PEST family phosphatases in immunity, autoimmunity, and autoinflammatory disorders
Bibliographic record
Abstract
The proline-, glutamic acid-, serine- and threonine-rich (PEST) family of protein tyrosine phosphatases (PTPs) includes proline-enriched phosphatase (PEP)/lymphoid tyrosine phosphatase (LYP), PTP-PEST, and PTP-hematopoietic stem cell fraction (HSCF). PEP/LYP is a potent inhibitor of T-cell activation, principally by suppressing the activity of Src family protein tyrosine kinases (PTKs). This function seems to be dependent, at least in part, on the ability of PEP to bind C-terminal Src kinase (Csk), a PTK also involved in inactivating Src kinases. Interestingly, a polymorphism of LYP in humans (R620W) is a significant risk factor for autoimmune diseases including type 1 diabetes, rheumatoid arthritis, and lupus. The R620W mutation may be a 'gain-of-function' mutation. In non-hematopoietic cells, PTP-PEST is a critical regulator of adhesion and migration. This effect correlates with the aptitude of PTP-PEST to dephosphorylate cytoskeletal proteins such as Cas, focal adhesion associated-kinase (FAK), Pyk2, and PSTPIP. While not established, a similar function may also exist in immune cells. Additionally, overexpression studies provided an indication that PTP-PEST may be a negative regulator of lymphocyte activation. Interestingly, mutations in a PTP-PEST- and PTP-HSCF-interacting protein, PSTPIP1, were identified in humans with pyogenic sterile arthritis, pyoderma gangrenosum, and acne (PAPA) syndrome and familial recurrent arthritis, two autoinflammatory diseases. These mutations abrogate the ability of PSTPIP1 to bind PTP-PEST and PTP-HSCF, suggesting that these two PTPs may be negative regulators of inflammation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".