Evidence map›Paper›PMID 30042956›Full record

ArticleTomography (Ann Arbor, Mich.)2016

Pre-Labeling of Immune Cells in Normal Bone Marrow and Spleen for Subsequent Cell Tracking by MRI.

Gabrielle M Siegers, Shruti Krishnamoorthy, Laura E Gonzalez-Lara, Catherine McFadden, Yuhua Chen, Paula J Foster

Open access · goldAbstract read
In one paragraph

Article in Tomography (Ann Arbor, Mich.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Tracking Cell Transplants in Femoral Osteonecrosis with Magnetic Resonance Imaging: A Proof-of-Concept Study in Patients.Clinical cancer research : an official journal of the American Association for Cancer Research · 2018
    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

6 authors at 2 institutions in 1 country.

Gabrielle M SiegersImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Shruti KrishnamoorthyImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Laura E Gonzalez-LaraImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Catherine McFaddenImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Yuhua ChenImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Paula J FosterImaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; and.
Robarts Clinical Trials · CAWestern University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Iron particles are intravenously (IV) administered to label cells in vivo during magnetic resonance imaging. This technique has been extensively used to monitor immune cells in the context of inflammatory diseases. Here, we have investigated whether resting immune cells can be labeled in vivo in healthy mice before disease onset or injury, thus allowing visualization of critical early cellular events. Using 1.5 T magnetic resonance imaging, we were able to detect signal loss in bone marrow, liver, and spleen as early as 1 hour after the IV injection of superparamagnetic iron oxide nanoparticles (Feridex; 80 to 120 nm in diameter) or larger micron-sized iron oxide particles (Bangs; 0.9 μm in diameter). Results were confirmed via histology. Further, flow cytometric analysis confirmed the presence of iron-labeled CD19

Indexed as

inflammationironmacrophagemiceMRI

Identifiers

PMID30042956
PMCPMC6024446
OpenAlexW2582496087

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.