Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 477

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Arsenic Mobilization by the Dissimilatory Fe(III)-Reducing Bacterium Shewanella alga BrY

Cummings, David E., Caccavo,, Frank, Fendorf, Scott, Rosenzweig, R. Frank·1999·Environmental Science & Technology

Abstract

The mobility of arsenic commonly increases as reducing conditions are established within sediments or flooded soils. Although the reduction of arsenic increases its solubility at circumneutral pH, hydrous ferric oxides (HFO) strongly sorb both As(V) (arsenate) and As(III) (arsenite), the two primary inorganic species. Thus, in the presence of excess HFO, reductive dissolution of iron may be the dominant mechanism by which As is released into solution. In this paper, we report that the dissimilatory iron-reducing bacterium Shewanella alga strain BrY promoted As mobilization from a crystalline ferric arsenate as well as from sorption sites within whole sediments. S. alga cells released arsenate from the mineral scorodite (FeAsO 4 ·2H 2 O) as a result of dissimilatory (i.e., respiratory) reduction of Fe(III) to Fe(II). Solid-phase analysis with SEM-EDS and XAFS (X-ray absorption fine structure) spectroscopy revealed that the valence states of Fe and As in the solid-phase product were identical to those in solution, i.e., Fe(II) and As(V). Additionally, As(V) sorbed to sediments from Lake Coeur d'Alene, ID, a mining-impacted environment enriched in both Fe and As, was solubilized by the activity of S. alga BrY. In neither experiment was As(III) detected. We conclude that arsenic mobility can be enhanced by the activity of dissimilatory iron-reducing bacteria in the absence of arsenic reduction.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/es980541c

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 477

Metadata

Authors
Cummings, D. E., Caccavo, Fendorf, S., & Rosenzweig, R. F.
Venue
Environmental Science & Technology
Published
1999-01-15
Volume
33
Issue
5
Pages
723-729
ISSN
  • 0013-936X (ISSN-L)
  • 1520-5851
OpenAlex
W2046568229
Cited by
477
References
2
FWCI
12.64
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.