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Record W2296750669 · doi:10.1128/mbio.00169-16

Kisameet Clay Isolated from the Central Coast of British Columbia, Canada, Demonstrates Broad-Spectrum Antimicrobial Activity

2016· article· en· W2296750669 on OpenAlexaffabout
George G. Zhanel, James A. Karlowsky

Bibliographic record

VenuemBio · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAntimicrobialAcinetobacter baumanniiEnterococcus faeciumMicrobiologyStaphylococcus aureusPseudomonas aeruginosaKlebsiella pneumoniaeEnterobacterEnterococcusAntibiotic resistanceAcinetobacterBiologyAntibioticsBacteriaEscherichia coli

Abstract

fetched live from OpenAlex

Clay minerals are naturally occurring layered phyllosilicates which consist of fine particles and possess antimicrobial activity. In a recent article, Behroozian et al. obtained Kisameet clay (KC) from Kisameet, from the central coast of British Columbia, Canada, northwest of Vancouver and assessed its antimicrobial activity versus 16 selected ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) possessing a variety of different resistance profiles [S. Behroozian, S. L. Svensson, and J. Davies, mBio 7(1):e01842-15, 2016, http://dx.doi.org/10.1128/mBio.01842-15]. KC demonstrated complete bacterial eradication of Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Staphylococcus aureus within 24 h. For Enterobacter spp., the organisms were eradicated with 1% KC within 5 h, while for Enterococcus faecium, it took 48 h to kill all organisms. Although many questions need to be answered, these exciting findings highlight the importance of testing natural substances/products from around the globe to assess whether they possess antimicrobial activity and potential for usage as topical, oral, or systemic agents for the treatment of multidrug-resistant pathogens.

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 score0.155
Threshold uncertainty score0.385

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 head0.004
GPT teacher head0.176
Teacher spread0.172 · 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

Citations4
Published2016
Admission routes2
Has abstractyes

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