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Record W4210339891 · doi:10.1080/14786419.2022.2032047

Antibacterial, anti-biofilm, and anti-adhesive activities of melittin, a honeybee venom-derived peptide, against quinolone-resistant uropathogenic <i>Escherichia coli</i> (UPEC)

2022· article· en· W4210339891 on OpenAlexaff
William Gustavo Lima, Francisco Leandro Batista Filho, Iasmin Pinheiro Lima, Daniela Carolina Simião, Júlio César Moreira Brito, Waleska Stephanie da Cruz Nizer, Valbert Nascimento Cardoso, Simone Odília Antunes Fernandes

Bibliographic record

VenueNatural Product Research · 2022
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsMelittinMicrobiologyEscherichia coliBiofilmPeptideQuinoloneAntibacterial activityMinimum inhibitory concentrationMultiple drug resistanceBiologyAntimicrobialBacteriaChemistryAntibioticsBiochemistry

Abstract

fetched live from OpenAlex

Here, we demonstrated the in vitro and in vivo antibacterial and anti-biofilm activities of melittin, a peptide derived from honeybee venom, against uropathogenic Escherichia coli (UPEC) resistant to quinolones. The minimum inhibitory concentration (MIC) of melittin varied from 0.5 to 8 μM. The bactericidal effect was considered rapid and potent (ranging from 3.0 to 6.0 h after incubation) against a quinolone-resistant and Extended Spectrum Beta-lactamase (ESBL)-producing UPEC strain. Prior exposure to melittin did not reduce the MIC of the quinolones tested, but it decreased the MIC of ceftizoxime by 8-fold due to its ability to form pores in the membrane. Furthermore, melittin disrupted mature biofilms (39.58% at 32 μM) and inhibited the adhesion of this uropathogen to the surfaces of urethral catheter. These results show that melittin is a promising molecule that can be incorporated into invasive urethral medical devices to prevent urinary infections caused by multidrug-resistant UPECs.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.054
GPT teacher head0.354
Teacher spread0.300 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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