Faculty Opinions recommendation of TCR clonotypes modulate the protective effect of HLA class I molecules in HIV-1 infection.
Bibliographic record
Abstract
The human leukocyte antigens HLA-B27 and HLA-B57 are associated with protection against progression of disease that results from infection with human immunodeficiency virus type 1 (HIV-1), yet most people with alleles encoding HLA-B27 and HLA-B57 are unable to control HIV-1. Here we found that HLA-B27-restricted CD8(+) T cells in people able to control infection with HIV-1 (controllers) and those who progress to disease after infection with HIV-1 (progressors) differed in their ability to inhibit viral replication through targeting of the immunodominant epitope of group-associated antigen (Gag) of HIV-1. This was associated with distinct T cell antigen receptor (TCR) clonotypes, characterized by superior control of HIV-1 replication in vitro, greater cross-reactivity to epitope variants and enhanced loading and delivery of perforin. We also observed clonotype-specific differences in antiviral efficacy for an immunodominant HLA-B57-restricted response in controllers and progressors. Thus, the efficacy of such so-called 'protective alleles' is modulated by specific TCR clonotypes selected during natural infection, which provides a functional explanation for divergent HIV-1 outcomes. PMID: 22683743 Funding information This work was supported by: NIAID NIH HHS, United States Grant ID: R01 AI030914 NIAID NIH HHS, United States Grant ID: P30 AI060354 Howard Hughes Medical Institute, United States NIAID NIH HHS, United States Grant ID: AI074415 Canadian Institutes of Health Research, Canada Intramural NIH HHS, United States NIAID NIH HHS, United States Grant ID: AI030914 NIAID NIH HHS, United States Grant ID: 5 P30 AI060354-04 NIAID NIH HHS, United States Grant ID: R21 AI124769 NIAID NIH HHS, United States Grant ID: P01 AI074415 More Less keyboard_arrow_down
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.509 | 0.238 |
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".