HIV Protective <i>KIR3DL1</i> and <i>HLA-B</i> Genotypes Influence NK Cell Function Following Stimulation with HLA-Devoid Cells
Bibliographic record
Abstract
Epidemiological studies in humans have implicated carriage of combinations of genes encoding certain KIR3DL1 (killer Ig-like receptor 3DL1) alleles and their HLA-Bw4 ligands in slower progression to AIDS, lower viral load and protection from infection. Given that the KIR3DL1*h/*y/HLA-B*57 genetic combination is strongly associated with favorable HIV outcomes, we measured responses from NK cells isolated from these individuals by multiparametric flow cytometry for cytokine secretion and degranulation in response to stimulation with HLA-devoid cells to assess whether the KIR/HLA compound genotypes linked to better HIV outcome favor increased NK cell functional potential. Our results indicate that NK cells from these individuals had increased functional potential, particularly in the KIR3DL1(+) NK cell subset. These results support a link between KIR/HLA genotypes and NK cell function and could provide an explanation for the observation that some KIR/HLA combinations are associated protective phenotypes in the context of host-HIV interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".