{
  "abstract": "Efficient whole blood processing at the point-of-care (POC) remains challenging due to interference from cellular components, risk of hemolysis, as well as reliance on external equipment and skilled operators. Here, we present a passive, low-cost microfluidic platform for rapid separation of cellular components from diluted samples of whole blood without the need for external pumps. The device features a circular maze-shaped microchannel incorporating 18 sequential wells, enabling effective cell retention through purely passive hydrodynamic mechanisms. Fabricated from hydrophilic polymer sheets and pressure-sensitive adhesive (PSA) layers, the platform is scalable, disposable, and enables very low-cost production (< $1 per unit). The blood-separation performance of the standalone microfluidic chip was validated using HEK-293 and AtT-20 cell suspensions, mixed cell suspensions, and diluted human blood. Efficient retention of cellular components in the early wells generated a cell-free filtrate suitable for downstream analytical applications. Building on this validated separation capability, the platform was integrated with a lateral flow immunoassay (LFIA) module as a proof-of-concept in a POC application by testing for hepatitis B surface antigen (HBsAg). The integrated system enabled detection of HBsAg at concentrations as low as 10 ng/mL within 10 min. In addition, deep learning–assisted convolutional neural networks were employed for automated assessment of filtration efficiency and test-line intensity. Overall, this work demonstrates a robust and accessible microfluidic sample-preparation platform with potential for decentralized diagnostic applications, particularly critical for resource-limited settings.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Biology, York University, 4700 Keele Street, Toronto, ON M3J 1P3 Canada",
    "Laboratory of Advanced Biotechnologies for Health Assessments (Lab-HA), Lassonde School of Engineering, York University, Toronto, ON M3J 1P3 Canada",
    "Department of Electrical Engineering and Computer Science (EECS), Lassonde School of Engineering, York University, Toronto, ON M3J 1P3 Canada"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Deniz Sadighbayan"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Alireza Norouziazad"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Fatemeh Rahimi"
    },
    {
      "affs": [
        0
      ],
      "name": "Jean-Paul Paluzzi"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Razieh Salahandish",
      "orcid": "0000-0003-1299-1051"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8edzby316xzv6.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-63706-6",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13710177/",
  "id": "8edzby316xzv6",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://doi.org/10.1038/s41598-026-63706-6",
  "language": "en",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "2204|Biosensors and Analytical Detection"
    ]
  ],
  "openalex": "W7171531219",
  "pdf_url": null,
  "pmcid": "PMC13710177",
  "pmid": null,
  "published": "2026-07-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/8edzby316xzv6.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T12:21:11Z",
      "native_id": "PMC13710177",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41598-026-63706-6"
    }
  ],
  "subjects": [],
  "title": "Microfluidic platform for rapid passive preparation of complex biological matrices in point-of-care testing",
  "title_text": "Microfluidic platform for rapid passive preparation of complex biological matrices in point-of-care testing",
  "type": "peer-reviewed",
  "updated_at": "2026-10-31T12:21:11Z",
  "url": "https://research.draconitic.com/paper/8edzby316xzv6",
  "venue": "Scientific Reports",
  "versions": []
}