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Record W2611288570 · doi:10.5539/ijb.v9n3p1

Treatment of Chromium Pollution by the Reductase Enzyme Generated by a Chromium-Resistant Bacterium Isolated in Dewatering Sludge

2017· article· en· W2611288570 on OpenAlexvenueno aff
Paul Fabrice Nguema, Zejiao Luo, Zachari Mohamadou Mounir, M A Jun

Bibliographic record

VenueInternational Journal of Biology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicChromium effects and bioremediation
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsBioremediationChromiumStrain (injury)ThiosulfateChemistryBacteriaFood scienceBacillus cereusReductaseEnzymeSubstrate (aquarium)MicrobiologyBiochemistryNuclear chemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

An efficient Cr (VI)-resistant and reducing bacterial strain was successfully isolated in dewatering sludge collected from a sewage treatment plant, and characterized in vitro Cr (VI) reduction through a reductase enzyme. Phylogenetic analysis using 16S rDNA gene sequencing revealed that the newly isolated strain namely Pf-1 was closely related to Bacillus cereus. The strain almost reduced 0.17 mM Cr (VI) within 24h incubation and the presence of different substrates such as glucose, sucrose, or acetate significantly enhanced the reduction rate of Cr (VI) to Cr (III). However, addition of the same substrate at the stationary phase of the microbial growth increased the reduction rate as well as bacterial growth. Additionally, raising the concentration of thiosulfate in the medium doubled the reduction rate under similar conditions. Assay with different fractions of the cells demonstrated that the reductase enzyme activity was mainly associated with the cytoplasmic fraction. The maximum activity was 23.3 µM h-1 mg-1 protein and was obtained at the Cr (VI) concentration of 2 mM. The promising strain can be efficiently employed for bioremediation of Cr (VI) polluted sites.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.260
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2017
Admission routes1
Has abstractyes

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