Coculture with Late, but Not Early, Human Endothelial Progenitor Cells Up Regulates IL-1<b><i>β</i></b>Expression in THP-1 Monocytic Cells in a Paracrine Manner
Bibliographic record
Abstract
Endothelial progenitor cells (EPCs) have been used in clinical trials to treat ischemic heart disease. Monocyte infiltration plays an important role in inflammation, angiogenesis, and tissue repair during tissue ischemia. It is important to understand the interactions between EPCs and monocytes. In this study, a human EPC/THP-1 monocytic cell coculture system was used to examine EPC effect on IL-1 α , IL-1 β , and TNF- α expression in THP-1 cells. Late, but not early, EPCs upregulated IL-1 β expression at both mRNA and protein levels. In contrast, neither early nor late EPCs affected IL-1 α or TNF- α expression. Coculture with human umbilical vein endothelial cells did not alter IL-1 β expression. It has been shown that activation of integrin β 2 in human neutrophils augments IL-1 β synthesis; however integrin β 2 was not involved in IL-1 β expression in THP-1 cells. Addition of late EPC conditioned medium to THP-1 cell culture led to a modest increase of IL-1 β mRNA levels, indicating that late EPCs upregulate IL-1 β expression partly through a paracrine pathway. IL-1 β , an important inflammation mediator, has been shown to promote EPC function. Our data therefore suggest that late EPCs can exert self-enhancement effects by interacting with monocytes and that EPCs might modulate inflammatory reactions by regulating IL-1 β expression in monocytes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".