Molecular evolution of aquaporins and silicon influx in plants
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Silicon (Si), although mostly ignored by plant nutritionists and ecologists, is now gaining more attention because of its beneficial role in plant fitness under stress environment imposed by a diverse range of biotic and abiotic factors. Si appears to systematically confer benefits to plants as long as a given species can absorb the element. Here, we review recent developments regarding the molecular mechanisms, evolution, regulation and structural specificity of influx transporter proteins involved in Si uptake by plants. Si absorption is facilitated by specific nodulin 26‐like intrinsic proteins ( NIP s). The Si transporter NIP s have evolved a unique amino acid selective filter ( SF ), which is one of the required features to regulate the influx of Si. While Si accumulation in plants requires the dual action of both an influx transporter and an efflux transporter, it appears that the presence of the former is the indispensable key for a plant to be able to absorb Si. Based on sequence analyses and comparisons, influx transporters appear to have conserved features across all species that allow to discriminate between plants that are Si competent or not. While it is unclear how and why plants have acquired or lost this trait, genomic data now offer a reliable tool to predict with accuracy which plant species are predisposed to benefit from Si. This will undoubtedly result in a better understanding of Si role in many fundamental aspects of ecology regarding plant fitness under stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it