Evidence map›Paper›PMID 21557390›Full record

ReviewStem cells (Dayton, Ohio)2011

Concise review: Mesenchymal stem cell tumor-homing: detection methods in disease model systems.

Michaela R Reagan, David L Kaplan

Abstract readReview
In one paragraph

Review in Stem cells (Dayton, Ohio), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 2 pooled it
–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

117 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Putting Hybrid Nanomaterials to Work for Biomedical Applications.Angewandte Chemie (International ed. in English) · 2024
    Review
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57 more citing papers are in PubMed but not listed here.

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

2 authors.

Michaela R ReaganDepartment of Biomedical Engineering, Tufts University, Medford, Massachusetts 02155, USA.
David L Kaplan

Funding

Translational Bioreactors - Engineering Complex TissuesP41EB002520 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI KAPLAN, DAVID L. · 2004 to 2018
$16.7M
NIBIB NIH HHS P41 EB002520
6 · The paper itself

Abstract

Despite the decline in U.S. cancer incidence and mortality rates, cancer remains the number one cause of death for people under the age of 85 and one in four people in the U.S. will die of cancer, mainly because of metastasis. Recently, interest in mesenchymal stem cell (MSC) tumor-homing has led to inquires into: (a) why MSCs home to tumors, (b) what the inherent protumor and antitumor consequences are, and (c) how to best capitalize on MSC tumor-homing for cell-based diagnostics and therapy. Here, these questions are reviewed and method for addressing them using animal models and tracking methodologies (or, synonymously, detection methodologies) are discussed. First, MSCs in a regenerative and tumor-homing context are reviewed, followed by MSC delivery and genetic labeling methods for tissue model systems. Finally, the use of the nonoptical methods, magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography, along with optical methods, fluorescence imaging and bioluminescent imaging, are reviewed related to tracking MSCs within disease model settings. The benefits and drawbacks of each detection method in animal models is reviewed along with the utility of each for therapeutic use.

Indexed as

Cell MovementAnimalsCell TrackingDiagnostic ImagingDisease Models, AnimalGenetic EngineeringHumansMesenchymal Stem CellsMesenchymal Stem Cell TransplantationNeoplasm MetastasisNeoplasmsTumor Microenvironment

Identifiers

PMID21557390
PMCPMC4581846

What OpenQuestion holds

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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.