Abstract 10257: Nuclear Angiotensin-II Receptor Gene Expression in Cardiac Fibroblasts: Receptor Subtype-Specific Differential Role of IP-3-Receptor (IP3R) Related and Nitric Oxide Signaling
Bibliographic record
Abstract
Introduction: Angiotensin-II (Ang-II) is a crucial regulator of cardiac fibroblast (FB) structure and function. This study assessed whether activation of nuclear delimited AT1 (AT1R) and AT2 (AT2R) receptors in cardiac fibroblasts activates signalling events that influence gene expression. Methods: Canine atrial (Atr) and ventricular (Vt) FBs were isolated and intracellular localization of AT1R and AT2R assessed by immunofluorescence and Western blot. Intact nuclei were purified by differential centrifugation. Nitric oxide (NO) was detected with the fluorescent dye DAF-2. De novo RNA production was measured by transcription initiation assay ([α 32 P]UTP). Results: AT1R and AT2R proteins localized to nuclear membrane (immunohisto and immunoblot) and colocalized with nuclear markers TOPRO 3 and Histone 3. Purified nuclei contained high concentrations of DNA (Atr nuclei 2206±108* μ g/ml DNA vs cytosol 97±13; Vt nuclei 874±20* μ g/ml DNA vs cytosol 84±8, *P + cpm/ng DNA and 148±8 + cpm/ng DNA vs 69±9 cpm/ng DNA control; Vt: 260±21 + cpm/ng DNA and 240±6 + cpm/ng DNA vs 49±5 cpm/ng DNA control, n=5/group, + P + (Atr) and 48% + (Vt) by the IP3R-blocker 2APB (but not L-NAME) and AT2R-mediated responses were reduced by 79% + (Atr) and 29% + (Vt) by L-NAME. Atr nuclei pretreated with both 2APB and L-NAME prior to Ang-II had 91%* reductions in [α 32 P]UTP incorporation, similar to pretreatment with the RNA polymerase II inhibitor α-amanitin. Conclusions: Ang-II regulates gene expression in cardiac FBs through activation of nuclear AT1 and AT2 receptors, with IP3R activation and NO generation being respective effectors. FB nuclear ATR-signaling may regulate FB phenotype and play an important role in cardiac fibrosis and remodeling.
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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) | 0.000 | 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) | 0.006 | 0.001 |
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".