Bibliographic record
Abstract
About 35 million people worldwide were living with HIV-1 at the end of 2013 and over 25 million have already died of AIDS. AIDS patients show high variability in the speed of disease progression in the absence of treatment. While certain immunological traits have been shown to correlate with accelerated or slowed progression in some subjects, including slow progressors, factors controlling HIV-1 replication and disease kinetics remain largely enigmatic. The importance of T lymphocytes and of protective HLA-alleles is undeniable, but not sufficient to explain every attenuated phenotype. A thorough understanding of HIV-1 infection control in these patient subsets may help the development of novel strategies for treatment and prevention. Restriction factors are type I interferon-induced specialized cellular proteins that block viruses at different steps of their life cycle. TRIM5α, Mx2/MxB, TRIM22/Staf50, SAMHD1, p21/CDKN1, tetherin/BST2/CD137, APOBEC3G and APOBEC3F have all been proposed to inhibit HIV-1, often with gene variant- or cellular context-specificity. Recent evidence highlights their possible implication in AIDS disease progression. In this review, we depict their restrictive activity against HIV-1 and recapitulate the latest data on their potential role in vivo, in both normal and slow progressors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".