Endothelial growth factors VEGF and bFGF differentially enhance monocyte and neutrophil recruitment to inflammation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) are produced at sites of inflammation. Previously, we demonstrated that bFGF enhances leukocyte recruitment and endothelial cell adhesion molecule (CAM) expression during inflammation. Here, we investigated the influence of VEGF during acute inflammation and whether VEGF and bFGF cooperate to modulate leukocyte recruitment. Inflammation was induced in skin of rats by intradermal injection of inflammatory stimuli +/- VEGF +/- bFGF. Migration of 51Cr-monocytes and 111In-polymorphonuclear leukocytes (PMN) to the dermal lesions and 125I-anti-CAM monoclonal antibody binding to the dermal vasculature were quantitated after 2 h. VEGF significantly enhanced tumor necrosis factor alpha (TNF-alpha)-induced monocyte recruitment by 39 +/- 16% and increased P-selectin, E-selectin, and intercellular CAM-1 expression by two- to threefold over TNF-alpha alone. However, recruitment of monocytes to TNF-alpha + interferon-gamma (IFN-gamma) and of PMN to all stimuli tested was not affected by VEGF. In contrast, bFGF enhanced recruitment of both leukocyte types to all stimuli tested. With the potent TNF-alpha + IFN-gamma stimulus, in contrast to bFGF, VEGF did not enhance E-selectin or ICAM-1 expression. bFGF, but not VEGF, increased the chemotactic activity for PMN in TNF-alpha + IFN-gamma-inflamed sites by 54%. The limited effect of VEGF on these mechanisms likely contributed to the differential effect of VEGF and bFGF on leukocyte recruitment. However, VEGF + bFGF increased PMN recruitment more than did either factor alone. Thus, bFGF and VEGF differentially but synergistically enhance leukocyte recruitment to inflammatory stimuli and individually as well as jointly function as positive regulators of inflammatory cell recruitment.
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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 | 0.000 |
| 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) | 0.000 | 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 it