Phenotypical and functional profiles of natural killer cells exhibiting matrix metalloproteinase-mediated CD16 cleavage after anti-HIV antibody-dependent activation
Bibliographic record
Abstract
Natural killer (NK) cell-mediated antibody-dependent cellular cytotoxicity (ADCC) has been linked to protection from HIV infection and slower progression towards AIDS. However, antibody-dependent activation of NK cells results in phenotypical alterations similar to those observed on NK cells from individuals with progressive HIV infection. Activation of NK cells induces matrix metalloproteinase (MMP)-mediated cleavage of cell surface CD16. In the present study we assessed the phenotype and functional profile of NK cells exhibiting post-activation MMP-mediated CD16 cleavage. We found that NK cells achieving the highest levels of activation during stimulation exhibit the most profound decreases in CD16 expression. Further, we observed that educated KIR3DL1(+) NK cells from human leucocyte antigen (HLA)-Bw4-carrying donors exhibit larger decreases in CD16 expression post-activation than the KIR3DL1(-) NK cell subset containing cells educated via other inhibitory receptor/ligand combinations and non-educated NK cells. Lastly, we assessed the ex-vivo expression of CD16 on educated KIR3DL1(+) NK cells and the KIR3DL1(-) NK cell subset from HLA-Bw4-carrying HIV-uninfected and HIV-infected donors. Suggestive of in-vivo activation of KIR3DL1(+) NK cells during HIV infection, CD16 expression was higher on KIR3DL1(+) than KIR3DL1(-) NK cells in uninfected donors but similar on both subsets in HIV-infected donors. These results are discussed in the context of how they may assist with understanding HIV disease progression and the design of immunotherapies that utilize antibody-dependent NK cell responses.
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".