Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/105237
DC FieldValueLanguage
dc.contributor.authorRibeiro, Mafalda-
dc.contributor.authorAli, Pamela-
dc.contributor.authorMetcalfe, Benjamin-
dc.contributor.authorMoschou, Despina-
dc.contributor.authorRocha, Paulo R. F.-
dc.date.accessioned2023-02-10T09:46:03Z-
dc.date.available2023-02-10T09:46:03Z-
dc.date.issued2021-06-20-
dc.identifier.issn2072-666Xpt
dc.identifier.urihttps://hdl.handle.net/10316/105237-
dc.description.abstractOrgan-on-Chip technology is commonly used as a tool to replace animal testing in drug development. Cells or tissues are cultured on a microchip to replicate organ-level functions, where measurements of the electrical activity can be taken to understand how the cell populations react to different drugs. Microfluidic structures are integrated in these devices to replicate more closely an in vivo microenvironment. Research has provided proof of principle that more accurate replications of the microenvironment result in better micro-physiological behaviour, which in turn results in a higher predictive power. This work shows a transition from a no-flow (static) multi-electrode array (MEA) to a continuous-flow (dynamic) MEA, assuring a continuous and homogeneous transfer of an electrolyte solution across the measurement chamber. The process through which the microfluidic system was designed, simulated, and fabricated is described, and electrical characterisation of the whole structure under static solution and a continuous flow rate of 80 µL/min was performed. The latter reveals minimal background disturbance, with a background noise below 30 µVpp for all flow rates and areas. This microfluidic MEA, therefore, opens new avenues for more accurate and long-term recordings in Organ-on-Chip systems.pt
dc.language.isoengpt
dc.publisherMDPI AGpt
dc.relationThe Royal Society, grant number RSGnR1n180260 “Modelling brain function through Organ-on-Chip platforms for drug discovery applications”pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectMEApt
dc.subjectbrain cellspt
dc.subjectelectrical recordingspt
dc.subjectOrgan-on-Chippt
dc.subjectmicrofluidicspt
dc.subjectBrain-on-Chippt
dc.titleMicrofluidics Integration into Low-Noise Multi-Electrode Arrayspt
dc.typearticle-
degois.publication.firstPage727pt
degois.publication.issue6pt
degois.publication.titleMicromachinespt
dc.peerreviewedyespt
dc.identifier.doi10.3390/mi12060727pt
degois.publication.volume12pt
dc.date.embargo2021-06-20*
uc.date.periodoEmbargo0pt
item.openairetypearticle-
item.fulltextCom Texto completo-
item.languageiso639-1en-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.researchunitCFE - Centre for Functional Ecology - Science for People & the Planet-
crisitem.author.orcid0000-0002-8917-9101-
Appears in Collections:I&D CFE - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons