LAG3 regulates antibody responses in a murine model of kidney transplantation
Bibliographic record
Abstract
Lymphocyte activation gene 3 (LAG3) is a coinhibitory receptor expressed by various immune cells. Although the immunomodulatory potential of LAG3 is being explored in cancer and autoimmunity, there is no information on its role after organ transplantation. Our study investigated the functions of LAG3 in a mouse model of renal allograft rejection. LAG3-/- recipients rapidly rejected MHC-mismatched renal allografts that were spontaneously accepted by WT recipients, with graft histology characteristic of antibody-mediated rejection. Depletion of recipient B cells but not CD8+ T cells significantly extended kidney allograft survival in LAG3-/- recipients. Treatment of WT recipients with an antagonistic LAG3 antibody enhanced anti-donor immune responses and induced kidney damage associated with chronic rejection. The studies of conditional LAG3-/- recipients and mixed bone marrow chimeras demonstrated that LAG3 expression on either T or B cells is sufficient to regulate anti-donor humoral immunity but not to induce acute allograft rejection. The numbers and proinflammatory functions of graft-infiltrating NK cells were markedly increased in LAG3-/- recipients, suggesting that LAG3 also regulates the effector stage of antibody-mediated rejection. These findings identified LAG3 as a regulator of immune responses to kidney allografts and a potential therapeutic target for antibody-mediated rejection prevention and treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".