In Vivo 3T Magnetic Resonance Imaging Using a Biologically Specific Contrast Agent for Prostate Cancer: A Nude Mouse Model
Bibliographic record
Abstract
We characterized in vivo a functional superparamagnetic iron-oxide magnetic resonance contrast agent that shortens the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mn fontstyle="italic">2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> relaxation time in magnetic resonance imaging (MRI) of prostate cancer xenografts. The agent was developed by conjugating Molday ION™ carboxyl-6 (MIC6), with a deimmunized mouse monoclonal antibody (muJ591) targeting prostate-specific membrane antigen (PSMA). This functional contrast agent could be used as a noninvasive method to detect prostate cancer cells that are PSMA positive and more readily differentiate them from surrounding tissues for treatment. The functional contrast agent was injected intravenously into mice and its effect was compared to both MIC6 (without conjugated antibody) and phosphate-buffered saline (PBS) injection controls. MR imaging was performed on a clinical 3T MRI scanner using a multiecho spin echo (MESE) sequence to obtain <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:msub><mml:mrow><mml:mi>T</mml:mi></mml:mrow><mml:mrow><mml:mn fontstyle="italic">2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> relaxation time values. Inductively coupled plasma atomic emission spectroscopy was used to confirm an increase in elemental iron in injected mice tumours relative to controls. Histological examination of H&E stained tissues showed normal morphology of the tissues collected.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".