Toll-like Receptor Polymorphism Associations With HIV-1 Outcomes Among Sub-Saharan Africans
Bibliographic record
Abstract
OBJECTIVE: We evaluated Toll-like receptors (TLRs) single nucleotide polymorphisms (SNPs) for associations with HIV-1 acquisition, set-point and disease progression in African couples. METHODS: Seven candidate and 116 haplotype-tagging SNPs (tagSNPs) were genotyped in 504 HIV-1 infected cases, and 343 seronegative controls. RESULTS: TLR9 1635A/G was associated with reduced HIV-1 acquisition among HIV-seronegative controls with high but not low HIV-1 exposure (odds ratio [OR] = 0.7; P = .03 and OR = 0.9, P = .5, respectively). TLR7 rs179012 and TLR2 597C/T reduced set-point; the latter modified by time since HIV-1 acquisition. TLR8 1A/G reduced disease progression. CONCLUSIONS: TLR SNPs impact HIV-1 outcomes with epidemiologic factors modifying these relationships.
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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 | 0.002 |
| 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) | 0.002 | 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".