Evidence map›Paper›PMID 35911158›Full record

ArticleEvidence-based complementary and alternative medicine : eCAM2022

Prediction of the Active Components and Mechanism of

Xiaoxue Wang, Ping Wang, Haitao Du, Na Li, Tianyuan Jing, Ru Zhang, Wanying Qi, Yanan Hu, Tianyu Liu, Lanxin Zhang and 4 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

4 citing papers in PubMed, 9 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

14 authors at 5 institutions in 2 countries.

Xiaoxue Wang *College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Ping Wang *Shandong Academy of Chinese Medicine, Jinan, Shandong, China.ORCID https://orcid.org/0000-0001-7517-8688
Haitao Du *College of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Na LiCollege of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Tianyuan JingCollege of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Ru ZhangCollege of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Wanying QiCollege of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Yanan HuCollege of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Tianyu LiuShanghai International Studies University, Shanghai, China.
Lanxin ZhangMacau University of Science and Technology, Macau, China.
Nan XuShandong Academy of Chinese Medicine, Jinan, Shandong, China.
Yi WangShandong Academy of Chinese Medicine, Jinan, Shandong, China.ORCID https://orcid.org/0000-0002-3168-9360
Huimin ZhangShandong Academy of Chinese Medicine, Jinan, Shandong, China.
Xiaoyan DingShandong Academy of Chinese Medicine, Jinan, Shandong, China.ORCID https://orcid.org/0000-0001-9294-1630
Shandong University of Traditional Chinese Medicine · CNShandong Academy of Chinese Medicine · CNMacau University of Science and Technology · MOShanghai International Studies University · CNTianjin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Methods: UPLC-Q-Exactive-MS was used to analyze the main chemical components of FSL. The compound disease target network, PPI, GO, and KEGG were used to obtain key targets and potential ways. Then, the molecular docking was verified by Schrödinger Maestro software. Next, the cell model of RSV infection was established, and the inhibitory effect of each drug on RSV was detected. Finally, western blotting was used to detect the effect of the active components of FSL on the expression of PI3K/AKT signaling pathway-related protein. Results: UPLC-Q-Exactive-MS analysis showed that there were 67 main chemical constituents in FSL, while network pharmacological analysis showed that there were 169 anti-RSV targets of the active components in FSL, involving 177 signal pathways, among which PI3K/AKT signal pathway played an important role in the anti-RSV process of FSL. The results of molecular docking showed that cryptochlorogenic acid, phillyrin, phillygenin, rutin, and rosmarinic acid had higher binding activities to TP53, STAT3, MAPK1, AKT1, and MAPK3, respectively. Conclusion: The active ingredients of FSL, phillyrin, and rosmarinic acid can play an anti-RSV role by inhibiting PI3K/AKT signaling pathway. This study provides reliable theoretical and experimental support for the anti-RSV treatment of FSL.

Identifiers

PMID35911158
PMCPMC9328944
OpenAlexW4286009605

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.