Evidence map›Paper›PMID 36212944›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Shenxian-Shengmai Oral Liquid Evoke Autophagy of Fibroblast to Attenuate Sinoatrial Node Fibrosis in Sick Sinus Syndrome Mice via the AKT/mTOR Pathway.

Chen Chen, Heng Zhang, Siyi Hou, Yue Liu, Lu Ren, Miao Hao, Keyan Chen, Lingkang Li, Xintong Cai, Zisu Deng and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Evidence-based complementary and alternative medicine : eCAM, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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.

Chen ChenLiaoning University of Traditional Chinese Medicine, Shenyang, China.ORCID https://orcid.org/0000-0002-7154-5767
Heng ZhangLiaoning University of Traditional Chinese Medicine, Shenyang, China.ORCID https://orcid.org/0000-0002-4896-2466
Siyi HouDepartment of Cardiology, Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, Shenyang, China.
Yue LiuLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Lu RenLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Miao HaoLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Keyan ChenDepartment of Laboratory Animal Science, China Medical University, Shenyang, China.ORCID https://orcid.org/0000-0002-8041-4312
Lingkang LiLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Xintong CaiLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Zisu DengLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Zhuang LiuLiaoning University of Traditional Chinese Medicine, Shenyang, China.
Ping HouLiaoning University of Traditional Chinese Medicine, Shenyang, China.ORCID https://orcid.org/0000-0003-2783-0728
Liaoning University of Traditional Chinese Medicine · CNChina Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sick sinus syndrome (SSS) is closely associated with cardiac syncope and sudden death, wherein sinoatrial node (SAN) fibrosis is one of the main pathological changes that occur. Shenxian-Shengmai oral liquid (SXSM) has been clinically proven to significantly improve the heart rate of SSS patients. In this study, we aimed to explore the mechanism of SXSM in reducing the SAN fibrosis by combining

Identifiers

PMID36212944
PMCPMC9534627
OpenAlexW4297498634

What OpenQuestion holds

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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.