Sample-to-answer mobile malaria molecular diagnositstic system for resource-limiting areas

Gihoon Choi, Daniel Song, Sony Shrestha, Jun Miao, Liwang Cui, Weihua Guan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work reports a field-deployable 'sample-to-answer' molecular diagnostic system (AnyMDx) for species-specific malaria detection at the point of need. The portable nucleic acid diagnostic system uses a disposable microfluidic disc, which incorporates integrated sample preparation steps of DNA extraction, purification, elution, and amplification. Built on our previous success with highly sensitive singleplex P. falciparum detection (low detection limit of ∼0.6 parasites/μl) [1], here we report the specificity performances of AnyMDx for distinguishing two of the most common endemic malaria species (P. falciparum and P. vivax). The AnyMDx system is fully automated and delivers real-time multiplexed species-specific molecular answers directly from the raw blood samples within 40 minutes without any requirement of laboratory infrastructures.

Original languageEnglish (US)
Title of host publication2017 IEEE 30th International Conference on Micro Electro Mechanical Systems, MEMS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages486-489
Number of pages4
ISBN (Electronic)9781509050789
DOIs
Publication statusPublished - Feb 23 2017
Event30th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2017 - Las Vegas, United States
Duration: Jan 22 2017Jan 26 2017

Publication series

NameProceedings of the IEEE International Conference on Micro Electro Mechanical Systems (MEMS)
ISSN (Print)1084-6999

Other

Other30th IEEE International Conference on Micro Electro Mechanical Systems, MEMS 2017
CountryUnited States
CityLas Vegas
Period1/22/171/26/17

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Mechanical Engineering
  • Electrical and Electronic Engineering

Cite this

Choi, G., Song, D., Shrestha, S., Miao, J., Cui, L., & Guan, W. (2017). Sample-to-answer mobile malaria molecular diagnositstic system for resource-limiting areas. In 2017 IEEE 30th International Conference on Micro Electro Mechanical Systems, MEMS 2017 (pp. 486-489). [7863449] (Proceedings of the IEEE International Conference on Micro Electro Mechanical Systems (MEMS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MEMSYS.2017.7863449