Microclusters of inhibitory killer immunoglobulin–like receptor signaling at natural killer cell immunological synapses
Bibliographic record
Abstract
We report the supramolecular organization of killer Ig-like receptor (KIR) phosphorylation using a technique applicable to imaging phosphorylation of any green fluorescent protein-tagged receptor at an intercellular contact or immune synapse. Specifically, we use fluorescence lifetime imaging (FLIM) to report Förster resonance energy transfer (FRET) between GFP-tagged KIR2DL1 and a Cy3-tagged generic anti-phosphotyrosine monoclonal antibody. Visualization of KIR phosphorylation in natural killer (NK) cells contacting target cells expressing cognate major histocompatibility complex class I proteins revealed that inhibitory signaling is spatially restricted to the immune synapse. This explains how NK cells respond appropriately when simultaneously surveying susceptible and resistant target cells. More surprising, phosphorylated KIR was confined to microclusters within the aggregate of KIR, contrary to an expected homogeneous distribution of KIR signaling across the immune synapse. Also, yellow fluorescent protein-tagged Lck, a kinase important for KIR phosphorylation, accumulated in a multifocal distribution at inhibitory synapses. Spatial confinement of receptor phosphorylation within the immune synapse may be critical to how activating and inhibitory signals are integrated in NK 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) | 0.001 | 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 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".