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Record W3013385399 · doi:10.3390/antibiotics9030136

Virulence-Inhibiting Herbal Compound Falcarindiol Significantly Reduced Mortality in Mice Infected with Pseudomonas aeruginosa

2020· article· en· W3013385399 on OpenAlexaff
Pansong Zhang, Qiaolian Wu, Lin Chen, Kangmin Duan

Bibliographic record

VenueAntibiotics · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of Manitoba
FundersNatural Science Foundation of Shaanxi Provincial Department of EducationNatural Science Foundation of Shaanxi Province
KeywordsVirulencePseudomonas aeruginosaMicrobiologyQuorum sensingSwarming motilityPyocyaninBiologyGeneBiofilmBacteriaBiochemistryGenetics

Abstract

fetched live from OpenAlex

Antipathogenic compounds that target the virulence of pathogenic bacteria rather than their viability offer a promising alternative approach to treat infectious diseases. Using extracts from 30 Chinese herbs that are known for treating symptoms resembling infections, we identified an active compound falcarindiol from Notopterygium incisum Ting ex H. T. Chang that showed potent inhibitory activities against Pseudomonas aeruginosa multiple virulence factors. Falcarindiol significantly repressed virulence-related genes, including the type III secretion system (T3SS); quorum sensing synthase genes lasIR and rhlIR; lasB; motility-related genes fliC and fliG; and phenazine synthesis genes phzA1 and phzA2. P. aeruginosa swarming motility and pyocyanin production were reduced significantly. In a burned mouse model, falcarindiol treatment significantly reduced the mortality in mice infected with P. aeruginosa, indicating that falcarindiol is a promising antipathogenic drug candidate for treating P. aeruginosa infections.

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 categoriesMeta-epidemiology (narrow)
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 score0.035
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.023
GPT teacher head0.243
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 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

Citations16
Published2020
Admission routes1
Has abstractyes

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