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Record W4376225928 · doi:10.1021/acs.est.3c00407

Exogenous Electroactive Microbes Regulate Soil Geochemical Properties and Microbial Communities by Enhancing the Reduction and Transformation of Fe(III) Minerals

2023· article· en· W4376225928 on OpenAlexaff
Xiaolin Zhang, Yuxia Liu, Qixing Zhou, Yuge Bai, Ruixiang Li, Li Tian, Jintian Li, Daniel S. Alessi, Kurt O. Konhauser

Bibliographic record

VenueEnvironmental Science & Technology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicrobial Fuel Cells and Bioremediation
Canadian institutionsUniversity of Alberta
FundersMinistry of Science and Technology of the People's Republic of ChinaMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsEnvironmental chemistryMicrobial population biologyFerrihydriteChemistryFirmicutesProteobacteriaSoil waterBacteriaMicroorganismEcologyBiologyBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Electroactive microbes can conduct extracellular electron transfer and have the potential to be applied as a bioresource to regulate soil geochemical properties and microbial communities. In this study, we incubated Fe-limited and Fe-enriched farmland soil together with electroactive microbes for 30 days; both soils were incubated with electroactive microbes and a common iron mineral, ferrihydrite. Our results indicated that the exogenous electroactive microbes decreased soil pH, total organic carbon (TOC), and total nitrogen (TN) but increased soil conductivity and promoted Fe(III) reduction. The addition of electroactive microbes also changed the soil microbial community from Firmicutes -dominated to Proteobacteria -dominated. Moreover, the total number of detected microbial species in the soil decreased from over 700 to less than 500. Importantly, the coexistence of N-transforming bacteria, Fe(III)-reducing bacteria and methanogens was also observed with the addition of electroactive microbes in Fe-rich soil, indicating the accelerated interspecies electron transfer of functional microflora.

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 categoriesScience and technology studies
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 score0.004
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
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 head0.007
GPT teacher head0.176
Teacher spread0.170 · 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.

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

Citations41
Published2023
Admission routes1
Has abstractyes

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