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Liposome Formation Using a Coaxial Turbulent Jet in Co-Flow

Overview of attention for article published in Pharmaceutical Research, October 2015
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Title
Liposome Formation Using a Coaxial Turbulent Jet in Co-Flow
Published in
Pharmaceutical Research, October 2015
DOI 10.1007/s11095-015-1798-8
Pubmed ID
Authors

Antonio P. Costa, Xiaoming Xu, Mansoor A. Khan, Diane J. Burgess

Abstract

Liposomes are robust drug delivery systems that have been developed into FDA-approved drug products for several pharmaceutical indications. Direct control in producing liposomes of a particular particle size and particle size distribution is extremely important since liposome size may impact cellular uptake and biodistribution. A device consisting of an injection-port was fabricated to form a coaxial turbulent jet in co-flow that produces liposomes via the ethanol injection method. By altering the injection-port dimensions and flow rates, a fluid flow profile (i.e., flow velocity ratio vs. Reynolds number) was plotted and associated with the polydispersity index of liposomes. Certain flow conditions produced unilamellar, monodispersed liposomes and the mean particle size was controllable from 25 up to >465 nm. The mean liposome size is highly dependent on the Reynolds number of the mixed ethanol/aqueous phase and independent of the flow velocity ratio. The significance of this work is that the Reynolds number is predictive of the liposome particle size, independent of the injection-port dimensions. In addition, a new model describing liposome formation is outlined. The significance of the model is that it relates fluid dynamic properties and lipid-molecule physical properties to the final liposome size.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 25%
Student > Master 8 18%
Researcher 7 16%
Professor 4 9%
Student > Bachelor 3 7%
Other 3 7%
Unknown 8 18%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 14 32%
Engineering 7 16%
Biochemistry, Genetics and Molecular Biology 3 7%
Chemistry 3 7%
Medicine and Dentistry 2 5%
Other 3 7%
Unknown 12 27%
Attention Score in Context

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 12 January 2016.
All research outputs
#20,716,759
of 23,316,003 outputs
Outputs from Pharmaceutical Research
#2,673
of 2,888 outputs
Outputs of similar age
#231,933
of 276,063 outputs
Outputs of similar age from Pharmaceutical Research
#22
of 25 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,888 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 1st percentile – i.e., 1% 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 276,063 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.