MétaCan
Menu
Back to cohort
Record W2159853997 · doi:10.1139/cjm-2013-0284

Bacteriocins of<i>Bacillus thuringiensis</i>can expand the potential of this bacterium to other areas rather than limit its use only as microbial insecticide

2013· review· en· W2159853997 on OpenAlexvenueno aff
Norma M. de la Fuente‐Salcido, Luz E. Casados‐Vázquez, José E. Barboza‐Corona

Bibliographic record

VenueCanadian Journal of Microbiology · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect Resistance and Genetics
Canadian institutionsnot available
Fundersnot available
KeywordsBacillus thuringiensisBacteriocinBiologyBiopesticideBacteriaMicrobiologyBacillus (shape)Antimicrobial peptidesAntimicrobialBiotechnologyPesticideEcologyGenetics

Abstract

fetched live from OpenAlex

Various strains of Bacillus thuringiensis are among the most successful entomopathogenic bacteria used commercially as biopesticides owing to their ability to synthesize insecticidal crystal (Cry) and cytolytic (Cyt) protein toxins during sporulation, and vegetative insecticidal (VIPs) proteins during the vegetative phase of growth. Whereas much is known about the molecular biology of Cry, Cyt, and VIPs, comparatively little is known about other proteins and metabolites synthesized by B. thuringiensis that could also have applied value. Here, we review recent reports on bacteriocins synthesized by this bacterium as they relate to antibacterial activity, molecular genetics, biophysical and biochemical properties, and methods used to separate and purify these antimicrobial peptides. We highlight the potential of bacteriocins for use as food preservatives, antibiotics, plant protection, and plant growth promoters. We suggest that B. thuringiensis could be used not only in biological control of insects but also in other agronomical and industrial areas of public interest.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.238
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations47
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of MicrobiologySame topicInsect Resistance and GeneticsFrench-language works237,207