In vitro and in vivo models define a molecular signature reference for human embryonic notochordal cells
Bibliographic record
Abstract
Understanding the emergence of human notochordal cells (NC) is essential for the development of regenerative approaches. We present a comprehensive investigation into the specification and generation of bona fide NC using a straightforward pluripotent stem cell (PSC)-based system benchmarked with human fetal notochord. By integrating in vitro and in vivo transcriptomic data at single-cell resolution, we establish an extended molecular signature and overcome the limitations associated with studying human notochordal lineage at early developmental stages. We show that TGF-β inhibition enhances the yield and homogeneity of notochordal lineage commitment in vitro . Furthermore, this study characterizes regulators of cell-fate decision and matrisome enriched in the notochordal niche. Importantly, we identify specific cell-surface markers opening avenues for differentiation refinement, NC purification, and functional studies. Altogether, this study provides a human notochord transcriptomic reference that will serve as a resource for notochord identification in human systems, diseased-tissues modeling, and facilitating future biomedical research.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".