Cation Exchange of Anisotropic-Shaped Magnetite Nanoparticles Generates High-Relaxivity Contrast Agents for Liver Tumor Imaging
Bibliographic record
Abstract
Cation exchange is a powerful means to adjust the properties of nanocrystals through composition change with morphology retention. Herein, we demonstrate that cation exchange can engineer the composition of iron oxide nanocrystals to dramatically improve their contrast ability in magnetic resonance imaging (MRI). We successfully construct manganese and zinc engineered iron oxide nanoparticles with diverse shapes (sphere, cube, and octapod) by facile cation exchange reactions. Extended X-ray absorption fine structure (EXAFS) study indicates that Mn 2+ and Zn 2+ ions are doped into the crystal lattice of ferrite, and more importantly, most of them are distributed in T d sites of ferrite. These engineered shaped-anisotropic iron oxide nanoparticles exhibit both high saturated magnetization and large effective boundary radii, which leads to remarkable transverse relaxivity ( r 2 ), for example, 754.2 mM –1 s –1 for zinc engineered octapod iron oxide nanoparticles. These engineered iron oxide nanoparticles, as high-performance T 2 contrast agents for in vivo MR imaging, enable sensitive imaging of early hepatic tumors and metastatic hepatic tumors (as small as 0.4 mm), holding great promise for prompt and accurate diagnosis of cancers and metastases.
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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".