Localisation du ganglion sentinelle au moyen de nanoparticules fluorescentes émettant dans le proche infrarouge : Application au cancer du sein
Bibliographic record
Abstract
Sentinel lymph node (SLN) biopsy is a reliable technique for the diagnosis of metastases in breast cancer. However, the tracers used (blue dye and radiocolloid) are not optimal because they can cause allergic reactions and major costs in waste processing. Our strategy was to use near-infrared emitting nanoparticles for the mapping of SLN: indium-based Quantum Dots (QDs) and cyanine 7 embedded in silica nanoparticles (SiNP). In a murine model of mammary carcinoma, all SLN containing lymphatic metastases could be visualized with fluorescent indium-based QDs. The biodistribution study concluded that the major organs of retention were the injection point and lymph nodes whereas liver and spleen accumulated fewer QDs. The cytotoxicity tests demonstrated a weak in vitro toxicity of indium- compared to cadmium-based QDs. SiNP show several advantages over free fluorophore such as biocompatibility, better retention in the SLN and greatest photophysical properties. SLN could be mapped as soon as 5 minutes after SiNP injection. The in vivo toxicity in mice was followed during 3 months after injection and did not reveal any signs of general or hepatic toxicity. Both fluorescent nanoparticles are thus well adapted for the mapping of the SLN and could be a favourable substitute to the actually tracers
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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; both teacher heads agree on what is shown here.
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".