Fate of Cd during Microbial Fe(III) Mineral Reduction by a Novel and Cd-Tolerant <i>Geobacter</i> Species
Bibliographic record
Abstract
Fe(III) (oxyhydr)oxides affect the mobility of contaminants in the environment by providing reactive surfaces for sorption. This includes the toxic metal cadmium (Cd), which prevails in agricultural soils and is taken up by crops. Fe(III)-reducing bacteria can mobilize such contaminants by Fe(III) mineral dissolution or immobilize them by sorption to or coprecipitation with secondary Fe minerals. To date, not much is known about the fate of Fe(III) mineral-associated Cd during microbial Fe(III) reduction. Here, we describe the isolation of a new Geobacter sp. strain Cd1 from a Cd-contaminated field site, where the strain accounts for 10(4) cells g(-1) dry soil. Strain Cd1 reduces the poorly crystalline Fe(III) oxyhydroxide ferrihydrite in the presence of at least up to 112 mg Cd L(-1). During initial microbial reduction of Cd-loaded ferrihydrite, sorbed Cd was mobilized. However, during continuous microbial Fe(III) reduction, Cd was immobilized by sorption to and/or coprecipitation within newly formed secondary minerals that contained Ca, Fe, and carbonate, implying the formation of an otavite-siderite-calcite (CdCO3-FeCO3-CaCO3) mixed mineral phase. Our data shows that microbially mediated turnover of Fe minerals affects the mobility of Cd in soils, potentially altering the dynamics of Cd uptake into food or phyto-remediating plants.
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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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 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".