Basiliximab impairs regulatory T cell (TREG) function and could affect the short-term graft acceptance in children with heart transplantation
Bibliographic record
Abstract
CD25, the alpha chain of the IL-2 receptor, is expressed on activated effector T cells that mediate immune graft damage. Induction immunosuppression is commonly used in solid organ transplantation and can include antibodies blocking CD25. However, regulatory T cells (Tregs) also rely on CD25 for their proliferation, survival, and regulatory function. Therefore, CD25-blockade may compromise Treg protective role against rejection. We analysed in vitro the effect of basiliximab (BXM) on the viability, phenotype, proliferation and cytokine production of Treg cells. We also evaluated in vivo the effect of BXM on Treg in thymectomized heart transplant children receiving BXM in comparison to patients not receiving induction therapy. Our results show that BXM reduces Treg counts and function in vitro by affecting their proliferation, Foxp3 expression, and IL-10 secretion capacity. In pediatric heart-transplant patients, we observed decreased Treg counts and a diminished Treg/Teff ratio in BXM-treated patients up to 6-month after treatment, recovering baseline values at the end of the 12-month follow up period. These results reveal that the use of BXM could produce detrimental effects on Tregs, and support the evidence suggesting that BXM induction could impair the protective role of Tregs in the period of highest incidence of acute graft rejection.
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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".