Single cell dynamics of embryonic muscle progenitor cells in zebrafish
Bibliographic record
Abstract
ABSTRACT Muscle stem cells hold a great therapeutic potential in regenerating damaged muscles. However, the in vivo behavior of muscle stem cells during muscle growth and regeneration is still poorly understood. Using zebrafish as a model, we describe the in vivo dynamics and function of dermomyotome cells, a population of embryonic muscle progenitor cells. Dermomyotome cells are located in a superficial layer external to muscle fibers and express many extracellular matrix (ECM) genes including col1a2 . Utilizing a new col1a2 transgenic line, we show that dermomyotome cells display a ramified morphology with dynamic cellular processes. Cell lineage tracing demonstrates that col1a2 + dermomyotome cells contribute to normal muscle growth as well as muscle injury repair. Combination of live imaging and single cell clonal analysis reveals a highly-choreographed process of muscle regeneration. Activated dermomyotome cells change from the quiescent ramified morphology to a polarized and elongated morphology and generate daughter cells that fuse with existing muscle fibers. Ablation of the dermomyotome severely compromises muscle injury repair. Our work provides a dynamic view of embryonic muscle progenitor cells during zebrafish muscle regeneration. Summary statement Live imaging and single cell clonal analysis reveal dynamic behaviors of zebrafish embryonic muscle progenitor cells in quiescence and activation.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".