ReviewBone marrow transplantation2020
Beyond chimerism analysis: methods for tracking a new generation of cell-based medicines.
Review in Bone marrow transplantation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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.
Who cites it
13 citing papers in PubMed.
- Article
- Chimerism practices across Canadian transplant centres: review of current standards and variations.Frontiers in transplantation · 2026Review
- Can novel methods replace the gold standard chimerism method after allogeneic hematopoietic stem cell transplantation?Annals of hematology · 2024Review
- Transitioning single-cell genomics into the clinic.Nature reviews. Genetics · 2023Review
- Potency Assays: The 'Bugaboo' of Stem Cell Therapy.Advances in experimental medicine and biology · 2023Article
- New methods for the quantification of mixed chimerism in transplantation.Frontiers in immunology · 2023Article
- Illustrative Potency Assay Examples from Approved Therapies.Advances in experimental medicine and biology · 2023Article
- Evaluation of a quantitative PCR-based method for chimerism analysis of Japanese donor/recipient pairs.Scientific reports · 2022Article
- Utility of assessing CD3HLA · 2022Article
- Allogeneic mesenchymal stromal cells for cartilage regeneration: A review of in vitro evaluation, clinical experience, and translational opportunities.Stem cells translational medicine · 2021Review
- Wharton's Jelly Mesenchymal Stromal Cells and Derived Extracellular Vesicles as Post-Myocardial Infarction Therapeutic Toolkit: An Experienced View.Pharmaceutics · 2021Review
- Chimerism Monitoring Techniques after Hematopoietic Stem Cell Transplantation: An Overview of the Last 15 Years of Innovations.Diagnostics (Basel, Switzerland) · 2021Review
- Densitometry of STR-PAGE for donor chimerism in acute leukemia's: A simple method for routine use.Pakistan journal of medical sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The analysis of chimerism is crucial to determine the status of patients receiving hematopoietic stem cell transplantation. The variety of relevant techniques available today range from those that analyse nucleic acids (i.e. polymerase chain reaction based, next generation sequencing) and cellular phenotype (i.e. flow cytometry) to sophisticated imaging (particularly multimodal imaging using labelling agents). However, current developments of advanced therapies bring chimerism studies into a new dimension in which methods for detection of donor cells in the patient need to adapt to a wider range of cell- and gene-based medicines, routes of administration, target organs and pathologies. Herein we describe and analyze the toolkit of suitable labelling and detection methodologies with actual examples along with a discussion on challenges ahead and potential solutions. Remarkably, existing methods commonly used in chimerism analysis are suitable for use with new cell- and gene-based medicines. Indeed, new developments may facilitate the evolution and combination of such methodologies to the use of non-invasive and highly informative approaches.
Indexed as
Identifiers
32024991What OpenQuestion holds
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.