Evidence map›Paper›PMID 32102332›Full record

ArticleInternational journal of molecular sciences2020

An Engineered Gene Nanovehicle Developed for Smart Gene Therapy to Selectively Inhibit Smooth Muscle Cells: An In Vitro Study.

Ling-Yi Cheng, Yu-Chi Wang, Ming-Hong Chen, Fu-I Tung, Kuan-Ming Chiu, Tse-Ying Liu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 2020. 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
0.2field-weighted citation impact, top 51% 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. 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

6 authors at 4 institutions in 1 country.

Ling-Yi ChengDepartment of Biomedical Engineering, National Yang-Ming University, Taipei 11221, Taiwan.
Yu-Chi WangDepartment of Biomedical Engineering, National Yang-Ming University, Taipei 11221, Taiwan.
Ming-Hong ChenDepartment of Neurosurgery, Taipei Municipal Wanfang Hospital, Taipei 11696, Taiwan.
Fu-I TungDepartment of Orthopaedic Surgery, Taipei City Hospital, Taipei 11146, Taiwan.
Kuan-Ming ChiuFar Eastern Memorial Hospital, Taipei 22060, Taiwan.
Tse-Ying LiuDepartment of Biomedical Engineering, National Yang-Ming University, Taipei 11221, Taiwan.
National Yang Ming Chiao Tung University · TWFar Eastern Memorial Hospital · TWTaipei Municipal YangMing Hospital · TWUniversity of Taipei · TW

Funding

Far Eastern Memorial Hospital 106DN21
6 · The paper itself

Abstract

In-stent restenosis is a serious concern for patients treated through the stenting procedure, although this can be solved using drug-eluting stents and/or drug-eluting balloon catheters. However, the chemical agents released from the drug-eluting layer for inhibiting smooth muscle cell (SMC) migration are inevitably associated with damage to vascular endothelial cell (ECs). The present in vitro study used a distinct strategy, in which a smart gene (phEGR1-PKCδ, an engineered plasmid consists of an SMC-specific promoter (human early growth response 1,

Indexed as

AnimalsAortaApoptosisCell SurvivalCoronary RestenosisDrug CarriersDrug-Eluting StentsEarly Growth Response Protein 1Endothelial CellsGenetic EngineeringGenetic TherapyMicroscopy, FluorescenceMuscle, Smooth, VascularMyocytes, Smooth MuscleNanostructuresProtein Kinase C-deltaDrug CarriersEarly Growth Response Protein 1EGR1 protein, humanProtein Kinase C-deltagene vehiclein-stent restenosissmooth muscle cellvascular endothelium cell

Identifiers

PMID32102332
PMCPMC7073206
OpenAlexW3006785658

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.