Importance and mechanism of ‘switch’ function of SAP family adapters
Bibliographic record
Abstract
The signaling lymphocytic activation molecule (SLAM)-associated protein (SAP) family of adapters includes SAP, Ewing's sarcoma-associated transcript-2 (EAT-2), and EAT-2-related transducer (ERT). These Src homology-2 (SH2) domain-only molecules play critical roles in immune regulation. The prototype of the SAP family, SAP, is mutated in X-linked lymphoproliferative disease in humans. Moreover, genetically engineered mice lacking one or more SAP family members have defects in multiple immune cell types including T cells, natural killer (NK) cells, NKT cells, and B cells. Accumulating data show that SAP family adapters regulate immunity by influencing the functions of SLAM family receptors, through two distinct but cooperative mechanisms. First, SAP family adapters couple SLAM family receptors to active biochemical signals, which promote immune cell functions. Second, SAP family adapters interfere with the intrinsic ability of SLAM family receptors to trigger inhibitory signals, which could be mediated via molecules such as SH2 domain-containing 5'-inositol phosphatase-1. The latter effect of SAP family adapters does not seem to be because of direct blocking of inhibitory effector binding to SLAM family receptors. Rather, it appears to implicate alternative mechanisms such as functional competition, trans-regulation, or steric hindrance. In the absence of SAP family adapters, the inhibitory signals mediated by SLAM family receptors suppress critical activating receptors, explaining in part the pronounced phenotypes seen in SAP family adapter-deficient humans and mice. Thus, SAP family adapters are molecular switches that regulate immunity as a result of their capacity to control the type of signals and functions emanating from SLAM family receptors.
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".