Extracellular Vesicles From Kidney Allografts Express miR-218-5p and Alter Th17/Treg Ratios
Bibliographic record
Abstract
Delayed graft function (DGF) in kidney transplantation is associated with ischemic injury and carries long term functional and immunological risks. Extracellular vesicles (EV) released from allografts may signal a degree of ischemic stress, and are thought to play an important role in the development of anti-donor immunity. Here, we show that kidney perfusate-derived extracellular vesicles (KP-EV) express donor-specific human leukocyte antigen. KP-EV from kidneys that experience DGF increase the T-helper 17 (Th17) to T-regulatory (Treg) ratio in third party peripheral blood mononuclear cells to a greater degree than those from kidneys with immediate function. We report miR-218-5p upregulation in KP-EV of kidney transplant recipients with DGF. Levels of miR-218-5p in KP-EV inversely correlated with recipient eGFR at multiple time points following transplantation. Additionally, the degree of increase in Th17/Treg ratio by KP-EV positively correlated with miR-218-5p expression in KP-EV samples. Taken together, these data provide evidence that KP-EV may contribute to modulating immune responses in transplant recipients. This could lead to novel intervention strategies to inhibit DGF in order to improve graft function and survival.
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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) | 0.001 | 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".