Isolation and characterization of yeasts associated with plants growing in heavy-metal- and arsenic-contaminated soils
Why this work is in the frame
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Bibliographic record
Abstract
Yeasts were quantified and isolated from the rhizospheres of 5 plant species grown at 2 sites of a Mexican region contaminated with arsenic, lead, and other heavy metals. Yeast abundance was about 10(2) CFU/g of soil and 31 isolates were obtained. On the basis of the phylogenetic analysis of 26S rRNA and internal transcribed spacer fragment, 6 species were identified within the following 5 genera: Cryptococcus (80.64%), Rhodotorula (6.45%), Exophiala (6.45%), Trichosporon (3.22%), and Cystobasidium (3.22%). Cryptococcus spp. was the predominant group. Pectinases (51.6%), proteases (51.6%), and xylanases (41.9%) were the enzymes most common, while poor production of siderophores (16.1%) and indole acetic acid (9.67%) was detected. Isolates of Rhodotorula mucilaginosa and Cystobasidium sloffiae could promote plant growth and seed germination in a bioassay using Brassica juncea. Resistance of isolates by arsenic and heavy metals was as follows: As(3+) ≥ 100 mmol/L, As(5+) ≥ 30 mmol/L, Zn(2+) ≥ 2 mmol/L, Pb(2+) ≥ 1.2 mmol/L, and Cu(2+) ≥ 0.5 mmol/L. Strains of Cryptococcus albidus were able to reduce arsenate (As(5+)) into arsenite (As(3+)), but no isolate was capable of oxidizing As(3+). This is the first study on the abundance and identification of rhizosphere yeasts in a heavy-metal- and arsenic-contaminated soil, and of the reduction of arsenate by the species C. albidus.
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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