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Detection of breast cancer cells using targeted magnetic nanoparticles and ultra-sensitive magnetic field sensors

Overview of attention for article published in Breast Cancer Research, November 2011
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
3 blogs
twitter
15 X users
patent
2 patents
facebook
3 Facebook pages
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
122 Dimensions

Readers on

mendeley
151 Mendeley
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Title
Detection of breast cancer cells using targeted magnetic nanoparticles and ultra-sensitive magnetic field sensors
Published in
Breast Cancer Research, November 2011
DOI 10.1186/bcr3050
Pubmed ID
Authors

Helen J Hathaway, Kimberly S Butler, Natalie L Adolphi, Debbie M Lovato, Robert Belfon, Danielle Fegan, Todd C Monson, Jason E Trujillo, Trace E Tessier, Howard C Bryant, Dale L Huber, Richard S Larson, Edward R Flynn

Abstract

Breast cancer detection using mammography has improved clinical outcomes for many women, because mammography can detect very small (5 mm) tumors early in the course of the disease. However, mammography fails to detect 10 - 25% of tumors, and the results do not distinguish benign and malignant tumors. Reducing the false positive rate, even by a modest 10%, while improving the sensitivity, will lead to improved screening, and is a desirable and attainable goal. The emerging application of magnetic relaxometry, in particular using superconducting quantum interference device (SQUID) sensors, is fast and potentially more specific than mammography because it is designed to detect tumor-targeted iron oxide magnetic nanoparticles. Furthermore, magnetic relaxometry is theoretically more specific than MRI detection, because only target-bound nanoparticles are detected. Our group is developing antibody-conjugated magnetic nanoparticles targeted to breast cancer cells that can be detected using magnetic relaxometry.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Germany 1 <1%
India 1 <1%
Turkey 1 <1%
Korea, Republic of 1 <1%
Canada 1 <1%
Unknown 144 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 44 29%
Researcher 22 15%
Student > Bachelor 15 10%
Student > Master 13 9%
Student > Doctoral Student 10 7%
Other 23 15%
Unknown 24 16%
Readers by discipline Count As %
Engineering 26 17%
Agricultural and Biological Sciences 21 14%
Biochemistry, Genetics and Molecular Biology 15 10%
Chemistry 15 10%
Physics and Astronomy 12 8%
Other 26 17%
Unknown 36 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 48. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 October 2023.
All research outputs
#879,863
of 25,373,627 outputs
Outputs from Breast Cancer Research
#69
of 2,052 outputs
Outputs of similar age
#3,570
of 153,746 outputs
Outputs of similar age from Breast Cancer Research
#1
of 48 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,052 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.2. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 153,746 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.