Mini-MEndR: a miniaturized 96-well predictive assay to evaluate muscle stem cell-mediated repair
Bibliographic record
Abstract
Abstract Background Functional evaluation of molecules that are predicted to promote stem cell mediated endogenous repair often requires in vivo transplant studies that are low throughput and hinder the rate of discovery. To offer greater throughput for functional validation studies, we miniaturized, simplified and expanded the functionality of a previously developed muscle endogenous repair (MEndR) in vitro assay that was shown to capture significant events of in vivo muscle endogenous repair. Methods The mini-MEndR assay consists of miniaturized cellulose scaffolds designed to fit in 96-well plates, the pores of which are infiltrated with human myoblasts encapsulated in a fibrin-based hydrogel to form engineered skeletal muscle tissues. Pre-adsorbing thrombin to the cellulose scaffolds facilitates in situ tissue polymerization, a critical modification that enables new users to rapidly acquire assay expertise. Following the generation of the 3D myotube template, muscle stem cells (MuSCs), enriched from digested mouse skeletal muscle tissue using an improved magnetic-activated cell sorting protocol, are engrafted within the engineered template. Murine MuSCs are fluorescently labeled, enabling co-evaluation of human and mouse Pax7+ cell responses to drug treatments. A regenerative milieu is introduced by injuring the muscle tissue with a myotoxin to initiate endogenous repair “in a dish”. Phenotypic data is collected at endpoints with a high-content imaging system and is analyzed using ImageJ-based image analysis pipelines. Results The miniaturized format and modified manufacturing protocol cuts reagent costs in half and hands-on seeding time ~ threefold, while the image analysis pipelines save 40 h of labour. By evaluating multiple commercially available human primary myoblast lines in 2D and 3D culture, we establish quality assurance metrics for cell line selection that standardizes myotube template quality. In vivo outcomes (enhanced muscle production and Pax7+ cell expansion) to a known modulator of MuSC mediated repair (p38/β MAPK inhibition) are recapitulated in the miniaturized culture assay, but only in the presence of stem cells and the regenerative milieu. Discussion The miniaturized predictive assay offers a simple, scaled platform to co-investigate human and mouse skeletal muscle endogenous repair molecular modulators, and thus is a promising strategy to accelerate the muscle endogenous repair discovery pipeline.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".