Open source software for quantification of cell migration, protrusions, and fluorescence intensities
Bibliographic record
Abstract
Cell migration is frequently accompanied by changes in cell morphology (morphodynamics) on a range of spatial and temporal scales. Despite recent advances in imaging techniques, the application of unbiased computational image analysis methods for morphodynamic quantification is rare. For example, manual analysis using kymographs is still commonplace, often caused by lack of access to user-friendly, automated tools. We now describe software designed for the automated quantification of cell migration and morphodynamics. Implemented as a plug-in for the open-source platform, ImageJ, ADAPT is capable of rapid, automated analysis of migration and membrane protrusions, together with associated fluorescently labeled proteins, across multiple cells. We demonstrate the ability of the software by quantifying variations in cell population migration rates on different extracellular matrices. We also show that ADAPT can detect and morphologically profile filopodia. Finally, we have used ADAPT to compile an unbiased description of a "typical" bleb formed at the plasma membrane and quantify the effect of Arp2/3 complex inhibition on bleb retraction.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.028 |
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".