Substantial Intrapatient Differences in the Breadth and Specificity of HIV-Specific CD8+ T-Cell Interferon-γ and Proliferation Responses
Bibliographic record
Abstract
HIV vaccine design and evaluation require a better understanding of protective immune responses. HIV-specific CD8+ T-cell responses have been characterized extensively using interferon-gamma (IFN-gamma) enzyme-linked immunosorbent spot (ELISPOT) assays, which do not always correlate with control of viral replication or disease progression. Alternative aspects of CD8+ T-cell responses, in particular those associated with a central memory (Tcm) phenotype, may be more protective against disease progression. To determine the extent that the breadth and specificity of HIV-specific CD8+ T-cell responses differ based on immunological readout, we screened in HIV-infected Kenyan sex workers for responses to HIV Env using IFN-gamma ELISPOT and 6-day carboxyfluorescein succinimidyl ester-based proliferation assays. This comparison revealed substantial differences in the epitopes recognized when the assay readout was IFN-gamma versus proliferation. Although 24 and 41 IFN-gamma and proliferative responses were identified, overlapping specificity was observed for only 5 responses. Breadth also differed between assays in several patients. Env-specific IFN-gamma breadth was found to correlate inversely with CD4 count (r = -0.66, P = 0.005), although this was not the case for proliferation. These data suggest that efforts to define HIV-specific CD8+ T-cell responses may need to be revisited using additional immunological readouts.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".