Delayed Progression of Lung Metastases Following Delivery of a Prodrug-activating Enzyme
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Chemotherapy is an effective option to treat recurrent or metastatic cancer but its debilitating side-effects limit the dose and time of exposure. Prodrugs that can be activated locally by an activating enzyme can minimize collateral damage from chemotherapy. We previously demonstrated the efficacy of a poly-L-lysine-based theranostic nanoplex containing bacterial cytosine deaminase (bCD) that locally converted 5-fluorocytosine (5-FC) to the chemotherapeutic agent 5-fluorouracil in MDA-MB-231 primary tumor xenografts. MATERIALS AND METHODS: Here we used a more effective variant of bCD to target metastatic red fluorescence protein expressing MDA-MB-435 cells in the lungs. We used an intravenous injection of tumor cells and monitored tumor growth in the lungs for 5 weeks by which time metastatic nodules were detected with optical imaging. The animals were then treated with the bCD-nanoplex and 5-FC. RESULTS: We observed a significant decrease in metastatic burden with a single dose of the enzyme-nanoplex and two consecutive prodrug injections. CONCLUSION: These results are a first step towards the longitudinal evaluation of such a strategy with multiple doses. Additionally, the enzyme can be directly coupled to imaging reporters to time prodrug administration for the detection and treatment of aggressive metastatic cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it