Modeling the Progression of Placental Transport from Early‐ to Late‐Stage Pregnancy by Tuning Trophoblast Differentiation and Vascularization
Bibliographic record
Abstract
The early-stage placental barrier is characterized by a lack of fetal circulation and by a thick trophoblastic barrier, whereas the later-stage placenta consists of vascularized chorionic villi encased in a thin, differentiated trophoblast layer, ideal for nutrient transport. In this work, predictive models of early- and late-stage placental transport are created using blastocyst-derived placental stem cells (PSCs) by modulating PSC differentiation and model vascularization. PSC differentiation results in a thinner, fused trophoblast layer, as well as an increase in human chorionic gonadotropin secretion, barrier permeability, and secretion of certain inflammatory cytokines, which are consistent with in vivo findings. Further, gene expression confirms this shift toward a differentiated trophoblast subtype. Vascularization results in a molecule type- and size-dependent change in dextran and insulin permeability. These results demonstrate that trophoblast differentiation and vascularization have critical effects on placental barrier permeability and that this model can be used as a predictive measure to assess fetal toxicity of xenobiotic substances at different stages of pregnancy.
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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 | 0.000 |
| 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".