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Record W3183263780 · doi:10.3390/d13080344

Genome Sequence of Brevundimonas sp., an Arsenic Resistant Soil Bacterium

2021· article· en· W3183263780 on OpenAlexaff
Javiera Soto, Trevor C. Charles, Michael D. J. Lynch, Giovanni Larama, Héctor Herrera, César Arriagada

Bibliographic record

VenueDiversity · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsUniversity of Waterloo
FundersFondo Nacional de Desarrollo Científico y TecnológicoComisión Nacional de Investigación Científica y Tecnológica
KeywordsEffluxArsenicBacteriaOperonGeneBioremediationBiologyGenomeMicrobiologyStrain (injury)Whole genome sequencingMicroorganismBacterial genome sizeGeneticsChemistryEscherichia coli

Abstract

fetched live from OpenAlex

Brevundimonas sp. is a bacteria able to grow in metal(loid) contaminated soil from Puchuncaví Valley, central Chile. This study has isolated a bacterial strain capable of growth under high doses of arsenic (As) (6000 mg L−1), and a draft genome sequence was generated. Additionally, real-time PCR was performed to examine the effect of As on some genes related to As resistance. Results demonstrated a total of 3275 predicted annotated genes with several genes related to the ars operon, metal(loid) resistance-related genes, metal efflux pumps, and detoxifying enzymes. Real-time PCR showed that the arsB involved in the efflux of As was down-regulated, whereas arsR, arsH, and ACR3 did not show differences with the addition of As. Our study provides novel evidence of diverse As regulating systems in tolerant bacteria that will lead to a better understanding of how microorganisms overcome toxic elements and colonize As contaminated soils and to the possible use of their specific properties in bioremediation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.024
GPT teacher head0.220
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2021
Admission routes1
Has abstractyes

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