Dynamic auxin transport patterns preceding vein formation revealed by live-imaging of Arabidopsis leaf primordia
Bibliographic record
Abstract
Self-regulatory patterning mechanisms capable of generating biologically meaningful, yet unpredictable cellular patterns offer unique opportunities for obtaining mathematical descriptions of underlying patterning systems properties. The networks of higher-order veins in leaf primordia constitute such a self-regulatory system. During the formation of higher-order veins, vascular precursors are selected from a homogenous field of subepidermal cells in unpredictable positions to eventually connect in complex cellular networks. Auxin transport routes have been implicated in this selection process, but understanding of their role in vascular patterning has been limited by our inability to monitor early auxin transport dynamics in vivo. Here we describe a live-imaging system in emerging Arabidopsis thaliana leaves that uses a PIN1:GFP reporter to visualize auxin transport routes and an Athb8:YFP reporter as a marker for vascular commitment. Live-imaging revealed common features initiating the formation of all higher-order veins. The formation of broad PIN1 expression domains is followed by their restriction, leading to sustained, elevated PIN1 expression in incipient procambial cells files, which then express Athb8. Higher-order PIN1 expression domains (hPEDs) are initiated as freely ending domains that extend toward each other and sometimes fuse with them, creating connected domains. During the restriction and specification phase, cells in wider hPEDs are partitioned into vascular and non-vascular fates: Central cells acquire a coordinated cell axis and express elevated PIN1 levels as well as the pre-procambial marker Athb8, while edge cells downregulate PIN1 and remain isodiametric. The dynamic nature of the early selection process is underscored by the instability of early hPEDs, which can result in dramatic changes in vascular network architecture prior to Athb8 expression, which is correlated with the promotion onto vascular cell fate.
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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".