Interaction of <scp>TAPP</scp> adapter proteins with phosphatidylinositol (3,4)‐bisphosphate regulates <scp>B</scp>‐cell activation and autoantibody production
Bibliographic record
Abstract
TAPP1 and TAPP2 (where TAPP is tandem PH domain containing protein) are dual PH domain adaptors that selectively bind PI(3,4)P2 (phosphatidylinositol (3,4)-bisphosphate). PI(3,4)P2 is a lipid messenger generated by phosphoinositide 3-kinase (PI3K) and SHIP, both of which are critical regulators of B-cell activation. To determine the functional role of TAPP-PI(3,4)P2 interactions, we utilized a double knock-in (KI) mouse bearing mutations within the PI-binding pocket of both TAPP1 and TAPP2. TAPP KI mice show evidence of altered B-cell development, but generate phenotypically normal mature B-cell populations. Total serum immunoglobulin IgM and IgG levels were found to be markedly elevated in TAPP KI mice. B cells purified from TAPP KI mice were hyper-responsive to antigen receptor cross-linking, showing increased proliferation, CD86 expression, and Akt phosphorylation on Ser473 and Thr308. Female TAPP KI mice developed elevated levels of anti-DNA and antinuclear antibodies with age, associated with IgG deposition in kidneys and significant glomerulonephritis pathology. Together our results indicate that interaction of TAPPs with PI(3,4)P2 mediates feedback inhibition impacting on BCR signaling, with functional significance for control of autoreactive B 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".