Evidence map›Paper›PMID 27375077›Full record

ReviewEuropean journal of pharmacology2016

Imaging technologies for monitoring the safety, efficacy and mechanisms of action of cell-based regenerative medicine therapies in models of kidney disease.

Jack Sharkey, Lauren Scarfe, Ilaria Santeramo, Marta Garcia-Finana, Brian K Park, Harish Poptani, Bettina Wilm, Arthur Taylor, Patricia Murray

Open access · hybridAbstract readReview
In one paragraph

Review in European journal of pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.1field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Nanoscale advances · 2019
    Article
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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

9 authors at 1 institution in 1 country.

Jack SharkeyDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK.
Lauren ScarfeDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK.
Ilaria SanteramoDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK.
Marta Garcia-FinanaDepartment of Biostatistics, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK.
Brian K ParkDepartment of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK.
Harish PoptaniDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK.
Bettina WilmDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK.
Arthur TaylorDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK.
Patricia MurrayDepartment of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool L69 3GE, UK; Centre for Preclinical Imaging, University of Liverpool, Liverpool L69 3GE, UK. Electronic address: p.a.murray@liv.ac.uk.
University of Liverpool · GB

Funding

Medical Research Council MR/K026739/1Medical Research Council MR/L012707/1
6 · The paper itself

Abstract

The incidence of end stage kidney disease is rising annually and it is now a global public health problem. Current treatment options are dialysis or renal transplantation, which apart from their significant drawbacks in terms of increased morbidity and mortality, are placing an increasing economic burden on society. Cell-based Regenerative Medicine Therapies (RMTs) have shown great promise in rodent models of kidney disease, but clinical translation is hampered due to the lack of adequate safety and efficacy data. Furthermore, the mechanisms whereby the cell-based RMTs ameliorate injury are ill-defined. For instance, it is not always clear if the cells directly replace damaged renal tissue, or whether paracrine effects are more important. Knowledge of the mechanisms responsible for the beneficial effects of cell therapies is crucial because it could lead to the development of safer and more effective RMTs in the future. To address these questions, novel in vivo imaging strategies are needed to monitor the biodistribution of cell-based RMTs and evaluate their beneficial effects on host tissues and organs, as well as any potential adverse effects. In this review we will discuss how state-of-the-art imaging modalities, including bioluminescence, magnetic resonance, nuclear imaging, ultrasound and an emerging imaging technology called multispectral optoacoustic tomography, can be used in combination with various imaging probes to track the fate and biodistribution of cell-based RMTs in rodent models of kidney disease, and evaluate their effect on renal function.

Indexed as

SafetyAnimalsCell- and Tissue-Based TherapyHumansKidneyKidney DiseasesMolecular ImagingRegenerative MedicineBiodistributionCell trackingKidney functionMultispectral optoacoustic tomographyPreclinical imagingStem cells

Identifiers

PMID27375077
PMCPMC5063540
OpenAlexW2462478200

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.