Evidence map›Paper›PMID 29018356›Full record

ArticleFrontiers in physiology2017

Xiao-Yao-San, a Chinese Medicine Formula, Ameliorates Chronic Unpredictable Mild Stress Induced Polycystic Ovary in Rat.

Hao-Yu Sun, Quan Li, Yu-Ying Liu, Xiao-Hong Wei, Chun-Shui Pan, Jing-Yu Fan, Jing-Yan Han

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 8% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Hao-Yu SunDepartment of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking UniversityBeijing, China.
Quan LiTasly Microcirculation Research Center, Peking University Health Science CenterBeijing, China.
Yu-Ying LiuTasly Microcirculation Research Center, Peking University Health Science CenterBeijing, China.
Xiao-Hong WeiTasly Microcirculation Research Center, Peking University Health Science CenterBeijing, China.
Chun-Shui PanTasly Microcirculation Research Center, Peking University Health Science CenterBeijing, China.
Jing-Yu FanTasly Microcirculation Research Center, Peking University Health Science CenterBeijing, China.
Jing-Yan HanDepartment of Integration of Chinese and Western Medicine, School of Basic Medical Sciences, Peking UniversityBeijing, China.
Peking University · CNShanghai Innovative Research Center of Traditional Chinese Medicine · CNState Administration of Traditional Chinese Medicine of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic stress induces endocrine disturbance, which contributes to the development of polycystic ovary syndrome (PCOS), a condition that remains a challenge for clinicians to cope with. The present study investigated the effect of Xiao-Yao-San (XYS), a traditional Chinese medicine formula used for treatment of gynecological disease, on the chronic stress-induced polycystic ovary and its underlying mechanism. Female Sprague-Dwaley rats underwent a 3 weeks chronic unpredictable mild stress (CUMS) procedure to establish the PCOS model, followed by 4 weeks treatment with XYS (0.505 g/kg or 1.01 g/kg) by gavage. Granulosa cells were exposed to noradrenaline (1 mM)

Indexed as

beta 2 adrenergic receptorchronic unpredictable stressgranulosa cells autophagynoradrenalinepolycystic ovary

Identifiers

PMID29018356
PMCPMC5614964
OpenAlexW2757897343

What OpenQuestion holds

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LicenceCC BY
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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.