Regulation of ATP utilization during metastatic cell migration by collagen architecture
Bibliographic record
Abstract
Cell migration in a three-dimensional matrix requires that cells either remodel the surrounding matrix fibers and/or squeeze between the fibers to move. Matrix degradation, matrix remodeling, and changes in cell shape each require cells to expend energy. While significant research has been performed to understand the cellular and molecular mechanisms guiding metastatic migration, less is known about cellular energy regulation and utilization during three-dimensional cancer cell migration. Here we introduce the use of the genetically encoded fluorescent biomarkers, PercevalHR and pHRed, to quantitatively assess ATP, ADP, and pH levels in MDA-MB-231 metastatic cancer cells as a function of the local collagen microenvironment. We find that the use of the probe is an effective tool for exploring the thermodynamics of cancer cell migration and invasion. Specifically, we find that the ATP:ADP ratio increases in cells in denser matrices, where migration is impaired, and it decreases in cells in aligned collagen matrices, where migration is facilitated. When migration is pharmacologically inhibited, the ATP:ADP ratio decreases. Together, our data indicate that matrix architecture alters cellular energetics and that intracellular ATP:ADP ratio is related to the ability of cancer cells to effectively migrate.
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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) | 0.001 | 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".