In vivo MRI of cancer cell fate at the single‐cell level in a mouse model of breast cancer metastasis to the brain
Bibliographic record
Abstract
Metastasis (the spread of cancer from a primary tumor to secondary organs) is responsible for most cancer deaths. The ability to follow the fate of a population of tumor cells over time in an experimental animal would provide a powerful new way to monitor the metastatic process. Here we describe a magnetic resonance imaging (MRI) technique that permits the tracking of breast cancer cells in a mouse model of brain metastasis at the single-cell level. Cancer cells that were injected into the left ventricle of the mouse heart and then delivered to the brain were detectable on MR images. This allowed the visualization of the initial delivery and distribution of cells, as well as the growth of tumors from a subset of these cells within the whole intact brain volume. The ability to follow the metastatic process from the single-cell stage through metastatic growth, and to quantify and monitor the presence of solitary undivided cells will facilitate progress in understanding the mechanisms of brain metastasis and tumor dormancy, and the development of therapeutics to treat this disease.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".