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 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) | 0.000 | 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 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".