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Attention Score in Context
Title |
Design and development of multifunctional polyphosphoester-based nanoparticles for ultrahigh paclitaxel dual loading
|
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Published in |
Nanoscale, January 2017
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DOI | 10.1039/c7nr05935c |
Pubmed ID | |
Authors |
Fuwu Zhang, Sarosh Khan, Richen Li, Justin A. Smolen, Shiyi Zhang, Guizhi Zhu, Lu Su, Ashlee A. Jahnke, Mahmoud Elsabahy, Xiaoyuan Chen, Karen L. Wooley |
Abstract |
Multifunctional polyphosphoester-based nanoparticles capable of loading paclitaxel (PTX) both chemically and physically were prepared, achieving an ultrahigh equivalent PTX aqueous concentration of 25.30 mg mL(-1). The dual-loaded nanoparticles were effective in killing cancer cells, which has the potential to minimize the amount of nanocarriers needed for clinical applications, due to their ultrahigh loading capacity. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 22% |
Student > Master | 4 | 17% |
Researcher | 3 | 13% |
Lecturer | 1 | 4% |
Student > Bachelor | 1 | 4% |
Other | 5 | 22% |
Unknown | 4 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Chemistry | 5 | 22% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 13% |
Biochemistry, Genetics and Molecular Biology | 2 | 9% |
Engineering | 2 | 9% |
Unspecified | 1 | 4% |
Other | 4 | 17% |
Unknown | 6 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 16 October 2017.
All research outputs
#18,814,057
of 23,316,003 outputs
Outputs from Nanoscale
#6,111
of 9,512 outputs
Outputs of similar age
#313,093
of 422,868 outputs
Outputs of similar age from Nanoscale
#467
of 689 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,512 research outputs from this source. They receive a mean Attention Score of 4.2. This one is in the 23rd percentile – i.e., 23% of its peers scored the same or lower than it.
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 422,868 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 689 others from the same source and published within six weeks on either side of this one. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.