The Actin Cytoskeleton Controls the Efficiency of Killer Ig-Like Receptor Accumulation at Inhibitory NK Cell Immune Synapses
Bibliographic record
Abstract
Killer cell Ig-like receptors (KIRs) are MHC class I-specific receptors expressed in NK and T lymphocytes. KIR antagonism of activation signals occurs at the immune synapse between the effector and target cells. The processes that regulate clustering of KIR are not well defined. We have expressed KIR-GFP receptor chimeras in two human NK-like lines, YTS and NK92. In this study, we show that the frequency of KIR enrichment at the synapse was decreased for a KIR that lacks a portion of the cytoplasmic tail. Strikingly, blocking actin polymerization with a high dose of cytochalasin D also substantially decreased clustering of KIR as well as KIR-induced clustering of HLA-C-GFP in target cells. However, the effect of inhibiting actin polymerization was only clearly evident at the earlier time points after cell mixing, and eventually clustering of KIR and HLA-C occurred independently of actin remodeling. Although treatment with anti-LFA-1 also decreased conjugate formation, the frequency of KIR clustering remained normal within the population of conjugates that did form, suggesting that the effect of cytochalasin D is not solely through LFA-1. Collectively, these data suggest that the actin cytoskeleton and the cytoplasmic tail of KIR regulate the efficiency by which KIR accumulates at inhibitory NK cell synapses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".