Evidence map›Paper›PMID 32849904›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2020

Si-Wu-Tang Alleviates Nonalcoholic Fatty Liver Disease via Blocking TLR4-JNK and Caspase-8-GSDMD Signaling Pathways.

Yaxing Zhang, Ge Zhou, Zifeng Chen, Weibing Guan, Jiongshan Zhang, Mingmin Bi, Fenglin Wang, Xinchao You, Yangjing Liao, Shuhui Zheng and 2 more

Open 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. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.7field-weighted citation impact, top 14% 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, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Hydrogen gas (HFrontiers in pharmacology · 2025
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Hepatocardiac or Cardiohepatic Interaction: From Traditional Chinese Medicine to Western Medicine.Evidence-based complementary and alternative medicine : eCAM · 2021
    Review
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

12 authors at 2 institutions in 1 country.

Yaxing ZhangDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-1179-8076
Ge ZhouDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Zifeng ChenBiofeedback Laboratory, Xinhua College of Sun Yat-sen University, Guangzhou, China.
Weibing GuanDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Jiongshan ZhangDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Mingmin BiDepartment of Otorhinolaryngology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
Fenglin WangDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Xinchao YouDepartment of Science and Education, The First Affiliated Hospital/School of Clinical Medicine of Guangdong Pharmaceutical University, Guangzhou, China.
Yangjing LiaoDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Shuhui ZhengResearch Center for Translational Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Kangquan XuBiofeedback Laboratory, Xinhua College of Sun Yat-sen University, Guangzhou, China.
Hongzhi YangDepartment of Traditional Chinese Medicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-9330-1931
Sun Yat-sen University · CNGuangdong Pharmaceutical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNonalcoholic fatty liver disease (NAFLD) has high global prevalence; however, the treatments of NAFLD are limited due to lack of approved drugs.

methodsMice were randomly assigned into three groups: Control group, NAFLD group, NAFLD plus Si-Wu-Tang group. A NAFLD mice model was established by feeding with a methionine- and choline-deficient (MCD) diet for four weeks. Si-Wu-Tang was given orally by gastric gavage at the beginning of 3rd week, and it lasted for two weeks. The treatment effects of Si-Wu-Tang were confirmed by examining the change of body weight, serum alanine aminotransferase (ALT) and aspartate transaminase (AST) levels, Oil Red O staining, and hematoxylin and eosin (H&E) staining of the liver samples and accompanied by steatosis grade scores. The expression and activation of the possible signaling proteins involved in the pathogenesis of NAFLD were determined by western blotting.

resultsMice fed with four weeks of MCD diet displayed elevated serum levels of ALT and AST, while there was decreased body weight. The hepatic Oil Red O staining and H&E staining showed severe liver steatosis with high steatosis grade scores. All these can be improved by treating with Si-Wu-Tang for two weeks. Mechanistically, the increased hepatic TLR4 expression and its downstream JNK phosphorylation induced by MCD diet were suppressed by Si-Wu-Tang. Moreover, the upregulations of Caspase-8, gasdermin D (GSDMD), and cleaved-GSDMD in liver mediated by MCD diet were all inhibited by Si-Wu-Tang.

conclusionsTreatment with Si-Wu-Tang improves MCD diet-induced NAFLD in part via blocking TLR4-JNK and Caspase-8-GSDMD signaling pathways, suggesting that Si-Wu-Tang has potential for clinical application in treating NAFLD.

Identifiers

PMID32849904
PMCPMC7439165
OpenAlexW3048734656

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.