Abstract 19535: Constitutive Expression of a Dominant Negative TGF-β Type-II Receptor in the Posterior Left Atrium Attenuates NADPH Oxidase and Mitochondrial Superoxide Production and Decreases Atrial Fibrosis (Resulting in Decreased AF)
Bibliographic record
Abstract
Background: Oxidative stress is an important mechanism in the creation of AF substrate, especially in the setting of heart failure (HF). This is in part through reactive oxygen species (ROS) leading to activation of TGF-β signaling, which results in creation of atrial fibrosis. ROS are also an important downstream mediator of TGF-β signaling. We therefore hypothesized that in a canine model of HF induced by ventricular tachypacing, decreasing TGF-β signaling via atria-targeted dominant-negative type II TGF-β receptor expression will attenuate both oxidative stress and atrial fibrosis, thereby leading to decreased AF. Methods: 17 dogs underwent injection + electroporation in the posterior left atrium (PLA) of either a plasmid expressing a dominant negative TGF-β type II receptor (pUBC-TGFβdnRII) (N=8) or control vector (p-UBC- LacZ ) (N=7), followed by 3-4 weeks of right ventricular tachypacing (240 bpm). A terminal study was performed to assess for AF inducibility. Tissue was assayed for changes in fibrosis (Trichrome staining) and oxidative stress (superoxide quantification via lucigenin chemiluminescence). Results: Downregulation of TGF-β signaling by TGFβdnRII significantly decreased fibrosis ( Figure 1a , blue staining), attenuated NADPH- and mitochondrial-generated superoxide ( Figure 1b ) and significantly decreased AF duration ( Figure 1c ), as compared to control animals. Conclusions: Targeted non-viral gene-therapy approaches aimed at reducing TGF-β signaling in the left atrium results in a decrease in AF substrate, in part through the reduction of oxidative stress and the development of fibrosis. Further optimization of this gene therapy approach may translate into effective AF therapies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".