The Antigen-Presenting Potential of Vγ9Vδ2 T Cells During Plasmodium falciparum Blood-Stage Infection
Bibliographic record
Abstract
During Plasmodium falciparum infections, erythrocyte-stage parasites inhibit dendritic cell maturation and function, compromising effective antimalarial adaptive immunity. Human Vγ9Vδ2 T cells can act in vitro as antigen-presenting cells (APCs) and induce αβ T-cell activation. However, the relevance of this activity in vivo has remained elusive. Because Vγ9Vδ2 T cells are activated during the early immune response against P. falciparum infection, we investigated whether they could contribute to the instruction of adaptive immune responses toward malaria parasites. In P. falciparum-infected patients, Vγ9Vδ2 T cells presented increased surface expression of APC-associated markers HLA-DR and CD86. In response to infected red blood cells in vitro, Vγ9Vδ2 T cells upregulated surface expression of HLA-DR, HLA-ABC, CD40, CD80, CD83, and CD86, induced naive αβ T-cell responses, and cross- presented soluble prototypical protein to antigen-specific CD8+ T cells. Our findings qualify Vγ9Vδ2 T cells as alternative APCs, which could be harnessed for therapeutic interventions and vaccine design.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".