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Record W2033750520 · doi:10.1155/2014/436206

The Kampo Medicine Rokumigan Possesses Antibiofilm, Anti-Inflammatory, and Wound Healing Properties

2014· article· en· W2033750520 on OpenAlexaff
James Liao, Jabrane Azelmat, Леи Жао, Masami Yoshioka, Daisuke Hinode, Daniel Grenier

Bibliographic record

VenueBioMed Research International · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacological Effects of Natural Compounds
Canadian institutionsUniversité Laval
FundersUniversidade de São Paulo
KeywordsKampoWound healingMedicineTraditional medicinePathologyAlternative medicineSurgery

Abstract

fetched live from OpenAlex

Periodontal diseases, which are inflammatory diseases of bacterial origin affecting the tooth-supporting tissues, are characterized by inflammation and destruction of gingival connective tissue and alveolar bone, and may lead to tooth loss. The aim of the study was to investigate Rokumigan, a Kampo Japanese traditional medicine made of six different plants, for its capacity to prevent biofilm formation by Fusobacterium nucleatum, to inhibit interleukin-6 (IL-6) and interleukin-8 (IL-8) secretion by mucosal cells, and to promote wound healing in a fibroblast model. Using a microplate colorimetric assay, Rokumigan prevented biofilm formation by F. nucleatum, while it had no effect on bacterial growth. Rokumigan inhibited IL-6 secretion in both epithelial cells and fibroblasts stimulated with lipopolysaccharide. However, it caused no significant inhibition of IL-8 secretion by both cell types. Rokumigan significantly increased proliferation and migration of gingival fibroblasts in a wound healing assay. In conclusion, the Kampo formulation Rokumigan, through suppression of biofilm formation by F. nucleatum, inhibition of IL-6 secretion by gingival epithelial cells and fibroblasts, and promotion of wound healing in a fibroblast model, may have potential application for periodontal diseases.

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)0.006
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.254
GPT teacher head0.519
Teacher spread0.265 · 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.

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

Citations21
Published2014
Admission routes1
Has abstractyes

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