Regulation of tyrosine phosphorylation cascades by phosphatases: What the actions of vanadium teach us
Bibliographic record
Abstract
Abstract Protein phosphorylation and dephosphorylation regulate much of the machinery of the cell. Emphasis in recent years has swung toward regulation by dephosphorylation. Much current research focuses on protein tyrosine phosphatases. Researchers of cellular regulation use vanadium as a probe because of its unparalleled ability to selectively inhibit protein tyrosine phosphatases at submicromolar concentrations. This review focuses on the biological actions of vanadium relevant to cellular regulatory cascades. Recent research has led to identification of control points and possible drug targets in 1) the glucose control mechanisms downstream from insulin receptors; 2) pathways regulating mitogenesis, tumor promotion, and other events downstream from growth factor receptors; 3) regulation of osteogenesis and possibilities for counteracting the bone damaging actions of glucocorticoids. An up‐to‐date understanding of the mechanisms by which vanadium acts and of its currently identified targets is prerequisite to the intelligent design of experiments of this kind. In this review, we will consider mechanisms at the enzymological level, in cellular regulatory cascades, and events affecting the cell or organism as a whole. J. Trace Elem. Exp. Med. 16:281–290, 2003. © 2003 Wiley‐Liss, Inc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".