Evidence map›Paper›PMID 34595163›Full record

ArticleFrontiers in cell and developmental biology2021

Multi-Omics Integration to Reveal the Mechanism of Hepatotoxicity Induced by Dictamnine.

Can Tu, Ziying Xu, Lichun Tian, Zihui Yu, Tieshang Wang, Zhaojuan Guo, Jingxuan Zhang, Ting Wang

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Impact of Traditional Chinese Medicine Antioxidants on Oxidative Stress and Drug-Induced Liver Injury: A Review.Medical science monitor : international medical journal of experimental and clinical research · 2024
    Review
  2. Article
  3. Article
  4. Article
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

8 authors.

Can TuBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Ziying XuBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Lichun TianBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Zihui YuKey Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences (CAS), Beijing, China.
Tieshang WangBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Zhaojuan GuoBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Jingxuan ZhangBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.
Ting WangBeijing Research Institute of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Herb-induced liver injury (HILI) has become a great concern worldwide due to the widespread usage of herbal products. Among these products is Dictamni Cortex (DC), a well-known Traditional Chinese Medicine (TCM), widely used to treat chronic dermatosis. Dictamni Cortex has drawn increasing attention because of its hepatotoxicity caused by the hepatotoxic component, dictamnine. However, the potential hepatotoxicity mechanism of dictamnine remains unclear. Therefore, this study aimed to use the multi-omics approach (transcriptomic, metabolomic, and proteomic analyses) to identify genes, metabolites, and proteins expressions associated with dictamnine-induced hepatotoxicity. A study on mice revealed that a high dose of dictamnine significantly increases serum aspartate aminotransferase (AST) activity, total bilirubin (TBIL), and direct bilirubin (DBIL) levels, the relative liver weight and liver/brain weight ratio in female mice (

Indexed as

dictamnineherb induced liver injurymechanismmulti-omics analysisRoussel Uclaf causality assessment method

Identifiers

PMID34595163
PMCPMC8476863

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