<scp>CEACAM</scp>1 on activated <scp>NK</scp> cells inhibits <scp>NKG</scp>2<scp>D</scp>‐mediated cytolytic function and signaling
Bibliographic record
Abstract
Carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is expressed on activated natural killer (NK) cells wherein it inhibits lysis of CEACAM1-bearing tumor cell lines. The mechanism for this is unknown. Here, we show that interleukin-2-induced expression of CEACAM1 on both mouse and primary human NK cells impairs the ability of NK gene complex group 2 member D (NKG2D) to stimulate cytolysis of CEACAM1-bearing cells. This process requires the expression of CEACAM1 on the NK cells and on the tumor cells, which is consistent with the involvement of trans-homophilic interactions between CEACAM1. Mechanistically, co-engagement of NKG2D and CEACAM1 results in a biochemical association between these two surface receptors and the recruitment of Src homology phosphatase 1 by CEACAM1 that leads to dephosphorylation of the guanine nucleotide exchange factor Vav1 and blockade of downstream signaling that is associated with the initiation of cytolysis. Thus, CEACAM1 on activated NK cells functions as an inhibitory receptor for NKG2D-mediated cytolysis, which has important implications for understanding the means by which CEACAM1 expression adversely affects tumor immunity.
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 | 0.001 |
| 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".