Literature DB >> 30350581

A Passive Mixing Microfluidic Urinary Albumin Chip for Chronic Kidney Disease Assessment.

Jiandong Wu1, Dumitru Tomsa1, Michael Zhang2, Paul Komenda2, Navdeep Tangri2, Claudio Rigatto2, Francis Lin1.   

Abstract

Urinary albumin level is an important indicator of kidney damage in chronic kidney disease (CKD) but effective routine albumin detection tools are lacking. In this paper, we developed a low-cost and high accuracy microfluidic urinary albumin chip (UAL-Chip) to rapidly measure albumin in urine. The UAL-Chip offers three major features: (1) we incorporated a fluorescent reaction assay into the chip to improve the detection accuracy; (2) we constructed a passive and continuous mixing module in the chip that provides user-friendly operation and greater signal stability; (3) we applied a pressure-balancing strategy based on the immiscible oil coverage that achieves precise control of the sample-dye mixing ratio. We validated the UAL-Chip using both albumin standards and urine samples from 12 CKD patients and achieved an estimated limit of detection (LOD) of 5.2 μg/mL. The albumin levels in CKD patients' urine samples measured by UAL-Chip is consistent with the traditional well-plate measurements and clinical results. We foresee the potential of extending this passive and precise mixing platform to assess various disease biomarkers.

Entities:  

Keywords:  albumin; albuminuria; chronic kidney disease; microfluidic device; point-of-care

Mesh:

Substances:

Year:  2018        PMID: 30350581     DOI: 10.1021/acssensors.8b01072

Source DB:  PubMed          Journal:  ACS Sens        ISSN: 2379-3694            Impact factor:   7.711


  3 in total

Review 1.  A comprehensive review on advancements in tissue engineering and microfluidics toward kidney-on-chip.

Authors:  Jasti Sateesh; Koushik Guha; Arindam Dutta; Pratim Sengupta; Dhanya Yalamanchili; Nanda Sai Donepudi; M Surya Manoj; Sk Shahrukh Sohail
Journal:  Biomicrofluidics       Date:  2022-08-16       Impact factor: 3.258

2.  Label-Free Protein Detection by Micro-Acoustic Biosensor Coupled with Electrical Field Sorting. Theoretical Study in Urine Models.

Authors:  Nikolay Mukhin; Georgii Konoplev; Aleksandr Oseev; Marc-Peter Schmidt; Oksana Stepanova; Andrey Kozyrev; Alexander Dmitriev; Soeren Hirsch
Journal:  Sensors (Basel)       Date:  2021-04-06       Impact factor: 3.576

Review 3.  Blood and Urinary Biomarkers of Antipsychotic-Induced Metabolic Syndrome.

Authors:  Aiperi K Khasanova; Vera S Dobrodeeva; Natalia A Shnayder; Marina M Petrova; Elena A Pronina; Elena N Bochanova; Natalia V Lareva; Natalia P Garganeeva; Daria A Smirnova; Regina F Nasyrova
Journal:  Metabolites       Date:  2022-08-05
  3 in total

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