Evidence map›Paper›PMID 38304342›Full record

ArticleMaterials today. Bio2024

Biocompatible and bioactivable terpolymer-lipid-MnO

Tin-Yo C Yen, Azhar Z Abbasi, Chungsheng He, Ho-Yin Lip, Elliya Park, Mohammad A Amini, Hibret A Adissu, Warren Foltz, Andrew M Rauth, Jeffrey Henderson and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials today. Bio, 2024. 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
–field-weighted citation impact
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.

  1. Review
  2. Article
  3. 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

11 authors.

Tin-Yo C YenLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Azhar Z AbbasiLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Chungsheng HeLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Ho-Yin LipLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Elliya ParkLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Mohammad A AminiLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.
Hibret A Adissu218 Johnson Meadow St, Gaithersburg, MD, 20878, USA.
Warren FoltzSTTARR Innovation Centre, Department of Radiation Oncology, Princess Margaret Hospital, Toronto, Ontario, M5G 2M9, Canada.
Andrew M RauthDepartments of Medical Biophysics and Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.
Jeffrey HendersonDepartments of Medical Biophysics and Radiation Oncology, University of Toronto, Toronto, Ontario, Canada.
Xiao Yu WuLeslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early and precise detection of solid tumor cancers is critical for improving therapeutic outcomes. In this regard, magnetic resonance imaging (MRI) has become a useful tool for tumor diagnosis and image-guided therapy. However, its effectiveness is limited by the shortcomings of clinically available gadolinium-based contrast agents (GBCAs), i.e. poor tumor penetration and retention, and safety concerns. Thus, we have developed a novel nanoparticulate contrast agent using a biocompatible terpolymer and lipids to encapsulate manganese dioxide nanoparticles (TPL-MDNP). The TPL-MDNP accumulated in tumor tissue and produced paramagnetic Mn

Indexed as

BiocompatibilityBiodistribution and kineticsManganese dioxide nanoparticlesMRI contract agentTumor imaging

Identifiers

PMID38304342
PMCPMC10832465

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.