Heavy metal capture by autochthonous yeasts from a volcanic influenced environment of Patagonia
Bibliographic record
Abstract
Heavy metals at elevated concentrations are a major threat to agricultural and human health. Typically, human activities tend to release these metals to the environment in aqueous solutions, generating high levels of pollution due to the mobility of the heavy metals. The aim of the present work was to assess heavy metal tolerance in yeasts isolated from Río Agrio − Lake Caviahue volcanic acidic aquatic environment and to evaluate the capacity of selected strains to capture metals in acidic culture media conditions. The ability of three yeast species, Cryptococcus agrionensis , Cryptococcus sp. 2, and Coniochaeta fodinicola , to tolerate and capture metals in live cultures has been evaluated. These three yeast species showed high tolerance to low pH and elevated concentrations of metals, thus implying their autochthonous status. Minimal inhibitory concentration (MIC) for growth obtained for these isolates showed elevated tolerance to the six heavy metals evaluated and were significantly higher than those registered for other microorganisms. C. agrionensis was able to capture 15.80 mg (g biomass) −1 of Cu 2+ (MIC: 0.22 g L −1 ), Cryptococcus sp. 2 was able to capture 36.25 and 65.28 mg (g biomass) −1 of Ni 2+ and Zn 2+ , respectively (MIC: 0.56 and 1.68, respectively), and C. fodinicola was able to capture 67.11 mg (g biomass) −1 of Zn 2+ (MIC: 3.75). This work reported the ability of yeasts to capture metals in acidic conditions for the first time. We hope that it represents the step‐stone for future researches in the ability and metabolism of yeasts form acidic aquatic environment related to metal tolerance and capture.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Microbiology study of heavy metal capture by yeasts; the object is bioremediation.
The study investigates heavy-metal tolerance and capture by yeasts.
Microbiology of heavy-metal capture by yeasts.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".