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Record W2612867295 · doi:10.1016/j.omtm.2017.05.002

Cell Therapy in Myology: Dynamics of Muscle Precursor Cell Death after Intramuscular Administration in Non-human Primates

2017· article· en· W2612867295 on OpenAlexafffund
Daniel Skuk, Jacques P. Tremblay

Bibliographic record

VenueMolecular Therapy — Methods & Clinical Development · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsCentre hospitalier universitaire de Québec
FundersCanadian Institutes of Health ResearchUniversité Laval
KeywordsImmunosuppressionTransplantationMyocyteProgrammed cell deathGenetic enhancementIn vitroBiologyCell therapyCellReporter geneAndrologyMedicinePathologyImmunologyInternal medicineGeneEndocrinologyBiochemistryGene expression

Abstract

fetched live from OpenAlex

Cell therapy could be useful for the treatment of myopathies. A problem observed in mice, with different results and interpretations, is a significant death among the transplanted cells. We analyzed this problem in non-human primates, the animal model more similar to humans. Autologous or allogeneic myoblasts (with or without a reporter gene) were proliferated in vitro, labeled with [ 14 C]thymidine, and intramuscularly injected in macaques. Some monkeys were immunosuppressed for long-term follow-up. Cell-grafted regions were biopsied at different intervals and analyzed by radiolabel quantification and histology. Most radiolabel was lost during the first week after injection, regardless of whether the cells were allogeneic or autologous, the culture conditions, and the use or not of immunosuppression. There was no significant difference between 1 hr and 1 day post-transplantation, a significant decrease between days 1 and 3 (45% to 83%), a significant decrease between days 3 and 7 (80% to 92%), and no significant differences between 7 days and 3 weeks. Our results confirmed in non-human primates a progressive and significant death of the grafted myoblasts during the first week after administration, relatively similar to some observations in mice but with different kinetics.

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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.409
Teacher spread0.376 · 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".

Quick stats

Citations17
Published2017
Admission routes2
Has abstractyes

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