Inkjet printing of paraffin on paper allows low-cost point-of-care diagnostics for pathogenic fungi

We present a high resolution, ultra-frugal printing of paper microfluidic devices using in-house paraffin formulation on a simple filter paper. The patterns printed using an office inkjet printer formed a selective hydrophobic barrier of 4 ± 1 µm thickness with a hydrophilic channel width of 275 µm....

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Bibliographic Details
Published in:Cellulose (London) 2020-09, Vol.27 (13), p.7691-7701
Main Authors: Prabhu, Anusha, Giri Nandagopal, M. S., Peralam Yegneswaran, Prakash, Singhal, Hardik Ramesh, Mani, Naresh Kumar
Format: Article
Language:English
Subjects:
Aqueous solutions
Biomarkers
Bioorganic Chemistry
Ceramics
Chemistry
Chemistry and Materials Science
Cinnamaldehyde
Composites
Filter paper
Fungi
Glass
Inkjet printing
Microfluidic devices
Natural Materials
Organic Chemistry
Original Research
Paraffins
Physical Chemistry
Polymer Sciences
Printers (data processing)
Proline
Solvents
Substrates
Sustainable Development
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Summary:We present a high resolution, ultra-frugal printing of paper microfluidic devices using in-house paraffin formulation on a simple filter paper. The patterns printed using an office inkjet printer formed a selective hydrophobic barrier of 4 ± 1 µm thickness with a hydrophilic channel width of 275 µm. These printed patterns effectively confine common aqueous solutions and solvents, which was verified by solvent compatibility studies. SEM analysis reveals that the solvent confinement is due to pore blockage in the filter paper. The fabricated paper-based device was validated for qualitative assessment of Candida albicans (pathogenic fungi) by using a combination of L-proline β-naphthylamide as the substrate and cinnamaldehyde as an indicator. Our studies reveal that the pathogenic fungi can be detected within 10 min with the limit of detection (LOD) of 0.86 × 10 6  cfu/mL. Owing to its simplicity, this facile method shows high potential and can be scaled up for developing robust paper-based devices for biomarker detection in resource-limited settings. Graphic abstract
ISSN:0969-0239
1572-882X
DOI:10.1007/s10570-020-03314-3