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Record W2170370760 · doi:10.1039/c5fo00820d

Rosa canina L. – new possibilities for an old medicinal herb

2015· article· en· W2170370760 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 · 2015
Typearticle
Languageen
FieldMedicine
TopicMedicinal Plants and Neuroprotection
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsTraditional medicineMedicinal herbsHerbBiologyMedicine

Abstract

fetched live from OpenAlex

Health beneficial properties of Rosa canina species are mainly attributed to rose hips, while the leaves are usually discarded as waste. In the present study we investigated chemical constituents as well as antimicrobial and antibiofilm potential of R. canina methanolic leaf extract. Chemical analysis showed that dominant phenolic compounds are quercetin and isorhamnetin derivatives (isoquercetin and isorhamnetin-3-O-rutinoside). Among the tested bacteria, Pseudomonas aeruginosa and Salmonella typhimurium were the most susceptible to the activity of R. canina leaf extract with MIC and MBC values both 0.009 mg mL(-1). For most of the bacterial strains investigated the extract showed significantly higher activity compared to the used standard compounds streptomycin and ampicillin. Also the tested extract powerfully inhibited in vitro biofilm growth in Pseudomonas aeruginosa, Staphylococcus aureus, Leishmania monocytogenes and Escherichia coli at sub MIC-levels. With concentrations equal to 1/4 and 1/8 of MIC values biofilm growth of P. aeruginosa and E. coli was inhibited by 90%. The obtained results are significant for a wider and efficient use of R. canina leaves.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.489
Threshold uncertainty score0.436

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 head0.116
GPT teacher head0.303
Teacher spread0.187 · 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