Time to Seroconversion in HIV-Exposed Subjects Carrying Protective versus Non Protective KIR3DS1/L1 and HLA-B Genotypes
Bibliographic record
Abstract
Natural killer (NK) cells play a role in the clearance of viral infections. Combinations of alleles at the polymorphic HLA-B locus and the NK cell surface killer immunoglobulin-like receptor locus KIR3DL1/S1 have been shown to influence time to AIDS in HIV-infected individuals and risk of seroconversion in HIV exposed seronegative (HESN) subjects. Here, we assessed time to seroconversion or duration of seronegative status in a group of 168 HIV exposed individuals, including 74 seroconverters and 94 HESN based on carriage or not of KIR3DL1/S1/HLA-B genotypes previously shown to be associated with protection from infection and/or slow time to AIDS. KIR3DL1/S1 genotyping was performed by sequence-specific primer polymerase chain reaction using two pairs of specific primers for each locus. The MHC class IB locus was typed to four-position resolution to resolve Bw4 and Bw6 alleles and the amino acid present at position 80. KIR3DL1/S1 heterozygotes became HIV infected significantly faster than KIR3DS1 homozygotes. Individuals who carried both KIR3DS1 and Bw4*80I did not remain HIV seronegative longer than those from a control group who were homozygous for HLA-Bw6 and carried no HLA-A locus Bw4 alleles Subjects who were *h/*y+B*57 showed a trend towards slower time to serconversion than those with other KIR3DL1 homozygous and KIR3DL1/S1 heterozygous genotypes. Thus, KIR3DS1 homozygosity is associated with protection from HIV infection while co-carriage of KIR3DS1 and Bw4*80I is not. The requirements for protection from HIV infection can differ from those that influence time to AIDS in HIV infected individuals.
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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 | 0.001 |
| 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 | 0.000 | 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".