Ultrastructural localization of heavy metals in the extraradical mycelium and spores of the arbuscular mycorrhizal fungus<i>Glomus intraradices</i>
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi, obligate symbionts of most plant species, are able to accumulate heavy metals, thereby, protecting plants from metal toxicity. In this study, the ultrastructural localization of Zn, Cu, and Cd in the extraradical mycelium and spores of the arbuscular mycorrhizal fungus Glomus intraradices grown in monoxenic cultures was investigated. Zinc, Cu, or Cd was applied to the extraradical mycelium to final concentrations of 7.5, 5.0, or 0.45 mmol/L, respectively. Samples were collected at time 0, 8 h, and 7 days after metal application and were prepared for rapid freezing and freeze substitution. Metal content in different subcellular locations (wall, cytoplasm, and vacuoles), both in hyphae and spores, was determined by energy-dispersive X-ray spectroscopy. In all treatments and fungal structures analysed, heavy metals accumulated mainly in the fungal cell wall and in the vacuoles, while minor changes in metal concentrations were detected in the cytoplasm. Incorporation of Zn into the fungus occurred during the first 8 h after metal addition with no subsequent accumulation. On the other hand, Cu steadily accumulated in the spore vacuoles over time, whereas Cd steadily accumulated in the hyphal vacuoles. These results suggest that binding of metals to the cell walls and compartmentalization in vacuoles may be essential mechanisms for metal detoxification.
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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) | 0.000 | 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 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".