Ultrasensitive Multiparameter Phenotyping of Rare Cells Using an Integrated Digital‐Molecular‐Counting Microfluidic Well Plate Article Swipe
Shiuan‐Haur Su
,
Yujing Song
,
Michael W. Newstead
,
Tao Cai
,
Mengxi Wu
,
Andrew Stephens
,
Benjamin H. Singer
,
Katsuo Kurabayashi
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1002/smll.202101743
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1002/smll.202101743
Integrated microfluidic cellular phenotyping platforms provide a promising means of studying a variety of inflammatory diseases mediated by cell‐secreted cytokines. However, immunosensors integrated in previous microfluidic platforms lack the sensitivity to detect small signals in the cellular secretion of proinflammatory cytokines with high precision. This limitation prohibits researchers from studying cells secreting cytokines at low abundance or existing at a small population. Herein, the authors present an integrated platform named the “digital Phenoplate (dPP),” which integrates digital immunosensors into a microfluidic chip with on‐chip cell assay chambers, and demonstrates ultrasensitive cellular cytokine secretory profile measurement. The integrated sensors yield a limit of detection as small as 0.25 pg mL −1 for mouse tumor necrosis factor alpha (TNF‐α). Each on‐chip cell assay chamber confines cells whose population ranges from ≈20 to 600 in arrayed single‐cell trapping microwells. Together, these microfluidic features of the dPP simultaneously permit precise counting and image‐based cytometry of individual cells while performing parallel measurements of TNF‐α released from rare cells under multiple stimulant conditions for multiple samples. The dPP platform is broadly applicable to the characterization of cellular phenotypes demanding high precision and high throughput.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/smll.202101743
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/smll.202101743
- OA Status
- bronze
- Cited By
- 7
- References
- 65
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3173751787
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3173751787Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/smll.202101743Digital Object Identifier
- Title
-
Ultrasensitive Multiparameter Phenotyping of Rare Cells Using an Integrated Digital‐Molecular‐Counting Microfluidic Well PlateWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-06-25Full publication date if available
- Authors
-
Shiuan‐Haur Su, Yujing Song, Michael W. Newstead, Tao Cai, Mengxi Wu, Andrew Stephens, Benjamin H. Singer, Katsuo KurabayashiList of authors in order
- Landing page
-
https://doi.org/10.1002/smll.202101743Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/smll.202101743Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/smll.202101743Direct OA link when available
- Concepts
-
Microfluidics, Microfluidic chip, Population, Proinflammatory cytokine, Flow cytometry, Tumor necrosis factor alpha, Cytokine, Cell, Nanotechnology, Cell biology, Biology, Materials science, Molecular biology, Inflammation, Immunology, Medicine, Biochemistry, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2023: 1, 2022: 3Per-year citation counts (last 5 years)
- References (count)
-
65Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| institutions_distinct_count | 8 |
| corresponding_institution_ids | https://openalex.org/I27837315 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.58013045 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |