<i>Ex Vivo</i> Detection of Circulating Tumor Cells from Whole Blood by Direct Nanoparticle Visualization
Bibliographic record
Abstract
The detection of circulating tumor cells (CTCs) from blood samples can predict prognosis, response to systemic chemotherapy, and metastatic spread of carcinoma. Therefore, approaches for CTC identification is an important aspect of current cancer research. Here, a method for the direct visualization of nanoparticle-coated CTCs under dark field illumination is presented. A metastatic breast cancer cell line (4T1) was transduced with a non-native target protein (Thy1.1). Positive 4T1-Thy1.1 cells incubated with antibody-coated metallic nanoshells appeared overly bright at low magnification, allowing a quick screening of samples and easy visual detection of even single isolated CTCs. The use of a nontransduced cell line as control creates the ideal scenario to evaluate nonspecific binding. A murine metastatic tumor model with the 4T1-Thy1.1 cell line was also implemented. Blood was drawn from mice over the course of one month, and CTCs were successfully detected in all positive subjects. This work validates the use of metallic nanoshells as labels for direct visualization of CTCs while providing guidelines to a systematic development of nanotechnology-based detection systems for CTCs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".