<i>In Vitro</i> Comparison of Sestamibi, Tetrofosmin, and Furifosmin as Agents for Functional Imaging of Multidrug Resistance in Tumors
Bibliographic record
Abstract
Sestamibi, tetrofosmin, and furifosmin are 99mTc-labeled myocardial perfusion imaging agents which have been shown to be substrates for P-glycoprotein (Pgp), the multidrug-resistance transporter which is overexpressed in some tumors. The three tracers were directly compared in vitro in the human breast cancer cell line MCF7-WT and two multidrug-resistant variants, MCF7-BC19 (MDR1 gene transfected) and MCF7-AdrR (doxorubicin selected). Tracer accumulation over the course of 60 minutes was determined. Dose-response curves were generated for two modulators of Pgp function, GG918 and PSC833. The general shape of accumulation curves for the three tracers in MCF7-WT cells was similar, with accumulation levels being sestamibi > tetrofosmin > furifosmin. Accumulation of sestamibi and furifosmin in MCF7-BC19 cells was reduced to 10% and 21% of MCF7-WT levels, respectively, but this accumulation deficit could be completely reversed by addition of 0.1 microM GG918 or 2 microM PSC833. Accumulation of sestamibi and tetrofosmin in MCF7-AdrR cells was 1.6% and 12% of MCF7-WT levels, respectively, and could only be enhanced to 30% and 45% of MCF7-WT levels by addition of GG918 or PSC833. In contrast, furifosmin showed similar levels of accumulation in MCF7-WT and MCF7-BC19 cells, slightly lower levels in MCF7-AdrR cells, and no consistent response to Pgp modulators. These results support the continued investigation of sestamibi and tetrofosmin as agents for functional imaging of multidrug resistance in human cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".