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Portable smartphone-based fluorescent microscopes are becoming popular owing to their ability to provide major functionalities offered by regular benchtop microscopes at a fraction of the cost. However, smartphone-based microscopes are still limited to a single fluorophore, fixed magnification, the inability to work with a different smartphones, and limited usability to either glass slides or cover slips. To overcome these challenges, here we present a modular smartphone-based microscopic attachment. The modular design allows the user to easily swap between different sets of filters and lenses, thereby enabling utility of multiple fluorophores and magnification levels. Our microscopic smartphone attachment can also be used with different smartphones and was tested with Nokia Lumia 1020, Samsung Galaxy S9+, and an iPhone XS. Further, we showed imaging results of samples on glass slides, cover slips, and microfluidic devices. A 1951 USAF resolution test target was used to quantify the maximum resolution of the microscope which was found to be 3.9 μm. The performance of the smartphone-based microscope was compared with a benchtop microscope and we found an R 2 value of 0.99 using polystyrene beads and blood cells isolated from human blood samples collected from Robert Wood Johnson Medical Hospital. Additionally, to count the particles (cells and beads) imaged from the smartphone-based fluorescent microscope, we developed artificial neural networks (ANNs) using multiple training algorithms, and evaluated their performances compared to the control (ImageJ). Finally, we did ANOVA and Tukey's post-hoc analysis and found a p -value of 0.97 which shows that no statistical significant difference exists between the performance of the trained ANN and control (ImageJ).
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Micro-mechanical blood clot testing using smartphones
Abstract Frequent prothrombin time (PT) and international normalized ratio (INR) testing is critical for millions of people on lifelong anticoagulation with warfarin. Currently, testing is performed in hospital laboratories or with expensive point-of-care devices limiting the ability to test frequently and affordably. We report a proof-of-concept PT/INR testing system that uses the vibration motor and camera on smartphones to track micro-mechanical movements of a copper particle. The smartphone system computed the PT/INR with inter-class correlation coefficients of 0.963 and 0.966, compared to a clinical-grade coagulation analyzer for 140 plasma samples and demonstrated similar results for 80 whole blood samples using a single drop of blood (10 μl). When tested with 79 blood samples with coagulopathic conditions, the smartphone system demonstrated a correlation of 0.974 for both PT/INR. Given the ubiquity of smartphones in the global setting, this proof-of-concept technology may provide affordable and effective PT and INR testing in low-resource environments.
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- Award ID(s):
- 1914873
- PAR ID:
- 10379237
- Date Published:
- Journal Name:
- Nature Communications
- Volume:
- 13
- Issue:
- 1
- ISSN:
- 2041-1723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41467-022-28499-y
