Spontaneous Pregnancy Loss Mediated by Abnormal Maternal Inflammation in Rats Is Linked to Deficient Uteroplacental Perfusion
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abnormal maternal inflammation during pregnancy is associated with spontaneous pregnancy loss and intrauterine fetal growth restriction. However, the mechanisms responsible for these pregnancy outcomes are not well understood. In this study, we used a rat model to demonstrate that pregnancy loss resulting from aberrant maternal inflammation is closely linked to deficient placental perfusion. Administration of LPS to pregnant Wistar rats on gestational day 14.5, to induce maternal inflammation, caused fetal loss in a dose-dependent manner 3-4 h later, and surviving fetuses were significantly growth restricted. Pregnancy loss was associated with coagulopathy, structural abnormalities in the uteroplacental vasculature, decreased placental blood flow, and placental and fetal hypoxia within 3 h of LPS administration. This impairment in uteroplacental hemodynamics in LPS-treated rats was linked to increased uterine artery resistance and reduced spiral arteriole flow velocity. Pregnancy loss induced by LPS was prevented by maternal administration of the immunoregulatory cytokine IL-10 or by blocking TNF-α activity after treatment with etanercept (Enbrel). These results indicate that alterations in placental perfusion are responsible for fetal morbidities associated with aberrant maternal inflammation and support a rationale for investigating a potential use of immunomodulatory agents in the prevention of spontaneous pregnancy loss.
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.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it