SHP-1 Phosphatase Is a Critical Regulator in Preventing Natural Killer Cell Self-Killing
Bibliographic record
Abstract
Balance of signals generated from the engaged activating and inhibitory surface receptors regulates mature NK cell activities. The inhibitory receptors signal through immunoreceptor tyrosine based inhibitory motifs (ITIM), and recruit phosphatases such as SHP-1 to inhibit NK cell activation. To directly examine the importance of SHP-1 in regulating activities and cell fate of mature NK cells, we used our established lentiviral-based engineering protocol to knock down the SHP-1 protein expression in primary C57BL/6NCrl cells. Gene silencing of the SHP-1 in primary NK cells abrogated the ability of ITIM-containing NK inhibitory receptors to suppress the activation signals induced by NK1.1 activating receptors. We followed the fates of stably transduced SHP-1 silenced primary NK cells over a longer period of time in IL-2 containing cultures. We observed an impaired IL-2 induced proliferation in the SHP-1 knockdown NK cells. More interestingly, these "de-regulated" SHP-1 knockdown NK cells mediated specific self-killing in a real-time live cell microscopic imaging system we developed to study NK cell cytotoxicity in vitro. Selective target recognition of the SHP-1 knockdown NK cells revealed also possible involvement of the SHP-1 phosphatase in regulating other NK functions in mature 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".