Document Detail


Prediction and control of number of cells in microdroplets by stochastic modeling.
MedLine Citation:
PMID:  23034772     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Manipulation and encapsulation of cells in microdroplets has found many applications in various fields such as clinical diagnostics, pharmaceutical research, and regenerative medicine. The control over the number of cells in individual droplets is important especially for microfluidic and bioprinting applications. There is a growing need for modeling approaches that enable control over a number of cells within individual droplets. In this study, we developed statistical models based on negative binomial regression to determine the dependence of number of cells per droplet on three main factors: cell concentration in the ejection fluid, droplet size, and cell size. These models were based on experimental data obtained by using a microdroplet generator, where the presented statistical models estimated the number of cells encapsulated in droplets. We also propose a stochastic model for the total volume of cells per droplet. The statistical and stochastic models introduced in this study are adaptable to various cell types and cell encapsulation technologies such as microfluidic and acoustic methods that require reliable control over number of cells per droplet provided that settings and interaction of the variables is similar.
Authors:
Elvan Ceyhan; Feng Xu; Umut Atakan Gurkan; Ahmet Emrehan Emre; Emine Sumeyra Turali; Rami El Assal; Ali Acikgenc; Chung-an Max Wu; Utkan Demirci
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Lab on a chip     Volume:  12     ISSN:  1473-0189     ISO Abbreviation:  Lab Chip     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-10-17     Completed Date:  2013-03-14     Revised Date:  2013-12-04    
Medline Journal Info:
Nlm Unique ID:  101128948     Medline TA:  Lab Chip     Country:  England    
Other Details:
Languages:  eng     Pagination:  4884-93     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Animals
Cell Count
Cell Size
Mice
Microtechnology / methods*
Models, Statistical*
Stochastic Processes
Grant Support
ID/Acronym/Agency:
R01 AI081534/AI/NIAID NIH HHS; R21 AI087107/AI/NIAID NIH HHS; R21 HL095960/HL/NHLBI NIH HHS; R21-AI087107/AI/NIAID NIH HHS; R21-HL095960/HL/NHLBI NIH HHS
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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