Elastic fiber macro‐assembly is a hierarchical, cell motion‐mediated process
Bibliographic record
Abstract
Elastic fibers are responsible for the extensibility and resilience of many vertebrate tissues, and improperly assembled elastic fibers are implicated in a number of human diseases. It was recently demonstrated that in vitro, cells first secrete tropoelastin into a punctate pattern of globules. To study the dynamics of macroassembly, that is, the assembly of the secreted tropoelastin globules into elastic fibers, we utilized long-term time-lapse immunofluorescence imaging and a tropoelastin p Timer fusion protein, which shifts its fluorescence spectrum over time. Pulse-chase immunolabeling of the fibroblast-like RFL-6 cells demonstrates that tropoelastin globules aggregate in a hierarchical manner, creating progressively larger fibrillar structures. By analyzing the correlation between cell and extracellular matrix movements, we show that both the aggregation process and shaping the aggregates into fibrillar form is coupled to cell motion. We also show that the motion of non-adjacent cells becomes more coordinated as the physical size of elastin-containing aggregates increases. Our data imply that the formation of elastic fibers involves the concerted action and motility of multiple cells.
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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) | 0.000 | 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) | 0.000 | 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".