characterization revealed that E-CMMs resemble a regulatory subtype of dendritic cells, producing IL-10, but not IL-12, in response to inflammatory stimuli. Coculture studies demonstrated the capacity of E-EPCs to stimulate autologous human and nude rat NK cells in vitro. These data support a novel mode of action for human E-CMMs in the prevention of PAH, whereby they act through an immune-dependent mechanism, potentially involving the stimulation of NK cells.
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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) | 0.001 | 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".