Disruption of Protein Kinase A Localization Using a Trans-activator of Transcription (TAT)-conjugated A-kinase-anchoring Peptide Reduces Cardiac Function
Bibliographic record
Abstract
Localization of protein kinase A (PKA) via A-kinase-anchoring proteins (AKAPs) is important for cAMP responsiveness in many cellular systems, and evidence suggests that AKAPs play an important role in cardiac signaling. To test the importance of AKAP-mediated targeting of PKA on cardiac function, we designed a cell-permeable peptide, which we termed trans-activator of transcription (TAT)-AKAD for TAT-conjugated A-kinase-anchoring disruptor, using the PKA binding region of AKAP10 and tested the effects of this peptide in isolated cardiac myocytes and in Langendorff-perfused mouse hearts. We initially validated TAT-AKAD as a PKA localization inhibitor in cardiac myocytes by the use of confocal microscopy and cellular fractionation to show that treatment with the peptide disrupts type I and type II PKA regulatory subunits. Knockdown of PKA activity was demonstrated by decrease in phosphorylation of phospholamban and troponin I after beta-adrenergic stimulation in isolated myocytes. Treatment with TAT-AKAD reduced myocyte shortening and rates of contraction and relaxation. Injection of TAT-AKAD (1 microM), but not scrambled control peptide, into the coronary circulation of isolated perfused hearts rapidly (<1 min) and reversibly decreased heart rate and peak left ventricular developed pressure. TAT-AKAD also had a pronounced effect on developed pressure (-dP/dt), consistent with a delayed relaxation of the heart. The effects of TAT-AKAD on heart rate and contractility persisted in hearts pretreated with isoproterenol. Disruption of PKA localization with TAT-AKAD thus had negative effects on chronotropy, inotropy, and lusitropy, thereby indicating a key role for AKAP-targeted PKA in control of heart rate and contractile function.
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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) | 0.000 | 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 | 0.000 |
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".