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Record W2890232220 · doi:10.1039/c8fo01466c

Characterization of phenolic compounds in tincture of edible<i>Nepeta nuda</i>: development of antimicrobial mouthwash

2018· article· en· W2890232220 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood & Function · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog RazvojaFundação para a Ciência e a TecnologiaFederación Española de Enfermedades Raras
KeywordsNepetaTincture (heraldry)AntimicrobialLamiaceaeTraditional medicinePathogenic bacteriaBiologyMicrobiologyBacteriaMedicine

Abstract

fetched live from OpenAlex

The activity of edible Nepeta nuda L. (Lamiaceae) tincture and Listerine towards a selected group of oral pathogenic microorganisms (4 bacterial and 9 fungal strains) has been explored. Their potentials to inhibit the formation of biofilm and to diminish established biofilm have been compared. The amount of N. nuda tincture and swishing time necessary for reaching better or equivalent antimicrobial effect than that of Listerine have been predicted. Phenolic compounds in N. nuda tincture are determined by LC-DAD/ESI-MSn. Both Listerine and N. nuda tincture possess good antimicrobial potentials (MIC in the range of 0.8-15 μL per well) including inhibition of biofilms. Rosmarinic acid and verminoside are the most dominant phenolic compounds present in the N. nuda tincture. Based on in vitro results, we infer that it is more desirable to swish 20 mL of mouthwashes (Listerine and N. nuda tincture, 100 mg mL-1) for 30 s when dealing with selected microorganisms in general and for 60 s (N. nuda tincture) when dealing with bacterial biofilms.

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.

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 score0.171
Threshold uncertainty score0.192

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 head0.014
GPT teacher head0.190
Teacher spread0.176 · 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