Comparative analysis of aluminum accumulation in leaves of three angiosperm species
Bibliographic record
Abstract
Aluminum (Al) accumulators are widely distributed in the plant kingdom but phylogenetic implications of internal Al detoxification mechanisms are not well understood. We investigated differences in the characteristics of Al accumulation (i.e., accumulation potential, chemical form, and localization) in three woody Al accumulators, Symplocos chinensis (Lour.) Druce var. leucocarpa (Nakai) Ohwi f. pilosa (Nakai) Ohwi (Symplocaceae, Ericales), Melastoma malabathricum L., and Tibouchina urvilleana Cogn. (both Melastomataceae, Myrtales). The order of Al accumulation potential under hydroponic conditions was S. chinensis ≈ M. malabathricum > T. urvilleana. Oxalate was at least partly involved in the internal Al detoxification mechanisms in leaves of all three Al accumulators, based on a correlation analysis between Al and organic acid in water and 0.02 mol·L−1 HCl extracts and the 27Al nuclear magnetic resonance spectra of intact leaves. However, the Al forms in the leaves were not simple Al-ligand complexes in a specific cell structure. Al localization in leaf sections differed among the three species. Extremely high levels of Al were found in trichomes of the lower epidermis in leaves of T. urvilleana. These data illustrate that woody Al-accumulating angiosperms have independently developed various internal Al-tolerance mechanisms in which oxalate plays a significant role.
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.
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 | 0.001 | 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".