Evidence map›Paper›PMID 32595723›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2020

Study on the Anticancer Effect of an Astragaloside- and Chlorogenic Acid-Containing Herbal Medicine (RLT-03) in Breast Cancer.

Yanchu Li, Xianyong Li, Chen Cuiping, Rong Pu, Yin Weihua

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.5field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
  2. Review
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  4. Biomolecules · 2024
    Review
  5. Research Progress on the Anti-Cancer Effects ofMolecules (Basel, Switzerland) · 2024
    Review
  6. Frontiers in oncology · 2024
    Review
  7. Article
  8. Article
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  11. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Yanchu LiOncology Department, West China Hospital of Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0003-2453-1298
Xianyong LiOncology Department, Chengdu Fuxing Hospital, Chengdu, China.ORCID https://orcid.org/0000-0003-4118-6203
Chen CuipingResearch Institution, Chengdu Fuxing Hospital, Chengdu, China.
Rong PuOncology Department, Chengdu Fuxing Hospital, Chengdu, China.ORCID https://orcid.org/0000-0003-3143-7996
Yin WeihuaOncology Department, Chengdu Fuxing Hospital, Chengdu, China.
Sichuan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough surgery, chemotherapy, radiotherapy, and endocrine therapy are widely used in clinical practice for breast cancer treatment, herbal medicines (HMs) are considered as an alternative to palliative treatments because of their coordinated intervention effects and relatively low side effects. Astragaloside (AS) and chlorogenic acid (CGA) are major active ingredients of

methodsRLT-03 was extracted using water and n-butanol, and the AS and CGA ingredients in RLT-03 were identified by high-performance liquid chromatography (HPLC) and evaporative light-scattering detector (ELSD). 4T1, EMT6, BT-549, and MDA-MB-231 breast cancer cell lines were used, and an EMT6 xenograft model was established. Cell proliferation, migration, and apoptosis were measured

resultsRLT-03 inhibited cell viability and induced apoptosis in a dose- and time-dependent manner.

conclusionRLT-03 exhibited therapeutic effects against breast cancer by regulating the expression of ligands of receptor tyrosine kinases (RTKs) and inflammatory factors. Thus, RLT-03 represents a potential supplementary HM that can be used in breast cancer therapy.

Identifiers

PMID32595723
PMCPMC7305538
OpenAlexW3034446286

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Registered trials

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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.