A PET Imaging Strategy to Visualize Activated T Cells in Acute Graft-versus-Host Disease Elicited by Allogenic Hematopoietic Cell Transplant
Bibliographic record
Abstract
Abstract A major barrier to successful use of allogeneic hematopoietic cell transplantation is acute graft-versus-host disease (aGVHD), a devastating condition that arises when donor T cells attack host tissues. With current technologies, aGVHD diagnosis is typically made after end-organ injury and often requires invasive tests and tissue biopsies. This affects patient prognosis as treatments are dramatically less effective at late disease stages. Here, we show that a novel PET radiotracer, 2′-deoxy-2′-[18F]fluoro-9-β-D-arabinofuranosylguanine ([18F]F-AraG), targeted toward two salvage kinase pathways preferentially accumulates in activated primary T cells. [18F]F-AraG PET imaging of a murine aGVHD model enabled visualization of secondary lymphoid organs harboring activated donor T cells prior to clinical symptoms. Tracer biodistribution in healthy humans showed favorable kinetics. This new PET strategy has great potential for early aGVHD diagnosis, enabling timely treatments and improved patient outcomes. [18F]F-AraG may be useful for imaging activated T cells in various biomedical applications. Cancer Res; 77(11); 2893–902. ©2017 AACR.
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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".