Advanced age does not impair the development of functional memory CD8+ T cells following West Nile virus infection (83.4)
Bibliographic record
Abstract
Abstract West Nile virus (WNV) infection of aged patients typically leads to the development of severe neuroencephalitis. Studies in mice have elucidated an important role for CD8+ T cell function in controlling WNV infection and we hypothesized that the increased severity of WNV illness in the aged results from impaired CD8+ T cell function due to immunosenescence. We examined the functional profile of WNV-specific CD8+ T cell memory responses from a cohort of young and aged WNV infected patients using polychromatic flow cytometry. We quantified production of IFN-γ, TNF-α, IL-2 and CD107a mobilization by WNV-specific CD8+ T cells. We did not observe any relationship between advanced age and either the breadth or the magnitude of CD8+ T cell function. The magnitude of IFN-γ and TNF-α responses to WNV epitope stimulation did not decline with advanced age. Production of IL-2 was not detected from either young or aged CD8+ T cells. The ability to degranulate in response to virus peptide was also the same in young and aged patients. Collectively these data fail to support our hypothesis and suggest that, contrary to current models of immunosenescence, aged patients do develop functional CD8+ T cell immunity following exposure to a novel virus infection. This work was funded by a contract from NIAID (N01-AI-40066).
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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".