Differential Localization of Effector and Memory CD8 T Cell Subsets in Lymphoid Organs during Acute Viral Infection
Bibliographic record
Abstract
It is unclear where within tissues subsets of effector and memory CD8 T cells persist during viral infection and whether their localization affects function and long-term survival. Following lymphocytic choriomeningitis virus infection, we found most killer cell lectin-like receptor G1 (KLRG1)(lo)IL-7R(hi) effector and memory cells, which are long-lived and high proliferative capacity, in the T cell zone of the spleen. In contrast, KLRG1(hi)IL-7R(lo) cells, which appear terminally differentiated and have shorter life spans, were exclusively localized to the red pulp. KLRG1(lo)IL-7R(hi) T cells homed to the T cell zone using pertussis toxin-sensitive chemokine receptors and appeared to contact gp38(+) stromal cells, which produce the chemokines CCL19 and CCL21 and the T cell survival cytokine IL-7. The transcription factors T-bet and B lymphocyte-induced maturation protein-1 controlled effector CD8 T cell splenic migration. Effector CD8 T cells overexpressing T-bet homed to the red pulp, whereas those lacking B lymphocyte-induced maturation protein-1 homed to the T cell zone. Upon memory formation, CD62L(+) memory T cells were predominantly found in the T cell zone, whereas CD62L(-) cells were found in the red pulp. Thus, effector and memory CD8 T cell subset localization within tissues is linked to their differentiation states, and this may identify anatomical niches that regulate their longevity and homeostasis.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".