Evidence map›Paper›PMID 32734365›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2021

Systemic pharmacology understanding of the key mechanism of Sedum sarmentosum Bunge in treating hepatitis.

MingZhu Chen, Qi Sun

Abstract read
PubMed Publisher
In one paragraph

Article in Naunyn-Schmiedeberg's archives of pharmacology, 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
1.2field-weighted citation impact, top 21% 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, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. 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

2 authors at 1 institution in 1 country.

MingZhu ChenDepartment of Pharmacy, Shanghai Tenth People's Hospital, Shanghai, 200072, China.
Qi SunDepartment of Pharmacy, Shanghai Tenth People's Hospital, Shanghai, 200072, China. qxysq@sina.com.ORCID 0000-0003-0988-4570
Shanghai Tenth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sedum sarmentosum Bunge is a Traditional Chinese Medicine that is widely used in treating hepatitis, whereas the detailed mechanisms have not been fully interpreted. A systemic pharmacology method including absorption, distribution, metabolism and elimination screening, drug targeting, interaction network plotting, and enrichment analysis was applied for exploring the underlying mechanisms of Sedum sarmentosum Bunge in the treatment of hepatitis. A total of 47 ingredients were identified in Sedum sarmentosum Bunge, and 5 active ingredients (DFV, isorhamnetin, beta-sitosterol, luteolin and quercetin) were screened out with the criteria of oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18. Those 5 ingredients interacted with 170 targets, 163 of which were hepatitis-related. By compound-target-disease network plotting, protein-protein interaction network plotting and enrichment analysis, the pathways that the 5 ingredients engaged in during hepatitis development and progression were investigated, such as threonine-protein kinase signaling. The integrated systemic pharmacology analysis facilitates the in-depth understanding of Sedum sarmentosum Bunge in the hepatitis treatment, which also paves the way for further knowledge of the molecular mechanism of Sedum sarmentosum Bunge in treating hepatitis.

Indexed as

SedumAnimalsBiological AvailabilityHepatitisHumansMedicine, Chinese TraditionalPharmacologyPhytochemicalsProtein Interaction MapsSystems BiologyPhytochemicalsHepatitisNetworkSedum sarmentosum BungeSystemic pharmacology

Identifiers

PMID32734365
OpenAlexW3046770009

What OpenQuestion holds

Textmetadata
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.