Arsenic Speciation Analysis of Cultivated White Button Mushrooms (<i>Agaricus bisporus</i>) Using High-Performance Liquid Chromatography−Inductively Coupled Plasma Mass Spectrometry, and X-ray Absorption Spectroscopy
Bibliographic record
Abstract
Agaricus bisporus mushrooms were grown in compost amended with either arsenic-contaminated mine waste or an arsenate solution, to a final concentration of approximately 200 microg g(-1). Fungi were cultivated at a small-scale mushroom facility in Vineland (ON), where the controlled environment allowed for a large number of fruiting bodies (mushrooms) to be produced. The total arsenic concentrations as well as speciation were examined for each treatment over several harvests (breaks). Total concentrations were determined by acid digestion and inductively coupled plasma mass spectrometry (ICP-MS) detection and ranged from 2.3 to 16 microg g(-1) dry mass in treatment mushrooms. Arsenic compounds were extracted from mushrooms with methanol/water (1:1 v/v), and separated by high-performance liquid chromatography (HPLC, anion/cation exchange) before detection with ICP-MS. Fruiting bodies from all treatments contained arsenite, dimethylarsinic acid (DMA), and arsenobetaine (AB), and to a lesser extent arsenate and trimethylarsine oxide (TMAO). The ratio of arsenic compounds did not vary greatly over the first three harvests. AB was absent in compost not inoculated with A. bisporus supporting the hypothesis that AB is a product of fungal, not microbial, arsenic metabolism. X-ray absorption spectroscopy results lead us to hypothesize that AB plays a role in nutrient translocation within the fruiting body, as well as maintaining turgor pressure to ensure the mushroom cap remains elevated for maximum spore dispersal.
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) | 0.001 | 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) | 0.001 | 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".