ArticleJournal of visualized experiments : JoVE2012
Multimodal imaging of stem cell implantation in the central nervous system of mice.
Article in Journal of visualized experiments : JoVE, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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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.
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Who cites it
4 citing papers in PubMed, 11 citations in OpenAlex.
- Targeted intracerebral delivery of the anti-inflammatory cytokine IL13 promotes alternative activation of both microglia and macrophages after stroke.Journal of neuroinflammation · 2018Article
- Intracerebral transplantation of interleukin 13-producing mesenchymal stem cells limits microgliosis, oligodendrocyte loss and demyelination in the cuprizone mouse model.Journal of neuroinflammation · 2016Article
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Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the past decade, stem cell transplantation has gained increasing interest as primary or secondary therapeutic modality for a variety of diseases, both in preclinical and clinical studies. However, to date results regarding functional outcome and/or tissue regeneration following stem cell transplantation are quite diverse. Generally, a clinical benefit is observed without profound understanding of the underlying mechanism(s). Therefore, multiple efforts have led to the development of different molecular imaging modalities to monitor stem cell grafting with the ultimate aim to accurately evaluate survival, fate and physiology of grafted stem cells and/or their micro-environment. Changes observed in one or more parameters determined by molecular imaging might be related to the observed clinical effect. In this context, our studies focus on the combined use of bioluminescence imaging (BLI), magnetic resonance imaging (MRI) and histological analysis to evaluate stem cell grafting. BLI is commonly used to non-invasively perform cell tracking and monitor cell survival in time following transplantation, based on a biochemical reaction where cells expressing the Luciferase-reporter gene are able to emit light following interaction with its substrate (e.g. D-luciferin). MRI on the other hand is a non-invasive technique which is clinically applicable and can be used to precisely locate cellular grafts with very high resolution, although its sensitivity highly depends on the contrast generated after cell labeling with an MRI contrast agent. Finally, post-mortem histological analysis is the method of choice to validate research results obtained with non-invasive techniques with highest resolution and sensitivity. Moreover end-point histological analysis allows us to perform detailed phenotypic analysis of grafted cells and/or the surrounding tissue, based on the use of fluorescent reporter proteins and/or direct cell labeling with specific antibodies. In summary, we here visually demonstrate the complementarities of BLI, MRI and histology to unravel different stem cell- and/or environment-associated characteristics following stem cell grafting in the CNS of mice. As an example, bone marrow-derived stromal cells, genetically engineered to express the enhanced Green Fluorescent Protein (eGFP) and firefly Luciferase (fLuc), and labeled with blue fluorescent micron-sized iron oxide particles (MPIOs), will be grafted in the CNS of immune-competent mice and outcome will be monitored by BLI, MRI and histology (Figure 1).
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Registered trials
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.