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44: Successful Transplantation of Human Muscle Precursor Cells in Nonhuman Primates Using Tacrolimus Immunosuprpression: A New Model for the Preclinical Test of Other Potentially Myogenic Human Cells

2019· article· en· W2970827636 on OpenAlexaffabout
Daniel Skuk, Jacques P. Tremblay

Bibliographic record

VenueTransplantation · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsTacrolimusTransplantationBiologyPathologyH&E stainMonoclonal antibodyMedicineImmunologyAntibodyImmunohistochemistryInternal medicine

Abstract

fetched live from OpenAlex

Background Different cells isolated from human tissues were proposed for cell transplantation in the skeletal muscle as a treatment of myopathies, essentially muscular dystrophies. However, the myogenic properties of most of these cells were found only after xenotransplantation in immunodeficient mice. Given that cell transplantation protocols developed in nonhuman primates (NHPs) were better extrapolated to humans than those that were not verified in this model, and considering that NHPs are crucial in preclinical transplantation research, we wanted to test the feasibility of xenotransplant human myogenic cells in NHP muscles. Methods Human CD56+ muscle precursor cells (MPCs) were transduced with the LacZ gene using a replication defective retroviral vector. They were injected into muscle regions of 1 cm3 (around 25 x 106 viable cells per site) in four cynomolgus macaques immunosuppressed with oral tacrolimus (Advagraf) and dexamethasone. Allogeneic LacZ-labeled MPCs were transplanted similarly in other muscles as a positive control for cell engraftment. Cell-grafted regions were sampled 1 month later and analyzed by histology in cryostat serial sections using ß-galactosidase (ß-Gal) histochemical detection, hematoxylin and eosin stain, and CD8 immunodetection. Blood was taken before transplantation and before muscle sampling to detect antibodies against the grafted cells. Tacrolimus blood levels were quantified by liquid chromatography tandem mass spectrometry. Results Tacrolimus blood levels and Advagraf doses in the monkeys of the study are shown in figure 1.{{AbstractFigure.1}} In monkeys #1 and #2 we targeted tacrolimus blood levels over 40 µg/L, while in monkeys #3 and #4 we targeted levels closer to those used in humans (around 20 µg/L). Abundant ß-Gal+ myofibers were found in all regions grafted with human MPCs (an average of around 25/mm2) distributed in bands aligned according to the injection trajectories (figure 2, red arrows indicate the original sense of the cell injections). The histological analyzes showed absence of specific cellular immune responses in three monkeys and minimal focal lymphocytic infiltrates in the monkey that had the lowest tacrolimus blood levels. Similar patterns of ß-Gal+ myofibers were observed in all regions grafted with cynomolgus MPCs (figure 2), in the absence of specific immune responses. Anti-donor antibodies were not detected in the sera. Conclusions We demonstrated that human MPCs can form hybrid myofibers in NHP muscles and that a conventional tacrolimus-based immunosuppression is sufficient to control rejection in this case. This opens the door to NHP studies with other human cells in which myogenic properties were found by xenotransplantation in immunodeficient mice, validating the myogenicity of these cells in a more appropriate model than mice for clinical translation and investigating the administration parameters necessary in humans. This work was supported by a grant of the Jesse’s Journey Foundation for Gene and Cell Therapy of Canada to D.S. and a grant of the Canadian Institutes of Health Research to J.P.T.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.304
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes2
Has abstractyes

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