Staphylococcal alpha-toxin tilts the balance between malignant and non-malignant CD4 <sup>+</sup> T cells in cutaneous T-cell lymphoma
Bibliographic record
Abstract
Staphylococcus aureus is implicated in disease progression in cutaneous T-cell lymphoma (CTCL). Here, we demonstrate that malignant T cell lines derived from CTCL patients as well as primary malignant CD4+ T cells from Sézary syndrome patients are considerably more resistant to alpha-toxin-induced cell death than their non-malignant counterparts. Thus, in a subset of Sézary syndrome patients the ratio between malignant and non-malignant CD4+ T cells increases significantly following exposure to alpha-toxin. Whereas toxin-induced cell death is ADAM10 dependent in healthy CD4+ T cells, resistance to alpha-toxin in malignant T cells involves both downregulation of ADAM10 as well as other resistance mechanisms. In conclusion, we provide first evidence that Staphylococcus aureus derived alpha-toxin can tilt the balance between malignant and non-malignant CD4+ T cells in CTCL patients. Consequently, alpha-toxin may promote disease progression through positive selection of malignant CD4+ T cells, identifying alpha-toxin as a putative drug target in CTCL.
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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".