Keyword search (4,163 papers available)

"microfluidic" Keyword-tagged Publications:

Title Authors PubMed ID
1 Microfluidic Liquid Biopsy Minimally Invasive Cancer Diagnosis by Nano-Plasmonic Label-Free Detection of Extracellular Vesicles: Review Neriya Hegade KP; Bhat RB; Packirisamy M; 40650129
ENCS
2 Microfluidic Wound-Healing Assay for Comparative Study on Fluid Dynamic, Chemical and Mechanical Wounding on Microglia BV2 Migration Yazdanpanah Moghadam E; Sonenberg N; Packirisamy M; 39203655
ENCS
3 An Automated Single-Cell Droplet-Digital Microfluidic Platform for Monoclonal Antibody Discovery Ahmadi F; Tran H; Letourneau N; Little SR; Fortin A; Moraitis AN; Shih SCC; 38441226
BIOLOGY
4 Measuring prion propagation in single bacteria elucidates a mechanism of loss Jager K; Orozco-Hidalgo MT; Springstein BL; Joly-Smith E; Papazotos F; McDonough E; Fleming E; McCallum G; Yuan AH; Hilfinger A; Hochschild A; Potvin-Trottier L; 37738299
PHYSICS
5 Microfluidic Wound-Healing Assay for ECM and Microenvironment Properties on Microglia BV2 Cells Migration Yazdanpanah Moghadam E; Sonenberg N; Packirisamy M; 36832056
ENCS
6 An electrochemical aptasensor for Δ9-tetrahydrocannabinol detection in saliva on a microfluidic platform Kékedy-Nagy L; Perry JM; Little SR; Llorens OY; Shih SCC; 36549107
BIOLOGY
7 Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications Allard P; Papazotos F; Potvin-Trottier L; 36312536
BIOLOGY
8 Microfluidics in smart packaging of foods Pou KRJ; Raghavan V; Packirisamy M; 36192908
ENCS
9 Microfluidic Platforms for the Isolation and Detection of Exosomes: A Brief Review Raju D; Bathini S; Badilescu S; Ghosh A; Packirisamy M; 35630197
ENCS
10 Numerical and Experimental Validation of Mixing Efficiency in Periodic Disturbance Mixers López RR; Sánchez LM; Alazzam A; Burnier JV; Stiharu I; Nerguizian V; 34577745
ENCS
11 Magnetic particle based liquid biopsy chip for isolation of extracellular vesicles and characterization by gene amplification Bathini S; Pakkiriswami S; Ouellette RJ; Ghosh A; Packirisamy M; 34517262
ENCS
12 Microfluidic Shear Processing Control of Biological Reduction Stimuli-Responsive Polymer Nanoparticles for Drug Delivery. Huang Y, Jazani AM, Howell EP, Reynolds LA, Oh JK, Moffitt MG 33455300
CHEMBIOCHEM
13 Controlled Microfluidic Synthesis of Biological Stimuli-Responsive Polymer Nanoparticles. Huang Y, Moini Jazani A, Howell EP, Oh JK, Moffitt MG 31820915
CHEMBIOCHEM
14 The Key Role of Intrinsic Lifetime Dynamics from Upconverting Nanosystems in Multiemission Particle Velocimetry Tessitore G; Maurizio SL; Sabri T; Skinner CD; Capobianco JA; 32924221
CNSR
15 One Cell, One Drop, One Click: Hybrid Microfluidics for Mammalian Single Cell Isolation. Samlali K, Ahmadi F, Quach ABV, Soffer G, Shih SCC 32705796
BIOLOGY
16 Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer. López RR, Ocampo I, Sánchez LM, Alazzam A, Bergeron KF, Camacho-León S, Mounier C, Stiharu I, Nerguizian V 32106424
ENCS
17 Lab-On-A-Chip for the Development of Pro-/Anti-Angiogenic Nanomedicines to Treat Brain Diseases. Subramaniyan Parimalam S, Badilescu S, Sonenberg N, Bhat R, Packirisamy M 31817343
ENCS
18 Dielectrophoresis Multipath Focusing of Microparticles through Perforated Electrodes in Microfluidic Channels. Alazzam A, Al-Khaleel M, Riahi MK, Mathew B, Gawanmeh A, Nerguizian V 31394810
ENCS

 

Title:Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer.
Authors:López RROcampo ISánchez LMAlazzam ABergeron KFCamacho-León SMounier CStiharu INerguizian V
Link:https://www.ncbi.nlm.nih.gov/pubmed/32106424?dopt=Abstract
DOI:10.3390/mi11030235
Publication:Micromachines
Keywords:continuous-flow synthesisliposomesmicrofluidicsmicromixersnanoparticles
PMID:32106424 Category:Micromachines (Basel) Date Added:2020-02-29
Dept Affiliation: ENCS
1 Department of Electrical Engineering, École de technologie supérieure, 1100 Notre Dame-West, Montreal, QC H3C 1K3, Canada.
2 School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Monterrey 64849, N.L., Mexico.
3 Department of Engineering, Universidad Autónoma de Querétaro Cerro de las Campanas s/n, Santiago de Querétaro 76010, Qro., México.
4 System on Chip Center, Department of Mechanical Engineering, Khalifa University, Abu Dhabi 127788, UAE.
5 Department of Biological Sciences, Université du Québec à Montréal, 141 Président-Kennedy, Montreal, QC H2X 1Y4, Canada.
6 Department of Mechanical and Industrial Engineering, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, QC H3G 1M8, Canada.

Description:

Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer.

Micromachines (Basel). 2020 Feb 25;11(3):

Authors: López RR, Ocampo I, Sánchez LM, Alazzam A, Bergeron KF, Camacho-León S, Mounier C, Stiharu I, Nerguizian V

Abstract

Liposomes nanoparticles (LNPs) are vesicles that encapsulate drugs, genes, and imaging labels for advanced delivery applications. Control and tuning liposome physicochemical characteristics such as size, size distribution, and zeta potential are crucial for their functionality. Liposome production using micromixers has shown better control over liposome characteristics compared with classical approaches. In this work, we used our own designed and fabricated Periodic Disturbance Micromixer (PDM). We used Design of Experiments (DoE) and Response Surface Methodology (RSM) to statistically model the relationship between the Total Flow Rate (TFR) and Flow Rate Ratio (FRR) and the resulting liposomes physicochemical characteristics. TFR and FRR effectively control liposome size in the range from 52 nm to 200 nm. In contrast, no significant effect was observed for the TFR on the liposomes Polydispersity Index (PDI); conversely, FRR around 2.6 was found to be a threshold between highly monodisperse and low polydispersed populations. Moreover, it was shown that the zeta potential is independent of TFR and FRR. The developed model presented on the paper enables to pre-establish the experimental conditions under which LNPs would likely be produced within a specified size range. Hence, the model utility was demonstrated by showing that LNPs were produced under such conditions.

PMID: 32106424 [PubMed]





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