A dual modality<sup>99m</sup>Tc/Re(<scp>i</scp>)-labelled T140 analogue for imaging of CXCR4 expression
Bibliographic record
Abstract
The C-X-C chemokine receptor 4 (CXCR4) has been shown to be overexpressed in at least 23 types of cancer, including prostate cancer which has been shown to have a significant distinction of expression rates between cancerous compared to healthy or benign tissue. In an attempt to exploit the difference in expression, we have synthesized a derivative of T140, a peptide antagonist for CXCR4, containing a fluorescent 4-amino-1,8-naphthalimide appended with a di-(2-picolyl)amine binding unit to chelate rhenium or technetium-99m for fluorescence or SPECT imaging. The rhenium-coordinated variant was shown to have similar binding affinity for the receptor as T140 and showed specific uptake by fluorescence microscopy in CXCR4 expressing cells. The peptide was radiolabelled with technetium-99m in decay corrected radiochemical yields ranging from 60-85%, radiochemical purities >95%, and molar activities of 36-44 GBq μmol-1. The technetium-99m labelled peptide showed two-fold higher uptake in U87 cells expressing CXCR4 compared to non-transfected cells. Ex vivo biodistribution studies were performed using the technetium-99m labelled peptide in NOD/SCID mice bearing tumors derived from U87 cells with CXCR4. Tumor uptake of 0.51 ± 0.09% ID g-1 was observed two-hours post-injection. Our novel T140 derivative is suitable for imaging of CXCR4 expression by confocal microscopy. Further structural modifications to the peptide or metal complex may result in improved biodistribution for use in SPECT imaging of CXCR4 expressing tumors.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".