Inducible expression of photoacoustic reporter gene tyrosinase in cells using a single plasmid
Bibliographic record
Abstract
We have previously demonstrated that tyrosinase is a reporter gene for photoacoustic imaging since tyrosinase is the rate-limiting step in the synthesis of melanin, a pigment capable of producing strong photoacoustic signals. We previously created a cell line capable of inducible tyrosinase expression (important due to toxicity of melanin) by stably transfecting tyrosinase in MCF-7 Tet-OnR cell line (Clontech) which expresses a doxycycline-controlled transactivator. Unfortunately, Clontech provides few Tet-On Advanced cell lines making it difficult to have inducible tyrosinase expression in cell lines not provided by Clontech. In order to simplify the creation of cell lines with inducible expression of tyrosinase, we created a single plasmid that encodes both the transactivator as well as tyrosinase. PCR was used to amplify both the transactivator and tyrosinase from the Tet-OnR Advanced and pTRE-Tight-TYR plasmids, respectively. Both PCR products were cloned into the pEGFP-N1 plasmid and the newly created plasmid was transfected into ZR-75-1, MCF-7, and MIA PaCa-1 cells using lipofectamine. After several days, brown melanin was only observed in cells incubated with doxycycline, suggesting that the newly created single plasmid allowed inducible tyrosinase expression in many different cells lines.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".