Human Leukocyte Antigen (HLA) Class I Down-Regulation by Human Immunodeficiency Virus Type 1 Negative Factor (HIV-1 Nef): What Might We Learn From Natural Sequence Variants?
Bibliographic record
Abstract
HIV-1 causes a chronic infection in humans that is characterized by high plasma viremia, progressive loss of CD4+ T lymphocytes, and severe immunodeficiency resulting in opportunistic disease and AIDS. Viral persistence is mediated in part by the ability of the Nef protein to down-regulate HLA molecules on the infected cell surface, thereby allowing HIV-1 to evade recognition by antiviral CD8+ T lymphocytes. Extensive research has been conducted on Nef to determine protein domains that are required for its immune evasion activities and to identify critical cellular co-factors, and our mechanistic understanding of this process is becoming more complete. This review highlights our current knowledge of Nef-mediated HLA class I down-regulation and places this work in the context of naturally occurring sequence variation in this protein. We argue that efforts to fully understand the critical role of Nef for HIV-1 pathogenesis will require greater analysis of patient-derived sequences to elucidate subtle differences in immune evasion activity that may alter clinical outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.015 |
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; both teacher heads agree on what is shown here.
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".