Evidence map›Paper›PMID 27314396›Full record

ArticleBiosensors2016

Optimal Magnetic Field for Crossing Super-Para-Magnetic Nanoparticles through the Brain Blood Barrier: A Computational Approach.

Maysam Z Pedram, Amir Shamloo, Aria Alasty, Ebrahim Ghafar-Zadeh

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

15 citing papers in PubMed, 52 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Maysam Z PedramDepartment of Mechanical Engineering, Sharif University of Technology, Tehran, PO Box: 11365-11155, Iran. maysam.pedram@gmail.com.
Amir ShamlooDepartment of Mechanical Engineering, Sharif University of Technology, Tehran, PO Box: 11365-11155, Iran. shamloo@sharif.edu.
Aria AlastyDepartment of Mechanical Engineering, Sharif University of Technology, Tehran, PO Box: 11365-11155, Iran. aalasti@sharif.edu.
Ebrahim Ghafar-ZadehDepartment of Electrical Engineering, York University, Toronto, ON M3J1P3, Canada. egz@cse.yorku.ca.
Sharif University of Technology · IRYork University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper scrutinizes the magnetic field effect to deliver the superparamagnetic nanoparticles (SPMNs) through the Blood Brain Barrier (BBB). Herein we study the interaction between the nanoparticle (NP) and BBB membrane using Molecular Dynamic (MD) techniques. The MD model is used to enhance our understanding of the dynamic behavior of SPMNs crossing the endothelial cells in the presence of a gradient magnetic field. Actuation of NPs under weak magnetic field offers the great advantage of a non-invasive drug delivery without the risk of causing injury to the brain. Furthermore, a weak magnetic portable stimulator can be developed using low complexity prototyping techniques. Based on MD simulation results in this paper, SPMNs can cross the cell membrane while experiencing very weak mechanical forces in the range of pN. This study also derives guidelines for the design of the SPMNs dedicated to crossing the BBB using external magnetic fields.

Indexed as

Blood-Brain BarrierMagnetic FieldsMagnetite NanoparticlesAlgorithmsDrug Delivery SystemsModels, TheoreticalMolecular Dynamics SimulationPermeabilityTranscytosisMagnetite NanoparticlesBlood Brain Barrierforce steeringMolecular Dynamics simulationsuperparamagnetic nanoparticles

Identifiers

PMID27314396
PMCPMC4931485
OpenAlexW2435986804

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.