Functional Consequences of Increased Virus-specific CD8+ Effector Memory T cells in the Response to Influenza in Older Adults (130.4)
Bibliographic record
Abstract
Abstract Background: The decline in adaptive immune function with age is a major cause for increased risk of complicated influenza illness in older adults especially those with congestive heart failure (CHF). Changes in the CD8+ T cell response to the virus may explain the increased risk of influenza in the older population. Methods: The response to influenza in 12-hour peripheral blood mononuclear cell (PBMC) cultures from vaccinated healthy young (20-40 y.o.) and older adults (age =60 y.o.) with or without CHF was measured in different CD8+ T cell subsets. Results: In unstimulated PBMC, older compared to young adults showed a higher proportion of GrB+CD8+ T cells, and these T cells also expressed higher levels of CD107a in the CHF group. Healthy young and older adults showed a significant increase in the GrzB+CD8+ T cells expressing CD107a, consistent with a cytolytic effector function; older adults with CHF had no response. Preliminary results suggest that this poor response is associated with an increased proportion of terminally-differentiated, effector memory (CD8+CD45RA+) T cells. Conclusions: An accumulation of terminally differentiated CD8+CD45RA+ T cells have an effector phenotype but do not respond to influenza virus and may explain the increased risk of influenza in the older adults.
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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".