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Record W3035646263 · doi:10.3389/fphar.2020.00813

The Potentiality of Herbal Remedies in Primary Sclerosing Cholangitis: From In Vitro to Clinical Studies

2020· review· en· W3035646263 on OpenAlexfundno aff
Elisa Ceccherini, Antonella Cecchettini, Maria Aurora Morales, Silvia Rocchiccioli

Bibliographic record

VenueFrontiers in Pharmacology · 2020
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsnot available
FundersMcMaster University
KeywordsMedicineSalvia miltiorrhizaPrimary sclerosing cholangitisFibrosisSilibininCirrhosisSilybum marianumHepatic fibrosisPrimary biliary cirrhosisTraditional medicinePathologyPharmacologyGastroenterologyTraditional Chinese medicineDisease

Abstract

fetched live from OpenAlex

Primary Sclerosing Cholangitis is a complex pathological condition, characterized by chronic inflammation and fibrosis of the biliary epithelium. Without proper clinical management, progressive bile ducts and liver damage lead to cirrhosis and, ultimately, to liver failure. The known limited role of current drugs for treating this cholangiopathy has driven Researchers to assess alternative therapeutic options. Some herbal remedies and their phytochemicals have shown anti-fibrotic properties in different experimental models of hepatic diseases and, occasionally, in clinical trials in primary sclerosing cholangitis patients; however their mechanism of action is not completely understood. This review briefly examines relevant studies focusing on the potential anti-fibrotic properties of Silybum marianum, Curcuma longa, Salvia miltiorrhiza and quercetin. Each natural product is individually reviewed and the possible mechanisms of action discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.117
GPT teacher head0.444
Teacher spread0.327 · 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 designSystematic review
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

Citations5
Published2020
Admission routes1
Has abstractyes

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