Development and Characterization of an Antibody-Labeled Super-Paramagnetic Iron Oxide Contrast Agent Targeting Prostate Cancer Cells for Magnetic Resonance Imaging
Bibliographic record
Abstract
In this study we developed, characterized and validated in vitro a functional superparagmagnetic iron-oxide based magnetic resonance contrast agent by conjugating a commercially available iron oxide nanoparticle, Molday ION Rhodamine-B Carboxyl (MIRB), with a deimmunized mouse monoclonal antibody (muJ591) targeting prostate-specific membrane antigen (PSMA). This functional contrast agent is intended for the specific and non-invasive detection of prostate cancer cells that are PSMA positive, a marker implicated in prostate tumor progression and metastasis. The two-step carbodiimide reaction used to conjugate the antibody to the nanoparticle was efficient and we obtained an elemental iron content of 1958 ± 611 per antibody. Immunofluorescence microscopy and flow cytometry showed that the conjugated muJ591:MIRB complex specifically binds to PSMA-positive (LNCaP) cells. The muJ591:MIRB complex reduced cell adhesion and cell proliferation on LNCaP cells and caused apoptosis as tested by Annexin V assay, suggesting anti-tumorigenic characteristics. Measurements of the T2 relaxation time of the muJ591:MIRB complex using a 400 MHz Innova NMR and a multi-echo spin-echo sequence on a 3T MRI (Achieva, Philips) showed a significant T2 relaxation time reduction for the muJ591:MIRB complex, with a reduced T2 relaxation time as a function of the iron concentration. PSMA-positive cells treated with muJ591:MIRB showed a significantly shorter T2 relaxation time as obtained using a 3T MRI scanner. The reduction in T2 relaxation time for muJ591:MIRB, combined with its specificity against PSMA+LNCaP cells, suggest its potential as a biologically-specific MR contrast agent.
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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 | 0.001 | 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) | 0.000 | 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".