Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 304

The DOI matches its Crossref record.

Surface Modulation of Magnetic Nanocrystals in the Development of Highly Efficient Magnetic Resonance Probes for Intracellular Labeling

Open access
Song, Ho-Taek, Choi, Jin-sil, Huh, Yong-Min, Kim, Sungjun, Jun, Young-wook, Suh, Jin-Suck, Cheon, Jinwoo·2005·Journal of the American Chemical Society

Abstract

High-quality biocompatible magnetic iron oxide (Fe3O4) nanocrystals were developed through a ligand exchange process of hydrophobically capped nanocrystals with hydrophilic molecules. By simple modulation of the nanocrystal surface ligand charge properties, we have been able to prepare magnetic nanocrystals with excellent intracellular labeling capabilities that efficiently label a variety of cell types without the need for additional transport facilitating agents. The excellent intracellular labeling capability of the newly developed cationic WSIO has further led to successful MRI monitoring of the migration of neural stem cells in rat spinal cord. The magnetic nanocrystals developed here have great potential in applications for labeling of various cell types and also the monitoring of cell-based medical treatments and cancer metastasis.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ja051833y

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 304

Metadata

Authors
Song, H.-T., Choi, J.-S., Huh, Y.-M., Kim, S., Jun, Y.-W., Suh, J.-S., & Cheon, J.
Venue
Journal of the American Chemical Society
Published
2005-06-25
Volume
127
Issue
28
Pages
9992-9993
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W1995269182
Cited by
304
References
0
FWCI
19.76
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Surface Modulation of Magnetic Nanocrystals in the Development of Highly Efficient Magnetic Resonance Probes for Intracellular Labeling. https://app.cochat.ai/papers/10.1021/ja051833y
The paper
Song, H.-T., Choi, J.-S., Huh, Y.-M., Kim, S., Jun, Y.-W., Suh, J.-S., & Cheon, J. (2005). Surface Modulation of Magnetic Nanocrystals in the Development of Highly Efficient Magnetic Resonance Probes for Intracellular Labeling. Journal of the American Chemical Society. https://doi.org/10.1021/ja051833y

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.