First steps towards simultaneous isolation and detection of exosomes with carbon nanotube-based SMRs

Mirea, Teona and Olivares Roza, Jimena and Yañez Mo, María and Valés Gómez, Mar and Iborra Grau, Enrique (2018). First steps towards simultaneous isolation and detection of exosomes with carbon nanotube-based SMRs. In: "IEEE International Ultrasonics Symposium (IUS 2018)", 22/10/2018 - 25/10/2018, Kobe, Japan. pp. 1-4. https://doi.org/10.1109/ULTSYM.2018.8579718.

Description

Title: First steps towards simultaneous isolation and detection of exosomes with carbon nanotube-based SMRs
Author/s:
  • Mirea, Teona
  • Olivares Roza, Jimena
  • Yañez Mo, María
  • Valés Gómez, Mar
  • Iborra Grau, Enrique
Item Type: Presentation at Congress or Conference (Article)
Event Title: IEEE International Ultrasonics Symposium (IUS 2018)
Event Dates: 22/10/2018 - 25/10/2018
Event Location: Kobe, Japan
Title of Book: IEEE International Ultrasonics Symposium (IUS 2018)
Título de Revista/Publicación: IEEE International Ultrasonics Symposium (IUS 2018)
Date: 2018
ISSN: 1051-0117
Subjects:
Freetext Keywords: Carbon nanotubes; solidly mounted resonator; biosensor; antibody
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

Exosomes are small (20-150nm) intercellular vesicles carrying valuable information regarding disease presence or evolution. Their isolation from body fluids is one of the most challenging targets. Although many techniques already exist, these are still inefficient, expensive and time-consuming. One of these new methods is nanofiltration. Within this technique, carbon nanotube (CNT) forests have been proposed as good candidates owing to their easily controllable tube separation and growth. Previous works have proven the isolation of different particles; however, optical read-out methods are still needed to confirm the success of the process. Here we propose and start studying the integration of CNT forests in solidly mounted resonators to simultaneously isolate exosomes and gravimetrically estimate the trapped amount. As a first step we prove the ability of our devices to trap and detect CD63 antibodies, due to their high affinity to exosomes. We demonstrate a frequency shift of around 280±8 kHz with an antibody concentration of 8 nM, four times lower than previously reported concentrations used for the detection of antibodies with thin film acoustic resonators, for similar frequency shifts.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2017-84817-C2-1-RUnspecifiedUnspecifiedSensores gravimétricos de gases basados en resonadores electroacústicos de película delgada de ALN para aplicaciones en temperaturas extremas
Government of SpainSAF2015-69169-RUnspecifiedUnspecifiedLas células natural killer y las nanovesículas extracelulares tumorales en la respuesta inmunitaria frente al cáncer humano
Government of SpainBIO2017-86500-RUnspecifiedUnspecifiedEstudio del potencial biotecnológico de herramientas frente a tetraspaninas en cáncer, secreción de exosomas y agentes vacunales
Madrid Regional GovernmentB2017/BMD-3733IMMUNOTHERCAN-CMUnspecifiedUnspecified

More information

Item ID: 55072
DC Identifier: http://oa.upm.es/55072/
OAI Identifier: oai:oa.upm.es:55072
DOI: 10.1109/ULTSYM.2018.8579718
Official URL: https://ieeexplore.ieee.org/document/8579718
Deposited by: Memoria Investigacion
Deposited on: 27 May 2019 16:08
Last Modified: 27 May 2019 16:08
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM