Evidence map›Paper›PMID 30637221›Full record

ReviewJournal of clinical and translational hepatology2018

Therapeutic Roles of Bile Acid Signaling in Chronic Liver Diseases.

Yan Li, Lun-Gen Lu

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of clinical and translational hepatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 18% 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

11 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. [Application of Mdr2 gene knockout mice in liver disease research].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. [Clinical analysis of 33 cases of chronic liver diseases overlapping with CMV infection].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2020
    Article
  11. A Current Understanding of Bile Acids in Chronic Liver Disease.Journal of clinical and experimental hepatology
    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

2 authors at 1 institution in 1 country.

Yan LiDepartment of Gastroenterology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Lun-Gen LuDepartment of Gastroenterology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Shanghai First People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bile acids (BAs) are the major metabolic product of cholesterol, having detergent-like activities and being responsible for absorption of lipid and lipid-soluble vitamins. In addition, it has been increasingly recognized that BAs are important signaling molecules, regulating energy metabolism and immunity. Under physiological circumstances, synthesis and transport of BAs are precisely regulated to maintain bile acid homeostasis. Disruption of bile acid homeostasis results in pathological cholestasis and metabolic liver diseases. During the last decades, BAs have been gradually recognized as an important therapeutic target for novel treatment in chronic liver diseases. This review will provide an update on the current understanding of synthesis, transport and regulation of BAs, with a focus on the therapeutic roles of bile acid signaling in chronic liver diseases.

Indexed as

BAsCholestasisChronic liver diseasesFXRTGR5

Identifiers

PMID30637221
PMCPMC6328738
OpenAlexW2898396345

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.