The Zebrafish Embryo: A Powerful Model System for Investigating Matrix Remodeling
Bibliographic record
Abstract
Extracellular matrix (ECM) remodeling is a process that is crucial to the development of embryos, the growth and metastasis of tumors, and wound healing and homeostasis of tissues in adults. As such, it involves dozens of gene products that are regulated by mechanisms operating at transcriptional and multiple posttranslational levels. This complexity of regulation has made the development of a comprehensive understanding of the biology of ECM remodeling in vivo an unusually challenging task, yet such an understanding would be of profound value to our knowledge of and clinical approaches to the treatment of many cancers. The primary effectors of ECM remodeling are the matrix metalloproteinases (MMPs). Homologs of this gene family have been identified in every metazoan examined. We propose that the zebrafish embryo is an ideal system for the study of the regulation of MMP activity, and we present some progress we have made in the development of this organism as a platform for MMP research. We have identified 25 genes encoding MMPs in the zebrafish genome, and 5 genes encoding their endogenous inhibitors, the tissue inhibitors of MMPs. Based on a phylogenetic analysis, we have identified the most probable homologies of these sequences and found that there are two that are of equivocal identity. We have developed 17 antibodies specific to zebrafish MMPs and have begun characterizing the ontogeny of these molecules. Finally, we have developed two novel assays that allow the detection and characterization of active MMPs in vivo (differential in vivo zymography and activity-based protease profiling). In combination with the array of powerful biochemical, genomic, cell, and molecular biological techniques available to zebrafish researchers already, we feel that these new reagents and techniques make the zebrafish the best model system for the study of MMP regulation currently available.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".