EBV-Specific CD8+ T Cell Memory: Relationships Between Epitope Specificity, Cell Phenotype, and Immediate Effector Function
Bibliographic record
Abstract
EBV infection in humans induces CD8+ T cell memory to viral epitopes derived from both lytic and latent cycle Ags. We have analyzed the relationship between the phenotype and function of the memory pool of T cells specific for these Ags. Lytic epitope-specific populations were heterogeneous in terms of CD45RO/RA and CD28 expression, whereas latent epitope-specific populations were uniformly CD45RO+ and CD28+, consistent with the higher antigenic challenge from lytic epitopes driving some memory cells toward a CD45RA+, CD28- phenotype. However, both types of memory population showed immediate epitope-specific cytotoxicity and type 1 cytokine production in ex vivo assays. Cytotoxic function was not associated with preactivated T cells, as EBV-specific populations were negative for activation markers such as CD69 or CD38, nor could cytotoxic function be ascribed to CD27- or CD56+ subsets, as such cells were not detected in EBV-specific memory. Furthermore, cytotoxicity was not limited to CD45RA+ and/or CD28- fractions, but also was observed in CD45RO+, CD28+ populations in lytic and latent epitope-specific memory. Cytokine (IFN-gamma, TNF-alpha) responses, measured by intracytoplasmic staining after peptide stimulation, also were detectable in CD45RO+ and RA+ subsets as well as CD28+ and CD28- subsets. Of other markers that were heterogeneous in both lytic and latent epitope populations, CCR7 gave the best discrimination of functionality; thus, CCR7+ cells consistently failed to give an IFN-gamma or TNF-alpha response, whereas many CCR7- cells were responsive. Our data are consistent with effector functions having a broad distribution among phenotypically distinct subsets of "effector memory" cells that have lost the CCR7 marker.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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 teacher head, 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".