Evidence map›Paper›PMID 36593772›Full record

ArticleBioMed research international2022

A Network Pharmacology-Based Study on the Mechanism of Dibutyl Phthalate of

Jimilihan Simayi, Bayinsang, Maimaitiming Nuermaimaiti, Sendaer Hailati, Mengyuan Han, Zulihuma Reheman, Ainiwaer Wumaier, Wenting Zhou

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

8 authors at 2 institutions in 1 country.

Jimilihan SimayiDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0002-8440-9684
BayinsangDepartment of Pharmacy, Urumqi Maternal and Child Health Care Hospital, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0003-2629-664X
Maimaitiming NuermaimaitiDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0003-3419-7027
Sendaer HailatiDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0001-5867-8744
Mengyuan HanDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0003-4145-1820
Zulihuma RehemanDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0001-7613-9330
Ainiwaer WumaierDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0002-8934-8163
Wenting ZhouDepartment of Pharmacology, Xinjiang Medical University, 830011 Urumqi, Xinjiang, China.ORCID https://orcid.org/0000-0003-2610-7634
Xinjiang Medical University · CNMaternal and Child Health Hospital of Xinjiang Uygur Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Methods: The components of OBL were compiled by literature search, and their active ingredients were screened by online database. The drug targets of OBL in the treatment of AD were predicted and analyzed using information derived from sources such as the SwissTargetPrediction tool. And through the network visual analysis function of Cytoscape software and protein-protein interaction analysis (PPI), the core targets of OBL treatment of AD are predicted. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were employed to analyze the related signaling pathways affected by OBL. Moreover, AutoDock software was used to assess the potential binding affinity between the core targets and the active compounds. Subsequently, Results: A total of 35 active compounds and 188 targets of OBL were screened, of which 43 common targets were related to AD. The active compounds of 35 OBLs induced 118 GO and 78 KEGG. The results of PPI and network topology parameter analysis show that targets such as MAPK1, GSK3B, NR3C2, ESR1, and EGFR are known as the core targets for the treatment of AD by OBL and are docked with the active ingredients of OBL. Molecular docking results suggest that diterbutyl phthalate (DBP) may be the main active component of OBL for the treatment of AD. Flow cytometry analysis results showed that apoptosis decreased with increasing DBP dose. In addition, DBP significantly decreased the levels of lactate dehydrogenase (LDH) and reactive oxygen species (ROS) in the supernatant of A Conclusions: Conclusively, our study suggests that DBP, the main active component of OBL, has potential in the prevention or treatment of AD.

Indexed as

Alzheimer DiseaseDrugs, Chinese HerbalOcimum basilicumDibutyl PhthalateGlycogen Synthase Kinase 3 betaMolecular Docking SimulationNetwork PharmacologyPhthalic AcidsProto-Oncogene Proteins c-aktDibutyl PhthalateDrugs, Chinese HerbalGlycogen Synthase Kinase 3 betaphthalic acidPhthalic AcidsProto-Oncogene Proteins c-akt

Identifiers

PMID36593772
PMCPMC9805396
OpenAlexW4312120193

What OpenQuestion holds

Textmetadata
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.