p40 homodimers bridge ischemic tissue inflammation and heterologous alloimmunity in mice via IL-15 transpresentation
Bibliographic record
Abstract
Virus-induced memory T cells often express functional cross-reactivity, or heterologous immunity, to other viruses and to allogeneic MHC molecules that is an important component of pathogenic responses to allogeneic transplants. During immune responses, antigen-reactive naive and central memory T cells proliferate in secondary lymphoid organs to achieve sufficient cell numbers to effectively respond, whereas effector memory T cell proliferation occurs directly within the peripheral inflammatory microenvironment. Mechanisms driving heterologous memory T cell proliferation and effector function expression within peripheral tissues remain poorly understood. Here, we dissected proliferation of heterologous donor-reactive memory CD8+ T cells and their effector functions following infiltration into heart allografts with low or high intensities of ischemic inflammation. Proliferation within both ischemic conditions required p40 homodimer-induced IL-15 transpresentation by graft DCs, but expression of effector functions mediating acute allograft injury occurred only in high-ischemic allografts. Transcriptional responses of heterologous donor-reactive memory CD8+ T cells were distinct from donor antigen-primed memory CD8+ T cells during early activation in allografts and at graft rejection. Overall, the results provide insights into mechanisms driving heterologous effector memory CD8+ T cell proliferation and the separation between proliferation and effector function that is dependent on the intensity of inflammation within the tissue microenvironment.
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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 | 0.001 |
| 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".