Evidence map›Paper›PMID 34880920›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2021

Exploring the Mechanisms of Arsenic Trioxide (

Xinmiao Wang, Luchang Cao, Jingyuan Wu, Guanghui Zhu, Xiaoyu Zhu, Xiaoxiao Zhang, Duoduo Han, Ning Shui, Baoyi Ni, Jie Li

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Pharmacology, Toxicology, and Therapeutics of Minerals in Traditional Medicine 2021.Evidence-based complementary and alternative medicine : eCAM · 2023
    Article
  5. 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

10 authors at 1 institution in 1 country.

Xinmiao WangGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.ORCID https://orcid.org/0000-0002-9367-4471
Luchang CaoGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.ORCID https://orcid.org/0000-0002-7460-2309
Jingyuan WuGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Guanghui ZhuGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.ORCID https://orcid.org/0000-0002-1182-1037
Xiaoyu ZhuGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Xiaoxiao ZhangGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Duoduo HanGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Ning ShuiGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Baoyi NiGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.
Jie LiGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing 100053, China.ORCID https://orcid.org/0000-0002-3461-8816
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveArsenic trioxide (

methodsThe potential targets of arsenic trioxide were collected from PubChem and TargetNet. HCC targets were obtained from the GeneCards database. Then, a protein-protein interaction (PPI) network of arsenic trioxide and HCC common targets was established using STRING. GO and KEGG pathway enrichment analyses were performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, an arsenic trioxide-target-pathway-HCC network was built by Cytoscape 3.2.1, and network topological analysis was carried out to screen the key candidate targets.

resultsA total of 346 corresponding targets of arsenic trioxide and 521 HCC-related targets were collected. After target mapping, a total of 52 common targets were obtained. GO analysis showed that the biological process was mainly involved in the negative regulation of cellular senescence, response to tumor necrosis factor, and cellular response to hypoxia. Molecular functions included NF-kappa B binding, enzyme binding, p53 binding, and transcription factor binding. Cellular components mainly were replication fork, ESC/E(Z) complex, RNA polymerase II transcription factor complex, and organelle membrane. KEGG pathways were mainly enriched in the PI3K-Akt signaling pathway, VEGF signaling pathway, p53 signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, AMPK signaling pathway, NF-kappa B signaling pathway, FoxO signaling pathway, ErbB signaling pathway, and MAPK signaling pathway. In the arsenic trioxide-target-pathway-HCC network, targets such as AKT1, RAF1, RELA, TP53, and PTEN had a higher degree

Identifiers

PMID34880920
PMCPMC8648446
OpenAlexW3216151021

What OpenQuestion holds

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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.