Evidence map›Paper›PMID 31382433›Full record

ArticleSensors (Basel, Switzerland)2019

Characterization and Relaxation Properties of a Series of Monodispersed Magnetic Nanoparticles.

Yapeng Zhang, Jingjing Cheng, Wenzhong Liu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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
–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

5 citing papers in PubMed.

  1. Contrast Agents for Enhanced Bioimaging: A Comprehensive Review.Chembiochem : a European journal of chemical biology · 2026
    Review
  2. Article
  3. Review
  4. Article
  5. Advances in Plasmonic Sensing at the NIR-A Review.Sensors (Basel, Switzerland) · 2021
    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

3 authors.

Yapeng ZhangSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China.
Jingjing ChengSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China. chengjj@hust.edu.cn.
Wenzhong LiuSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China. lwz7410@hust.edu.cn.

Funding

National Natural Science Foundation of China 61571199
6 · The paper itself

Abstract

Magnetic iron oxide nanoparticles are relatively advanced nanomaterials, and are widely used in biology, physics and medicine, especially as contrast agents for magnetic resonance imaging. Characterization of the properties of magnetic nanoparticles plays an important role in the application of magnetic particles. As a contrast agent, the relaxation rate directly affects image enhancement. We characterized a series of monodispersed magnetic nanoparticles using different methods and measured their relaxation rates using a 0.47 T low-field Nuclear Magnetic Resonance instrument. Generally speaking, the properties of magnetic nanoparticles are closely related to their particle sizes; however, neither longitudinal relaxation rate r 1 nor transverse relaxation rate r 2 changes monotonously with the particle size d . Therefore, size can affect the magnetism of magnetic nanoparticles, but it is not the only factor. Then, we defined the relaxation rates r i ' (

Indexed as

Contrast MediaDynamic Light ScatteringFerric CompoundsLinear ModelsMagnetic FieldsMagnetic Resonance SpectroscopyMagnetite NanoparticlesMicroscopy, Electron, TransmissionParticle SizeContrast MediaFerric Compoundsferric oxideMagnetite Nanoparticlescontrast agentLangevin modelmagnetic field inhomogeneitymagnetic nanoparticlesrelaxationrelaxation rate

Identifiers

PMID31382433
PMCPMC6696352

What OpenQuestion holds

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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.