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Generation of Dynamical Environmental Conditions using a High-Throughput Microfluidic Device
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An Autonomous Microfluidic Device for Generating Volume-Defined Dried Plasma Spots.

Janosch Hauser1, Gabriel Lenk1, Shahid Ullah2

  • 1Department of Micro and Nanosystems , KTH Royal Institute of Technology , 10044 Stockholm , Sweden.

Analytical Chemistry
|May 8, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an autonomous device using microfluidics to create dried plasma spots (DPS) from blood samples in under 6 minutes. This innovation simplifies plasma preparation for quantitative blood analysis.

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Area of Science:

  • Biomedical Engineering
  • Analytical Chemistry
  • Clinical Diagnostics

Background:

  • Traditional plasma preparation is time-consuming, requires skilled personnel, and involves centrifugation.
  • Accurate plasma volume measurement is crucial for reliable quantitative blood analysis.

Purpose of the Study:

  • To develop an autonomous device for rapid, patient-centric plasma sampling.
  • To create dried plasma spots (DPS) for simplified storage and analysis.
  • To assess the performance of the autonomous DPS device compared to traditional methods.

Main Methods:

  • Utilized capillary forces and microfluidic engineering to design an autonomous plasma sampling device.
  • Tested prototypes with whole blood from 10 volunteers, varying input volumes and hematocrit levels.
  • Assessed plasma volume gravimetrically and analyzed caffeine concentrations using LC-MS/MS.

Main Results:

  • The device autonomously filtered and stored plasma as DPS in less than 6 minutes.
  • Achieved a mean plasma volume of 11.6 μL with a 3.0% relative standard deviation.
  • LC-MS/MS analysis showed a strong correlation (R² = 0.99) for caffeine concentrations in DPS compared to centrifuged plasma.

Conclusions:

  • The autonomous DPS device offers a simplified, patient-centric approach to plasma sampling via finger-prick.
  • Enables the generation of volume-defined DPS for quantitative blood analysis, reducing labor and potential for error.
  • Potential to advance point-of-care diagnostics and remote patient monitoring.