Diversity and distribution of plant metallothioneins: a review of structure, properties and functions
Bibliographic record
Abstract
More than 30 years have passed since the discovery of the first plant metallothionein in wheat embryos, from which the emergence of a uniquely diverse metallothionein family with a fascinating array of structural nuances and molecular properties has been witnessed. Metallothioneins are not only constitutively expressed, but the production of different types of plant metallothionein is also stimulated by a myriad of endogenous and exogenous agents in both a temporally and spatially regulated manner. This ubiquitous, yet discrete expression of metallothioneins not only signifies their importance for plant survival and development, but also suggests a functional divergence for the individual plant metallothionein subfamilies. Understanding why one type of plant metallothionein has more advantageous structural and metal binding attributes over another for a given biological process is a crucial piece in the puzzle of assigning physiological functions to these proteins. In this review, we discuss how in vivo and in vitro studies have advanced our understanding of the structure-property-function relationship for the plant metallothionein family. In particular, we highlight the progress that has been made for the Type 4 plant metallothioneins.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".