Evidence map›Paper›PMID 36045712›Full record

ArticleOpen life sciences2022

Preparation and evaluation of LA-PEG-SPION, a targeted MRI contrast agent for liver cancer.

Lei Xia, Xiaowei Song, Guanghai Yan, Jishan Quan, Guangyu Jin

Open access · goldAbstract read
In one paragraph

Article in Open life sciences, 2022. 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 50% 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, 4 citations in OpenAlex.

  1. MRI Contrast Agents in Glycobiology.Molecules (Basel, Switzerland) · 2022
    Review
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

5 authors at 2 institutions in 1 country.

Lei XiaDepartment of Radiology, Affiliated Hospital of Yanbian University, No. 1327, Juzi Street, Yanji 133000, Jilin Province, P.R. China.
Xiaowei SongDepartment of Radiology, Affiliated Hospital of Yanbian University, No. 1327, Juzi Street, Yanji 133000, Jilin Province, P.R. China.
Guanghai YanDepartment of Anatomy, Basic Medical College, Yanbian University, Yanji 133000, Jilin Province, P.R. China.
Jishan QuanDepartment of Pharmaceutics, College of Pharmacy, Yanbian University, No. 977, Gongyuan Street, Yanji 133000, Jilin Province, P.R. China.
Guangyu JinDepartment of Radiology, Affiliated Hospital of Yanbian University, No. 1327, Juzi Street, Yanji 133000, Jilin Province, P.R. China.
Yanbian University Hospital · CNYanbian University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to synthesize a magnetic resonance imaging (MRI) contrast agent that can specifically target the asialoglycoprotein receptor of liver cancer cells and evaluate its ability as a targeted MRI contrast agent. Lactobionic acid (LA) and polyethylene glycol (PEG) were used to modify superparamagnetic iron oxide nanoparticles (SPION) to obtain LA-PEG-SPION. LA-PEG-SPION was uniformly spherical under the electron microscope, with regular morphology and good dispersion. The particle size of LA-PEG-SPION was about 30 ± 4.5 nm, and its surface potential was about 31 ± 1.5 mV. LA-PEG-SPION had no toxicity or low toxicity to HepG2 cells and HeLa cells, even at 400 μg/mL. The uptake of LA-PEG-SPION by HepG2 cells was higher than that of SPION, with increased blue-stained particles. The fluorescent labeling rate of HepG2 cells reached 68.8%, which was higher than that of the control group.

Indexed as

asialoglycoprotein receptorliver cancerMRI contrast agentsuperparamagnetic iron oxide nanoparticles

Identifiers

PMID36045712
PMCPMC9380906
OpenAlexW4292103365

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.