<i>Schistosoma mansoni</i> Worms Induce Anergy of T Cells via Selective Up-Regulation of Programmed Death Ligand 1 on Macrophages
Bibliographic record
Abstract
Infectious pathogens can selectively stimulate activation or suppression of T cells to facilitate their survival within humans. In this study we demonstrate that the trematode parasite Schistosoma mansoni has evolved with two distinct mechanisms to suppress T cell activation. During the initial 4- to 12-wk acute stages of a worm infection both CD4(+) and CD8(+) T cells are anergized. In contrast, infection with male and female worms induced T cell anergy at 4 wk, which was replaced after egg laying by T cell suppression via a known NO-dependent mechanism, that was detected for up to 40 wk after infection. Worm-induced anergy was mediated by splenic F4/80(+) macrophages (Mphi) via an IL-4-, IL-13-, IL-10-, TGF-beta-, and NO-independent, but cell contact-dependent, mechanism. F4/80(+) Mphi isolated from worm-infected mice were shown to induce anergy of naive T cells in vitro. Furthermore, naive Mphi exposed to live worms in vitro also induced anergy in naive T cells. Flow cytometry on in vivo and in vitro worm-modulated Mphi revealed that of the family of B7 costimulatory molecules, only programmed death ligand 1 (PD-L1) was selectively up-regulated. The addition of inhibitory mAb against PD-L1, but not PD-L2, to worm-modulated Mphi completely blocked the ability of these cells to anergize T cells. These data highlight a novel mechanism through which S. mansoni worms have usurped the natural function of PD-L1 to reduce T cell activation during early acute stages of infection before the subsequent emergence of egg-induced T cell suppression in the chronic stages of infection.
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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".