Evidence map›Paper›PMID 38872874›Full record

ArticleInternational journal of thermal sciences = Revue generale de thermique2021

Parametric Investigations of Magnetic Nanoparticles Hyperthermia in Ferrofluid using Finite Element Analysis.

Izaz Raouf, Jaehun Lee, Heung Soo Kim, Min-Ho Kim

Abstract read
In one paragraph

Article in International journal of thermal sciences = Revue generale de thermique, 2021. 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. 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

4 authors.

Izaz RaoufDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Republic of Korea.
Jaehun LeeDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Republic of Korea.
Heung Soo KimDepartment of Mechanical, Robotics and Energy Engineering, Dongguk University-Seoul, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Republic of Korea.
Min-Ho KimDepartment of Biological Sciences, Kent State University, Kent, OH 44242, USA.

Funding

Targeted magnetic nanoparticle hyperthermia for minimally invasive disruption of amyloid beta plaques towards the treatment of Alzheimer's diseaseR01NR015674 · NINR · KENT STATE UNIVERSITY · PI KIM, MIN HO · 2015 to 2019
$2.2M
NINR NIH HHS R01 NR015674
6 · The paper itself

Abstract

Recently, magnetic nanoparticles (MNPs) based hyperthermia therapy has gained much attention due to its therapeutic potential in biomedical applications. This necessitates the development of numerical models that can reliably predict the temporal and spatial changes of temperature during the therapy. The objective of this study is to develop a comprehensive numerical model for quantitatively estimating temperature distribution in the ferrofluid system. The reliability of the numerical model was validated by comparative analysis of temperature distribution between experimental measurements and numerical analysis based on finite element method. Our analysis showed that appropriate incorporation of the heat effects of electromagnetic energy dissipation as well as thermal radiation from the ferrofluid system to the surrounding in the modeling resulted in the estimation of temperature distribution that is in close agreement with the experimental results. In summary, our developed numerical model is useful to evaluate the thermal behavior of the ferrofluid system during the process of magnetic fluid hyperthermia.

Indexed as

Finite element methodInduction heatingMagnetic fluid hyperthermiaMagnetic nanoparticleSpecific loss powerThermal analysis

Identifiers

PMID38872874
PMCPMC11172412

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Registered trials

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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.