CIN85 Interacting Proteins in B Cells-Specific Role for SHIP-1
Bibliographic record
Abstract
The Cbl-interacting 85-kDa protein (CIN85) plays an important role as a negative regulator of signaling pathways induced by receptor tyrosine kinases. By assembling multiprotein complexes this versatile adaptor enhances receptor tyrosine kinase-activated clathrin-mediated endocytosis and reduces phosphatidylinositol-3-kinase-induced phosphatidylinositol-3,4,5-trisphosphate production. Here we report the expression of CIN85 in primary splenic B lymphocytes and the B-lymphoma cell lines WEHI 231 and Ba/F3. Cross-linking of the B cell antigen receptor resulted in an increased association of CIN85 with the ubiquitin ligase Cbl. Through a systematic pull-down proteomics approach we identified 51 proteins that interact with CIN85 in B cells, including proteins not shown previously to be CIN85-associated. Among these proteins, the SH2-containing inositol phosphatase 1 (SHIP-1) co-precipitated with both the full-length CIN85 and each of its three SH3 domains. We also showed that this association is constitutive and depends on a region of 79 amino acids near the carboxyl terminus of SHIP-1, a region rich in potential SH3 domain binding sites. Because SHIP-1 is a major negative regulator of the phosphatidylinositol-3-kinase pathway in lymphocytes, we hypothesize that the interaction between SHIP-1 and CIN85 might synergistically facilitate the down-regulation of phosphatidylinositol-3,4,5-trisphosphate levels.
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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".