CD154 and IL-2 Signaling of CD4+ T Cells Play a Critical Role in Multiple Phases of CD8+ CTL Responses Following Adenovirus Vaccination
Bibliographic record
Abstract
Adenoviral (AdV) vectors represent most commonly utilized viral vaccines in clinical studies. While the role of CD8(+) cytotoxic T lymphocyte (CTL) responses in mediating AdV-induced protection is well understood, the involvement of CD4(+) T cell-provided signals in the development of functional CD8(+) CTL responses remain unclear. To explore CD4(+) T helper signals required for AdVova-stimulated CTL responses, we established an adoptive transfer system by transferring CD4(+) T cells derived from various knock out and transgenic mice into wild-type and/or CD4-deficient animals, followed by immunizing with recombinant ovalbumin (OVA)-expressing AdVova vector. Without CD4(+) T help, both primary and memory CTL responses were greatly reduced in this model, and were associated with increased PD-1 expression. The provision of OVA-specific CD4(+) T help in CD4(+) T cell-deficient mice restored AdVova-induced primary CTL responses, and supported survival and recall responses of AdVova-stimulated memory CTLs. These effects were specifically mediated by CD4(+) T cell-produced IL-2 and CD154 signals. Adoptive transfer of "helped" or "unhelped" effector and memory CTLs into naïve CD4(+) T cell-deficient or -sufficient mice also revealed an additional role for polyclonal CD4(+) T cell environment in the survival of AdVova-stimulated CTLs, partially explaining the extension of CTL contraction phase. Finally, during recall responses, CD4(+) T cell environment, particularly involving memory CD4(+) T cells, greatly enhanced expansion of memory CTLs. Collectively, our data strongly suggest a critical role for CD4(+) T help in multiple phases of AdV-stimulated CTL responses, and could partially explain certain failures in AdV-based immunization trials targeting malignant tumors and chronic diseases that are often associated with compromised CD4(+) T cell population and function.
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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) | 0.001 | 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 | 0.001 |
| 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".