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Record W3048037829 · doi:10.1101/2020.08.09.243485

<i>Trans</i> -cinnamaldehyde potently kills <i>Enterococcus faecalis</i> biofilm cells and prevents biofilm recovery

2020· preprint· en· W3048037829 on OpenAlexaff
Islam A. A. Ali, B. P. K. Cheung, JP Matinlinna, Céline M. Lévesque, Prasanna Neelakantan

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldDentistry
TopicEndodontics and Root Canal Treatments
Canadian institutionsUniversity of Toronto
FundersUniversity of Hong Kong
KeywordsBiofilmEnterococcus faecalisSodium hypochloriteChlorhexidineMicrobiologyRoot canalChemistryEnterococcusBiologyStaphylococcus aureusBacteriaAntibioticsMedicineDentistry

Abstract

fetched live from OpenAlex

Abstract Enterococcus faecalis is a biofilm-forming, nosocomial pathogen that is frequently isolated from failed root canal treatments. Contemporary root canal disinfectants are ineffective in eliminating these biofilms and preventing reinfection. As a result, there is a pressing need to identify novel and safe antibiofilm molecules. The effect of short-term (5 and 15 min) and long-term (24 h) treatments of TC on the viability of E. faecalis biofilms was compared with currently used root canal disinfectants. Treatment for 15 min with TC reduced biofilm metabolic activity as effective as 1% sodium hypochlorite and 2% chlorhexidine. Treatment with TC for 24 h was significantly more effective than 2% chlorhexidine in reducing the viable cell counts of biofilms. This serendipitous effect of TC was sustained for 10 days under growth-favoring conditions. For the first time, our study highlights the strong antibacterial activity of TC against E. faecalis biofilms, and notably, its ability to prevent biofilm recovery after treatment.

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 score0.003
Threshold uncertainty score0.008

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)0.0020.001

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 head0.015
GPT teacher head0.224
Teacher spread0.210 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicEndodontics and Root Canal TreatmentsFrench-language works237,207