E. coli promotes human Vγ9Vδ2 T cell transition from cytokine-producing bactericidal effectors to professional phagocytic killers in a TCR-dependent manner
Bibliographic record
Abstract
γδT cells provide immune-surveillance and host defense against infection and cancer. Surprisingly, functional details of γδT cell antimicrobial immunity to infection remain largely unexplored. Limited data suggests that γδT cells can phagocytose particles and act as professional antigen-presenting cells (pAPC). These potential functions, however, remain controversial. To better understand γδT cell-bacterial interactions, an ex vivo co-culture model of human peripheral blood mononuclear cell (PBMC) responses to Escherichia coli was employed. Vγ9Vδ2 cells underwent rapid T cell receptor (TCR)-dependent proliferation and functional transition from cytotoxic, inflammatory cytokine immunity, to cell expansion with diminished cytokine but increased costimulatory molecule expression, and capacity for professional phagocytosis. Phagocytosis was augmented by IgG opsonization, and inhibited by TCR-blockade, suggesting a licensing interaction involving the TCR and FcγR. Vγ9Vδ2 cells displayed potent cytotoxicity through TCR-dependent and independent mechanisms. We conclude that γδT cells transition from early inflammatory cytotoxic killers to myeloid-like APC in response to infectious stimuli.
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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) | 0.002 | 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".