Concurrent Dual Contrast for Cellular Magnetic Resonance Imaging Using Gadolinium Oxide and Iron Oxide Nanoparticles
Bibliographic record
Abstract
Rationale and Objectives. Concurrent visualization of differential targets in cellular and molecular imaging is valuable for resolving processes spatially and temporally, as in monitoring different cell subtypes. The purpose of this study was to demonstrate concurrent, dual (positive and negative) contrast visualization on magnetic resonance imaging (MRI) of two colocalized cell populations labeled with Gadolinium "Gd" oxide and iron "Fe" oxide nanoparticles. Materials and Methods. Human aortic endothelial cells (EC) and smooth muscle cells (SMC) were labeled with various concentrations of Gd oxide and Fe oxide, respectively. MRI on single- or mixed-cell samples was performed at 7 tesla. Proper cell phenotype expressions, cell uptake of contrast agents, and the effect of labeling on cell viability and proliferation were also determined. Results. Both contrast agents were efficiently taken up by cells, with viability and proliferation largely unaffected. On MRI, the positive contrast associated with Gd oxide-labeled EC and negative contrast associated with Fe oxide-labeled SMC discriminated the presence of each cell type, whether it existed alone or colocalized in a mixed-cell sample. Conclusion. It is feasible to use Gd oxide and Fe oxide for dual contrast and concurrent discrimination of two colocalized cell populations on MRI at 7 tesla.
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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) | 0.000 | 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".