Connexin 31 (GJB3) Deficiency in Mouse Trophoblast Stem Cells Alters Giant Cell Differentiation and Leads to Loss of Oxygen Sensing1
Bibliographic record
Abstract
The nonphysiological placental oxidative environment has been implicated in many complications during human pregnancy. Oxygen tension can influence a broad spectrum of molecular changes leading to alterations in trophoblast cell lineage development. In this study, we report that mouse wild-type trophoblast stem cells (TSCs) react to low oxygen (3%) with an enhanced differentiation into the giant cell pathway, indicated by a downregulation of the early stem cell markers Eomes and Cdx2 as well as by a significant upregulation of Tfap2c and the differentiation markers Tpbpa and Prl3d1. Here we demonstrated that connexin 31/GJB3-deficient TSCs failed to stabilize HIF-1A under low oxygen, resulting in nonresponsiveness of different marker genes, such as Cdx2 and Eomes and Tfap2c and Tpbpa. Moreover, connexin 31-deficient TSCs revealed a shift in giant cell differentiation from Prl3d1 expressing parietal giant cells to Ctsq, Prl3b1, and Prl2c2-positive giant cells, probably sinusoidal and canal lining trophoblast giant cells. Thus, loss of connexin 31 led to different giant cell subtypes which bypass the progenitor regulators Tfap2c and Tpbpa under low oxygen conditions.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".