Evidence map›Paper›PMID 22693536›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2012

Astragaloside IV Downregulates β-Catenin in Rat Keratinocytes to Counter LiCl-Induced Inhibition of Proliferation and Migration.

Fu-Lun Li, Xin Li, Yi-Fei Wang, Xiu-Li Xiao, Rong Xu, Jie Chen, Bin Fan, Wen-Bin Xu, Lin Geng, Bin Li

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In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Fu-Lun LiDepartment of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 200437, China.
Xin Li
Yi-Fei Wang
Xiu-Li Xiao
Rong Xu
Jie Chen
Bin Fan
Wen-Bin Xu
Lin Geng
Bin Li
Shanghai University of Traditional Chinese Medicine · CNYueyang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Re-epithelialization is a crucial step towards wound healing. The traditional Chinese medicine, Astragalus membranaceus (Fisch) Bge, has been used for hundreds of years for many kinds of ulcerated wounds. Recent research has identified the active compound in this drug as astragaloside IV (AS-IV), but the underlying molecular mechanisms of its therapeutic action on keratinocytes remain poorly understood. In this study, we used an in vitro model of ulcer-like wound processes, lithium chloride (LiCl)-induced cultured mouse keratinocytes, to investigate the effects of AS-IV treatment. The effects on cell proliferation were evaluated by the MTS/PMS colorimetric assay, effects on cell migration were determined by a wound-healing scratch experiment, effects on the cell cycle were analyzed by flow cytometry, and effects on protein expression were analyzed by immunoblotting and immunofluorescence. LiCl strongly inhibited cell proliferation and migration, up-regulated β-catenin expression, and down-regulated proliferating cell nuclear antigen (PCNA) expression. AS-IV treatment attenuat the inhibition of proliferation and migration, significantly reducing the enhanced β-catenin expression, and recovering PCNA and β-tubulin expression. Thus, AS-IV mediates mouse keratinocyte proliferation and migration via regulation of the Wnt signaling pathway. Down-regulating β-catenin to increase keratinocyte migration and proliferation is one mechanism by which AS-IV can promote ulcerated wound healing.

Identifiers

PMID22693536
PMCPMC3368212
OpenAlexW2013884675

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.