Coronary Flow Reserve in Pregnant Rats with Increased Left Ventricular Afterload
Bibliographic record
Abstract
BACKGROUND: Coronary flow reserve (CFR) is used as a measure of coronary endothelial function. We investigated the effect of increased afterload on CFR of pregnant and non-pregnant rats. METHODS: Afterload increase in Wister rats (both pregnant and non-pregnant) was achieved by the infusion of angiotensin II (Ang II) for ∼10 days or by subjecting them to transverse aortic constriction (TAC) for ∼14 days. Control groups were infused with 0.9% NaCl or had sham surgery, respectively. In pregnant rats, the experiments were performed close to term gestation. Doppler velocity waveforms of the left main coronary artery were recorded using a high resolution ultrasound imaging system (Vevo 770, VisualSonics, Canada) at baseline while the animals were anesthetized with 1.5% inhaled isoflurane, and during maximal coronary dilatation obtained by the inhalation of 3.5% of isoflurane. CFR was calculated as the ratio between the peak coronary flow velocities (CFRpeak) and the velocity-time integrals (CFRVTI) recorded at hyperemia and at baseline. RESULTS: CFR could be calculated in 60 of 75 (80%) animals. There were no differences in CFR between intervention and control groups irrespective of whether afterload was increased by Ang II or TAC. In the TAC-study CFRpeak (1.54±0.07 vs 1.85±0.17; p = 0.03) was decreased in pregnant compared to non-pregnant shams. When sham animals from both studies were pooled together both CFRpeak (1.42±0.07 vs 1.86±0.16; p = 0.005) as well as CFRVTI (1.45±0.07 vs 1.78±0.12; p = 0.03) were significantly lower in pregnant rats compared to non-pregnant. CONCLUSIONS: CFR can be measured non-invasively in rats using Doppler echocardiography and high concentrations of inhaled isoflurane as a coronary vasodilator. In pregnant rats, CFR is reduced close to term. CFR is not affected by increased left ventricular afterload caused by chronic Ang II infusion or TAC.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".