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Record W2174004567 · doi:10.1586/14787210.2016.1118345

The antimicrobial properties of ginseng and ginseng extracts

2015· review· en· W2174004567 on OpenAlexaff
Karina Kachur, Zacharias E. Suntres

Bibliographic record

VenueExpert Review of Anti-infective Therapy · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsNOSM UniversityLakehead University
Fundersnot available
KeywordsGinsengAntimicrobialTraditional medicineAraliaceaeBiologyImmune systemYeastMicrobiologyQuorum sensingBiofilmBacteriaMedicineBiochemistryImmunology

Abstract

fetched live from OpenAlex

Ginseng is commonly used in traditional Chinese medicine as a tonic and an adaptogen to reduce fatigue and boost the immune system. In recent years, ginseng extracts are shown to have both bacteriostatic and bactericidal actions and seem to exert their effects by several mechanisms, including disruption of biofilms, inhibition of quorum-sensing and virulence factors, and altering motility. Also, ginseng extracts are shown to have antifungal properties as demonstrated by their ability to inhibit the growth of several mold and yeast species. Extracts from ginseng root have a strong antiviral activity against the RNA viruses in cell cultures and animal models. In addition to the antimicrobial activities, ginseng extracts are shown to possess immunomodulatory properties involved in the amelioration of infections. The present paper describes the antimicrobial effects of ginseng and its extracts.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.357
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations40
Published2015
Admission routes1
Has abstractyes

Explore more

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