Time‐lapse imaging of Arabidopsis leaf development shows dynamic patterns of procambium formation
Bibliographic record
Abstract
The principles underlying the formation of leaf veins have long intrigued developmental biologists. In leaves, networks of vascular precursor procambial cells emerge from seemingly homogeneous subepidermal tissue through the selection of anatomically inconspicuous preprocambial cells. Understanding dynamics of procambium formation has been hampered by the difficulty of observing the process in vivo. Here we present a live-imaging technique that allows visual access to complex events occurring in developing leaves. We combined this method with stage-specific fluorescent markers in Arabidopsis (Arabidopsis thaliana) to visualize preprocambial strand formation and procambium differentiation during the undisturbed course of development and upon defined perturbations of vein ontogeny. Under all experimental conditions, we observed extension, termination and fusion of preprocambial strands and simultaneous initiation of procambium differentiation along entire individual veins. Our findings strongly suggest that progressiveness of preprocambial strand formation and simultaneity of procambium differentiation represent inherent properties of the mechanism underlying vein formation.
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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".