Positron-Emission Tomography Imaging of the TSPO with [ <sup>18</sup> F]FEPPA in a Preclinical Breast Cancer Model
Bibliographic record
Abstract
The present study aims to image the 18-kDa translocator protein (TSPO; formerly known as the peripheral benzodiazepine receptor) in a preclinical human breast cancer (BC) xenograft mouse model with positron-emission tomography (PET). An automated radiosynthesis of [(18)F]-N-(2-(2-fluoroethoxy)benzyl)-N-(4-phenoxypyridin-3-yl)acetamide ([(18)F]FEPPA) was validated for human use using a commercial synthesis module and resulted in a high radiochemical yield (30%±8%, uncorrected; n=54) and specific activity (6±4 Ci/μmol). Tumor uptake of [(18)F]FEPPA in mice bearing subcutaneous MDA-MB-231 BC xenografts was evaluated by PET-computed tomography imaging and ex vivo biodistribution studies. Although the tumor was successfully visualized, ex vivo biodistribution studies revealed low tumor uptake (0.7%ID/g), with the majority of radioactivity distributed in the spleen, muscle, and heart despite high TSPO expression in this cell line. Our laboratory routinely prepares [(18)F]FEPPA for human-imaging studies in the central nervous system, and we envision that radiopharmaceuticals that target the TSPO have the potential for imaging macrophages in the tumor microenvironment.
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.
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".