Mice Overexpressing Both Human Angiotensinogen and Human Renin as a Model of Superimposed Preeclampsia on Chronic Hypertension
Bibliographic record
Abstract
Preeclampsia is the major cause of maternal and fetal mortality/morbidity. Because hypertension is an important risk factor for preeclampsia, we investigated whether hypertensive mice that overexpress human renin and angiotensinogen develop superimposed preeclampsia. Given that the mechanisms underlying this disease are still poorly understood, animal models are of great use for elucidation. Blood pressure and proteinuria were measured by telemetry and ELISA, respectively. Heart function was evaluated by echocardiography, whereas pathological cardiac hypertrophy-related genes were assessed by real-time PCR. Soluble fms-like tyrosine kinase 1 plasma concentrations were quantitated by ELISA and placental expression by real-time PCR. Transgenic mice develop de novo proteinuria during gestation and marked blood pressure elevation, which are hallmarks of superimposed preeclampsia on chronic hypertension. Abnormal placentation present in these mothers produced a significant decrease in pup and placental weight and was associated with an increased placental expression of soluble fms-like tyrosine kinase 1. We also found heightened circulating levels of this receptor, when adjusted for placental mass, as has been observed in women who suffer from preeclampsia. Cardiac hypertrophy could be observed in the transgenic mice and was exacerbated by gestation. As a result, heart function was significantly decreased, and markers of pathological hypertrophy were increased. Our data, thus, confirm the characterization of a new model of superimposed preeclampsia on chronic hypertension. Because chronically hypertensive women are at risk of developing the pathology, our model reflects a clinical reality and is, thus, an excellent tool to elucidate the molecular mechanisms triggering this disease.
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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".