Bibliographic record
Abstract
Questions in developmental biology are most frequently addressed by using fluorescent markers of otherwise invisible cell states. In plants, such questions can be addressed most conveniently in leaves. Indeed, from the formation of stomata and trichomes within the leaf epidermis to that of vein networks deep into the leaf inner tissue, leaf cells and tissues differentiate anew during the development of each leaf. Moreover, leaves are produced in abundance and are easily accessible to visualization and perturbation. Yet a detailed procedure for the perturbation, dissection, mounting, and imaging of developing leaves has not been described. Here we address this limitation (1) by providing robust, step-by-step protocols for the local application of the plant hormone auxin to developing leaves and for the routine dissection and mounting of leaves and leaf primordia, and (2) by offering practical guidelines for the optimization of imaging parameters for confocal microscopy. We describe the procedure for the first leaves of Arabidopsis, but the same approach can be easily applied to other leaves of Arabidopsis or to leaves of other plants. © 2022 Wiley Periodicals LLC. Support Protocol 1: Preparation of plant growth medium Support Protocol 2: Preparation of growth medium plates Basic Protocol 1: Seed sterilization, sowing, and germination, and seedling growth Support Protocol 3: Preparation of IAA-lanolin paste Basic Protocol 2: Application of IAA-lanolin paste to 3.5-DAG first leaves Basic Protocol 3: Dissection of 3- to 6-DAG first leaves and leaf primordia Basic Protocol 4: Dissection of 1- and 2-DAG first-leaf primordia Basic Protocol 5: Mounting of dissected leaves and leaf primordia Support Protocol 4: Quality check of mounted leaves and leaf primordia by fluorescence microscopy Basic Protocol 6: Imaging of mounted leaves and leaf primordia by confocal microscopy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.011 |
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".