Compartmentation and compartment-specific regulation of PDE5 by protein kinase G allows selective cGMP-mediated regulation of platelet functions
Bibliographic record
Abstract
It is generally accepted that nitric oxide (NO) donors, such as sodium nitroprusside (SNP), or phosphodiesterase 5 (PDE5) inhibitors, including sildenafil, each impact human platelet function. Although a strong correlation exists between the actions of NO donors in platelets and their impact on cGMP, agents such as sildenafil act without increasing global intra-platelet cGMP levels. This study was undertaken to identify how PDE5 inhibitors might act without increasing cGMP. Our data identify PDE5 as an integral component of a protein kinase G1beta (PKG1beta)-containing signaling complex, reported previously to coordinate cGMP-mediated inhibition of inositol-1, 4, 5-trisphosphate receptor type 1 (IP(3)R1)-mediated Ca(2+)-release. PKG1beta and PDE5 did not interact in subcellular fractions devoid of IP(3)R1 and were not recruited to IP(3)R1-enriched membranes in response to cGMP-elevating agents. Activation of platelet PKG promoted phosphorylation and activation of the PDE5 fraction tethered to the IP(3)R1-PKG complex, an effect not observed for the nontethered PDE5. Based on these findings, we elaborate a model in which PKG selectively activates PDE5 within a defined microdomain in platelets and propose that this mechanism allows spatial and temporal regulation of cGMP signaling in these cells. Recent reports indicate that sildenafil might prove useful in limiting in-stent thrombosis and the thrombotic events associated with the acute coronary syndromes (ACS), situations poorly regulated with currently available therapeutics. We submit that our findings may define a molecular mechanism by which PDE5 inhibition can differentially impact selected cellular functions of platelets, and perhaps of other cell types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
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".