Evidence map›Paper›PMID 22993215›Full record

ArticleRadiology2012

Science to practice: genetic engineering meets cell tracking--a promising approach for cell-based therapies?

Fabian Kiessling

Abstract readComment
PubMed Publisher
In one paragraph

Article in Radiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 86% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Fabian KiesslingDepartment of Experimental Molecular Imaging University Clinics, RWTH Aachen University Pauwelsstrasse 20, 52074 Aachen, Germany. fkiessling@ukaachen.de
RWTH Aachen University · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell-based therapies are gaining increasing importance and have been evaluated in many settings, including cancer, Parkinson disease, myocardial repair, stroke, and diabetes. In this context, it is of major importance that the cells are implanted into an optimal tissue environment and, correspondingly, that they reach the diseased region. Intravenous cell injection often is the route of choice, particularly if the cells are expected to circulate in the blood for longer periods of time and are able to actively migrate to the diseased tissue. Unfortunately, often only a small percentage of intravenously injected cells reach the target area. Higher accumulation can be achieved if the cells are injected into an artery that feeds the diseased area. However, in this case, fast blood velocities and substantial sheer stress make it difficult for the cells to adhere. In the study by Gorelik and colleagues (1), genetic engineering was used to overcome this limitation. Glial precursor cells were transiently transfected with very late antigen-4 (VLA-4) binding to vascular cell adhesion molecule-1 (VCAM-1), which is upregulated in inflamed endothelial cells. After labeling these cells with superparamagnetic iron oxide (SPIO) containing rhodamine, significantly increased binding to inflamed brain endothelial cells was shown and their homogeneous distribution over the inflamed brain tissue was convincingly demonstrated with magnetic resonance (MR) imaging and histologic examination. The authors concluded that transient transfection of SPIO-labeled cells with VLA-4 in combination with their arterial injection and the use of MR imaging monitoring may be an elegant way to increase the efficacy of cell-based treatments of inflammatory brain diseases.

Indexed as

AnimalsBrainCell TrackingHumansIntegrin alpha4beta1Magnetic Resonance ImagingNeurogliaReceptors, Very Late AntigenIntegrin alpha4beta1Receptors, Very Late Antigen

Identifiers

PMID22993215
OpenAlexW2128776003

What OpenQuestion holds

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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.