Abstract 477: Human Ang-(1-12) and Hemodynamic and Cardiac biometrics in Rats Overexpressing Human Angiotensinogen
Bibliographic record
Abstract
It has been reported that insertion of the human angiotensinogen (AGT) gene in rats does not cause hypertension as rat renin has no hydrolytic activity on human AGT. Initial studies in transgenic rats expressing the human AGT gene [TGR(hAGT)L1623] demonstrated the presence of human angiotensin-(1-12) [Ang-(1-12)] immunoreactivity in the heart of these rats. The exciting possibility that [TGR(hAGT)L1623] rats have increased precursor availability for Ang II formation from both human and rat origin stimulated further investigation of this model through measurements of arterial pressure and heart rate with implanted telemetry probes (Data Science International, MN), assessment of cardiac structure and function by echocardiography (VevoLAZR; VisualSonics Inc., Canada), and heart weight (n=9). Comparative studies were done in Sprague Dawley rats (SD; n=11). 24 h mean arterial pressures (Figure), but not heart rates, were significantly higher in [TGR(hAGT)L1623] rats compared to SD controls during 4 weeks of continuous measurement (starting at 13 weeks of age). Although there was no difference in systolic or diastolic function between these two strains, [TGR(hAGT)L1623] rats showed increased thickness of left ventricular posterior wall (2.3 ± 0.1 vs. 2.1 ± 0.1 mm; p<0.05) and diameter (8.1 ± 0.2 vs. 7.5 ± 0.1 mm; p<0.05) that was associated with increased heart weight (1.51 ± 0.03 vs 1.16 ± 0.01 g; p<0.001) and heart weight/tibia length ratio (34.6 ± 0.7 vs 28.6 ± 0.4 mg/mm; p<0.001). Detection of hypertension and cardiac Ang-(1-12) in rats with overexpression of the human AGT gene suggests a non-renin dependent enzymatic mechanism able to cleave Ang-(1-12) from the human substrate.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".