Quantitative and Qualitative Assessment of Human Immunodeficiency Virus Type 1 (HIV‐1)–Specific CD4<sup>+</sup>T Cell Immunity to<i>gag</i>in HIV‐1–Infected Individuals with Differential Disease Progression: Reciprocal Interferon‐γ and Interleukin‐10 Responses
Bibliographic record
Abstract
The human immunodeficiency virus type 1 (HIV-1)-specific CD4(+) T cell response was investigated in 33 untreated HIV-1-infected individuals, using highly sensitive ELISPOT assays and intracellular flow cytometry. The median frequencies of interferon (IFN)-gamma-producing HIV-1 gag-specific CD4(+) T cells did not correlate significantly with control of viral replication or progression. HIV-1 gag-specific interleukin (IL)-4-producing cells were rarely detected. Circulating frequencies of CD4(+) T cells constitutively producing IL-10, however, were significantly higher in individuals with progression or active replication. In 17 of 30 HIV-1-infected individuals, gag antigen was observed to induce IL-10 production from CD4(+) T cells. In 2 individuals, early treatment of acute HIV-1 infection "rescued" low to undetectable gag-specific IFN-gamma-producing CD4(+) T cell responses and dramatically down-regulated constitutive IL-10 production from circulating CD4(+) T cells. The detection of HIV-1-specific IL-10-inducing CD4(+) T cells in HIV-1-infected individuals suggests that HIV-1 may directly subvert specific immune responses by IL-10 induction.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".