Cyclic Nucleotide Phosphodiesterases: important signaling modulators and therapeutic targets
Bibliographic record
Abstract
By catalyzing hydrolysis of cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP), cyclic nucleotide phosphodiesterases are critical regulators of their intracellular concentrations and their biological effects. As these intracellular second messengers control many cellular homeostatic processes, dysregulation of their signals and signaling pathways initiate or modulate pathophysiological pathways related to various disease states, including erectile dysfunction, pulmonary hypertension, acute refractory cardiac failure, intermittent claudication, chronic obstructive pulmonary disease, and psoriasis. Alterations in expression of PDEs and PDE-gene mutations (especially mutations in PDE6, PDE8B, PDE11A, and PDE4) have been implicated in various diseases and cancer pathologies. PDEs also play important role in formation and function of multimolecular signaling/regulatory complexes, called signalosomes. At specific intracellular locations, individual PDEs, together with pathway-specific signaling molecules, regulators, and effectors, are incorporated into specific signalosomes, where they facilitate and regulate compartmentalization of cyclic nucleotide signaling pathways and specific cellular functions. Currently, only a limited number of PDE inhibitors (PDE3, PDE4, PDE5 inhibitors) are used in clinical practice. Future paths to novel drug discovery include the crystal structure-based design approach, which has resulted in generation of more effective family-selective inhibitors, as well as burgeoning development of strategies to alter compartmentalized cyclic nucleotide signaling pathways by selectively targeting individual PDEs and their signalosome partners.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".