Strategies for investigating the maternal-fetal interface in the first trimester of pregnancy: What can we learn about pathology?
Bibliographic record
Abstract
The pathologies of the pregnancy complications pre-eclampsia (PE) and fetal growth restriction (FGR) are established in the first trimester of human pregnancy. In a normal pregnancy, decidual spiral arteries are transformed into wide diameter, non-vasoactive vessels capable of meeting the increased demands of the developing fetus for nutrients and oxygen. Disruption of this transformation is associated with PE and FGR. Very little is known of how these first trimester changes are regulated normally and even less is known about how they are compromised in complicated pregnancies. Interactions between maternal and placental cells are essential for pregnancy to progress and this review will summarise the challenges in investigating this area. We will discuss how first trimester studies of pregnancies with an increased risk of developing PE/FGR have started to provide valuable information about pregnancy at this most dynamic and crucial time. We will discuss where there is scope to progress these studies further by refining the ability to identify compromised pregnancies at an early stage, by integrating information from many cell types from the same pregnancy, and by improving our methods for modelling the maternal-fetal interface in vitro.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".