Distribution, function, and prognostic value of cytotoxic T lymphocytes in follicular lymphoma: a 3-D tissue-imaging study
Bibliographic record
Abstract
CD8+ CTLs are thought to play a role in the control of follicular lymphoma (FL). Yet, the link between CTL tissue distribution, activation status, ability to kill FL cells in vivo, and disease progression is still elusive. Pretreatment lymph nodes from FL patients were analyzed by IHC (n = 80) or by 3-color confocal microscopy (n = 10). IHC revealed a rich infiltrate of CD8+ granzyme B+ (GrzB) cells in FL interfollicular spaces. Accordingly, confocal microscopy showed an increased number of CD3+CD8+GrzB+ CTLs and a brighter GrzB staining in individual CTL in FL samples compared with reactive lymph nodes. CTLs did not penetrate tumor nodules. In 3-dimensional (3-D) image reconstructions, CTLs were detected at the FL follicle border where they formed lytic synapse-like structures with FL B cells and with apoptotic cells, suggesting an in situ cytotoxic function. Finally, although GrzB expression in CTLs did not correlate with risk factors, high GrzB content correlated with prolonged progression free-survival (PFS) after rituximab-combined chemotherapy. Our results show the recruitment of armed CTLs with a tumor-controlling potential into FL lymph nodes and suggest that CTL-associated GrzB expression could influence PFS in FL patients having received rituximab-combined chemotherapy.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".