Distinct intracellular Ca2+ dynamics regulate apical constriction and differentially contribute to neural tube closure
Bibliographic record
Abstract
Early in the development of the central nervous system, progenitor cells undergo a shape change, called apical constriction, that triggers the neural plate to form a tubular structure. How apical constriction in the neural plate is controlled and how it contributes to tissue morphogenesis are not fully understood. In this study, we show that intracellular calcium ions (Ca2+) are required for Xenopus neural tube formation and that there are two types of Ca2+-concentration changes, a single-cell and a multicellular wave-like fluctuation, in the developing neural plate. Quantitative imaging analyses revealed that transient increases in Ca2+ concentration induced cortical F-actin remodeling, apical constriction and accelerations of the closing movement of the neural plate. We also show that extracellular ATP and N-cadherin (cdh2) participate in the Ca2+-induced apical constriction. Furthermore, our mathematical model suggests that the effect of Ca2+ fluctuations on tissue morphogenesis is independent of fluctuation frequency and that fluctuations affecting individual cells are more efficient than those at the multicellular level. We propose that distinct Ca2+ signaling patterns differentially modulate apical constriction for efficient epithelial folding and that this mechanism has a broad range of physiological outcomes.
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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 | 0.001 | 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 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".