Leishmania surface protein gp63 binds directly to human natural killer cells and inhibits proliferation
Bibliographic record
Abstract
Natural killer (NK) cells contribute to immunity as the first line of defence in numerous infections by early cytokine secretion and cytotoxicity. In Leishmania infection, NK cells contribute with interferon-gamma and may assist in directing the immune response towards T helper type 1, which is essential for successful control of the parasites. Thus, NK cells may play an important role in both resistance and control of the infection. However, during Leishmania infection NK cells show signs of suppression. To explore the reason for this suppression, we exposed naive and interleukin (IL)-2 activated NK cells directly to promastigotes of Leishmania major in vitro. As a rapid consequence of contact between naive NK cells and promastigotes, expression of NK cell receptors show significant changes. We identify one of the major surface molecules of promastigotes, glycoprotein (gp) 63, as an important agent for these suppressive effects by using promastigotes of a gp63ko strain of L. major. Furthermore, proliferation of IL-2-activated purified NK cells is suppressed after exposure to the wild-type but not to gp63ko promastigotes. However, gp63ko L. major induced no NK cell proliferation when NK cells were co-cultured with peripheral blood mononuclear cells populations such as CD14(+) monocytes or T cells.
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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) | 0.000 | 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 | 0.001 |
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".