Modelling preeclampsia: a comparative analysis of the common human trophoblast cell lines
Bibliographic record
Abstract
ABSTRACT Preeclampsia remains a challenge without an effective therapy. Evidence supports targetability of soluble fms‐like tyrosine kinase‐1 (sFlt‐1) and soluble endoglin (sEng), which are released excessively from the placenta under ischemic and hypoxic stresses. We compared four trophoblast cell lines, BeWo, Jar, Jeg‐3, and HTR‐8/SVneo, in order to identify a suitable model for drug screening. Cultured trophoblasts were exposed to 1% oxygen vs. normoxia for 24‐48 hr; human umbilical vein and aortic endothelial cells were included for comparison. Supernatant sFlt‐1 and sEng concentrations were measured by ELISA, and sFlt‐1 mRNA expression determined by RT‐PCR. Cellular responses to experimental therapeutics were explored. All four trophoblast lines secreted sEng, which did not increase by hypoxia. BeWo, Jar, and Jeg‐3 exhibited significantly enhanced expression of sFlt‐1 i13 and e15a mRNA in response to hypoxia; however, only BeWo released a detectable level of sFlt‐1 protein, which was doubled by hypoxia. In contrast, hypoxia decreased sFlt‐1 mRNA expression and protein release in HTR‐8/SVneo, similarly to endothelial cells. The cellular mechanism involved HIFα. BeWo responded to representative agents similarly to human primary placental tissues in the literature. These data support that the BeWo‐hypoxia model mimics a key pathogenic mechanism of preeclampsia and has potential value for translational drug discovery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".