CD56/NCAM mediates cell migration of human NK cells by promoting integrin-mediated adhesion turnover
Bibliographic record
Abstract
Natural killer (NK) cells patrol tissue to mediate lysis of virally infected and tumorigenic cells. Human NK cells are typically identified by their expression of neural cell adhesion molecule (NCAM, CD56), yet, despite its ubiquitous expression on NK cells, CD56 remains a poorly understand protein on immune cells. CD56 has been previously demonstrated to play roles in NK cell cytotoxic function and cell migration. Specifically, CD56-deficient NK cells have impaired cell migration on stromal cells and CD56 is localized to the uropod of NK cells migrating on stroma. Here, we show that CD56 is required for NK cell migration on ICAM-1 and is required for the establishment of persistent cell polarity and unidirectional actin flow. The intracellular domain of CD56 (NCAM-140) is required for its function, and the loss of CD56 leads to enlarged actin foci and sequestration of phosphorylated Pyk2, accompanied by increased size and frequency of activated LFA-1 clusters. Together, these data identify a role for CD56 in regulating human NK cell migration through modulation of actin dynamics and integrin turnover.
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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".