Imaging the Impact of Chemically Inducible Proteins on Cellular Dynamics In Vivo
Bibliographic record
Abstract
The analysis of dynamic events in the tumor microenvironment during cancer progression is limited by the complexity of current in vivo imaging models. This is coupled with an inability to rapidly modulate and visualize protein activity in real time and to understand the consequence of these perturbations in vivo. We developed an intravital imaging approach that allows the rapid induction and subsequent depletion of target protein levels within human cancer xenografts while assessing the impact on cell behavior and morphology in real time. A conditionally stabilized fluorescent E-cadherin chimera was expressed in metastatic breast cancer cells, and the impact of E-cadherin induction and depletion was visualized using real-time confocal microscopy in a xenograft avian embryo model. We demonstrate the assessment of protein localization, cell morphology and migration in cells undergoing epithelial-mesenchymal and mesenchymal-epithelial transitions in breast tumors. This technique allows for precise control over protein activity in vivo while permitting the temporal analysis of dynamic biophysical parameters.
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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 | 0.001 |
| 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".