A New Pyrimidine-Specific Reporter Gene: A Mutated Human Deoxycytidine Kinase Suitable for PET During Treatment with Acycloguanosine-Based Cytotoxic Drugs
Bibliographic record
Abstract
UNLABELLED: In this article, we describe a series of new human-derived reporter genes based on human deoxycytidine kinase (dCK) suitable for clinical PET. METHODS: Native dCK and its mutant reporter genes were tested in vitro and in vivo for their phosphorylation of pyrimidine- and acycloguanosine-based radiotracers including 2'-deoxy-2'-fluoroarabinofuranosylcytosine, 2'-fluoro-2'-deoxyarabinofuranosyl-5-ethyluracil (FEAU), penciclovir, and 9-[4-fluoro-3-(hydroxymethyl)butyl]guanine (FHBG) and clinically applied antiviral and anticancer drugs. RESULTS: Cells transduced with dCK mutant reporter genes showed high in vitro and in vivo uptake of pyrimidine-based radiopharmaceuticals ((18)F-FEAU) comparable to that of herpes simplex virus type-1 thymidine kinase (HSV1-tk)-transduced cells. These mutants did not phosphorylate acycloguanosine-based radiotracers ((18)F-FHBG) or antiviral drugs (ganciclovir). Furthermore, the mutants displayed suicidal activation of clinically used pyrimidine-based prodrugs (cytarabine, gemcitabine). CONCLUSION: The mutants of human dCK can be used as pyrimidine-specific PET reporter genes for imaging with (18)F-FEAU during treatment with acycloguanosine-based antiviral drugs. Additionally, the prosuicidal activity of these reporters with pyrimidine-based analogs will allow for the safe elimination of transduced cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".