Tumor Paint: A Chlorotoxin:Cy5.5 Bioconjugate for Intraoperative Visualization of Cancer Foci
Bibliographic record
Abstract
Toward the goal of developing an optical imaging contrast agent that will enable surgeons to intraoperatively distinguish cancer foci from adjacent normal tissue, we developed a chlorotoxin:Cy5.5 (CTX:Cy5.5) bioconjugate that emits near-IR fluorescent signal. The probe delineates malignant glioma, medulloblastoma, prostate cancer, intestinal cancer, and sarcoma from adjacent non-neoplastic tissue in mouse models. Metastatic cancer foci as small as a few hundred cells were detected in lymph channels. Specific binding to cancer cells is facilitated by matrix metalloproteinase-2 (MMP-2) as evidenced by reduction of CTX:Cy5.5 binding in vitro and in vivo by a pharmacologic blocker of MMP-2 and induction of CTX:Cy5.5 binding in MCF-7 cells following transfection with a plasmid encoding MMP-2. Mouse studies revealed that CTX:Cy5.5 has favorable biodistribution and toxicity profiles. These studies show that CTX:Cy5.5 has the potential to fundamentally improve intraoperative detection and resection of malignancies.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Development of a chlorotoxin bioconjugate for intraoperative cancer visualization; the object is an imaging agent.
It develops an optical cancer-imaging agent, not a study of research.
Cancer imaging bioconjugate (tumor paint); translational oncology tool, not research-on-research.
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".