Two-Photon Photodynamic Therapy Targeting Cancers with Low Carboxylesterase 2 Activity Guided by Ratiometric Fluorescence
Bibliographic record
Abstract
Human carboxylesterase 2 (hCES2) converts anticancer prodrugs, such as irinotecan, into their active metabolites via phase I drug metabolism. Owing to interindividual variability, hCES2 serves as a predictive marker of patient response to hCES2-activated prodrug-based therapy, whereby a low intratumoral hCES2 activity leads to therapeutic resistance. Despite the ability to identify nonresponders, effective treatments for resistant patients are needed. Clinically approved photodynamic therapy is an attractive alternative for irinotecan-resistant patients. Here, we describe the application of our hCES2-selective small-molecule ratiometric fluorescent chemosensor, Benz-AP, as a single theranostic agent given its discovered functionality as a photosensitizer. Benz-AP produces singlet oxygen and induces photocytotoxicity in cancer cells in a strong negative correlation with hCES2 activity. Two-photon excitation of Benz-AP produces fluorescence, singlet oxygen, and photocytotoxicity in tumor spheroids. Overall, Benz-AP serves as a novel theranostic agent with selective photocytotoxicity in hCES2-prodrug resistant cancer cells, making Benz-AP a promising agent for in vivo applications.
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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".