Abstract 411: Decreased Circulating and Neutrophil Mediated Vegf Release in Stable Long-term Cardiac Transplant Recipients
Bibliographic record
Abstract
Background: A chronic state of inflammation may contribute to the long-term cardiac and vascular complications following cardiac transplantation (CTx). However, the assessment of neutrophil pro- or anti-inflammatory response has not been investigated in long-term CTx recipients. Herein, we measured the circulating levels of pro-inflammatory (interleukin-8; IL-8), anti-inflammatory (interleukin 1 receptor antagonist; IL-1RA) and a pro-angiogenic and inflammatory cytokine (vascular endothelial growth factor; VEGF), concomitantly with their release from neutrophils of CTx recipients and as compared to healthy volunteers. Methods: Eighteen CTx recipients aged 49.6 ± 3.1 years being transplanted for 145 ± 20 months were aged-matched to 20 healthy control (HC) subjects. Seven (39%) patients exhibited coronary allograft vasculopathy (all CAV1). VEGF, IL-8 and IL-1ra plasmatic levels were measured in resting state. Circulating neutrophils were isolated, purified and stimulated by vehicle (PBS), N-Formyl-Met-Leu-Phe (fMLP, 10-7 M), bacterial lipopolysaccharide (LPS, 1 μg/ml), or tumor necrosis factor alpha (TNF-α, 10 ng/ml). Results: Compared with HC, CTx recipients exhibited a decrease (-80%) in circulating levels of VEGF (225 ± 42 (HC) versus 44 ± 10 pg/ml (CTx); (p < 0.001). There were no differences in the levels of IL-8 and IL-1ra. Under basal or stimulated conditions, neutrophils from CTx patients exhibited a significant decrease on their capacity to release VEGF, IL-8 and IL-1ra upon stimulation. Conclusions: Long-term CTx recipients exhibit a marked reduction in the circulating levels of VEGF, as well as neutrophil-mediated release of VEGF, IL-8 and IL-1ra. The mechanisms and physiological impacts of these findings in relationship with various severities of CAV deserve additional investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".