Pretransplant, Th17 dominant alloreactivity in highly sensitized kidney transplant candidates
Bibliographic record
Abstract
Introduction Sensitization to donor human leukocyte antigen (HLA) molecules prior to transplantation is a significant risk factor for delayed access to transplantation and to long-term outcomes. Memory T cells and their cytokines play a pivotal role in shaping immune responses, thereby increasing the risk of allograft rejection among highly sensitized patients. This study aims to elucidate the precise contribution of different CD4+memory T cell subsets to alloreactivity in highly sensitized (HS) kidney transplant recipients. Methods and results Stimulation of peripheral blood mononuclear cells (PBMC) with various polyclonal stimulating agents to assess non-specific immune responses revealed that HS patients exhibit elevated immune reactivity even before kidney transplantation, compared to non-sensitized (NS) patients. HS patients' PBMC displayed higher frequencies of CD4+T cells expressing IFNγ, IL4, IL6, IL17A, and TNFαand secreted relatively higher levels of IL17A and IL21 upon stimulation with PMA/ionomycin. Additionally, PBMC from HS patients stimulated with T cell stimulating agent phytohemagglutinin (PHA) exhibited elevated expression levels ofIFNγ,IL4and,IL21. On the other hand, stimulation with a combination of resiquimod (R848) and IL2 for the activation of memory B cells demonstrated higher expression ofIL17A,TNFα andIL21, as determined by quantitative real-time PCR. A mixed leukocyte reaction (MLR) assay, employing third-party donor antigen presenting cells (APCs), was implemented to evaluate the direct alloreactive response. HS patients demonstrated notably higher frequencies of CD4+T cells expressing IL4, IL6 and IL17A. Interestingly, APCs expressing recall HLA antigens triggered a stronger Th17 response compared to APCs lacking recall HLA antigens in sensitized patients. Furthermore, donor APCs induced higher activation of effector memory T cells in HS patients as compared to NS patients. Conclusion These results provide an assessment of pretransplant alloreactive T cell subsets in highly sensitized patients and emphasize the significance of Th17 cells in alloimmune responses. These findings hold promise for the development of treatment strategies tailored to sensitized kidney transplant recipients, with potential clinical implications.
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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 | 0.000 |
| 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".