Close Menu
geekfence.comgeekfence.com
    What's Hot

    Just 3 in 10 Workers Believe Their Role Is Safe from AI Over the Next Decade

    July 28, 2026

    Teaching Coding When AI Can Write the Code – O’Reilly

    July 28, 2026

    FCC exempts new Starlink devices from router ban

    July 28, 2026
    Facebook X (Twitter) Instagram
    • About Us
    • Contact Us
    Facebook Instagram
    geekfence.comgeekfence.com
    • Home
    • UK Tech News
    • AI
    • Big Data
    • Cyber Security
      • Cloud Computing
      • iOS Development
    • IoT
    • Mobile
    • Software
      • Software Development
      • Software Engineering
    • Technology
      • Green Technology
      • Nanotechnology
    • Telecom
    geekfence.comgeekfence.com
    Home»Nanotechnology»Diagnosing brain cancer without a biopsy – Physics World
    Nanotechnology

    Diagnosing brain cancer without a biopsy – Physics World

    AdminBy AdminDecember 11, 2025No Comments3 Mins Read6 Views
    Facebook Twitter Pinterest LinkedIn Telegram Tumblr Email
    Diagnosing brain cancer without a biopsy – Physics World
    Share
    Facebook Twitter LinkedIn Pinterest Email


    A black phosphorus-based system detects micro-RNA in aqueous humor, enabling safe diagnosis of Primary Central Nervous System Lymphoma

    RNA chain

    RNA chain (Courtesy: iStock/Christoph Burgstedt)

    Early diagnosis of primary central nervous system lymphoma (PCNSL) remains challenging because brain biopsies are invasive and imaging often lacks molecular specificity. A team led by researchers at Shenzhen University has now developed a minimally invasive fibre-optic plasmonic sensor capable of detecting PCNSL-associated microRNAs in the eye’s aqueous humor with attomolar sensitivity.

    At the heart of the approach is a black phosphorus (BP)–engineered surface plasmon resonance (SPR) interface. An ultrathin BP layer is deposited on a gold-coated fiber tip. Because of the work-function difference between BP and gold, electrons transfer from BP into the Au film, creating a strongly enhanced local electric field at the metal–semiconductor interface. This BP–Au charge-transfer nano-interface amplifies refractive-index changes at the surface far more efficiently than conventional metal-only SPR chips, enabling the detection of molecular interactions that would otherwise be too subtle to resolve and pushing the limit of detection down to 21 attomolar without nucleic-acid amplification. The BP layer also provides a high-area, biocompatible surface for immobilizing RNA reporters.

    To achieve sequence specificity, the researchers integrated CRISPR-Cas13a, an RNA-guided nuclease that becomes catalytically active only when its target sequence is perfectly matched to a designed CRISPR RNA (crRNA). When the target microRNA (miR-21) is present, activated Cas13a cleaves RNA reporters attached to the BP-modified fiber surface, releasing gold nanoparticles and reducing the local refractive index. The resulting optical shift is read out in real time through the SPR response of the BP-enhanced fiber probe, providing single-nucleotide-resolved detection directly on the plasmonic interface.

    With this combined strategy, the sensor achieved a limit of detection of 21 attomolar in buffer and successfully distinguished single-base-mismatched microRNAs. In tests on aqueous-humor samples from patients with PCNSL, the CRISPR-BP-FOSPR assay produced results that closely matched clinical qPCR data, despite operating without any amplification steps.

    Because aqueous-humor aspiration is a minimally invasive ophthalmic procedure, this BP-driven plasmonic platform may offer a practical route for early PCNSL screening, longitudinal monitoring, and potentially the diagnosis of other neurological diseases reflected in eye-fluid biomarkers. More broadly, the work showcases how black-phosphorus-based charge-transfer interfaces can be used to engineer next-generation, fibre-integrated biosensors that combine extreme sensitivity with molecular precision.

    Do you want to learn more about this topic?

    Theoretical and computational tools to model multistable gene regulatory networks by Federico Bocci, Dongya Jia, Qing Nie, Mohit Kumar Jolly and José Onuchic (2023)



    Source link

    Share. Facebook Twitter Pinterest LinkedIn Tumblr Email

    Related Posts

    Hidden spin-valley locking stabilizes nanosecond spin polarization in 2D perovskites

    July 28, 2026

    Tescan Unveils the New CLARA to Help Researchers See More at the Nanoscale

    July 26, 2026

    New programmable photonic chip can control how fast light moves

    July 25, 2026

    Immunostimulatory lipogel implant enhances cancer immunotherapy

    July 23, 2026

    The physics of protein condensates – Physics World

    July 22, 2026

    Invisible Microbes ‘Mining’ Toxic Waste in the Flinders Ranges

    July 21, 2026
    Top Posts

    Understanding U-Net Architecture in Deep Learning

    November 25, 202567 Views

    The Next Paradigm in Efficient Inference Scaling – The Berkeley Artificial Intelligence Research Blog

    May 16, 202636 Views

    Hard-braking events as indicators of road segment crash risk

    January 14, 202634 Views
    Don't Miss

    Just 3 in 10 Workers Believe Their Role Is Safe from AI Over the Next Decade

    July 28, 2026

    Just three in ten Irish workers (30%) believe their role is safe from AI or…

    Teaching Coding When AI Can Write the Code – O’Reilly

    July 28, 2026

    FCC exempts new Starlink devices from router ban

    July 28, 2026

    Posit AI Blog: TensorFlow and Keras 2.9

    July 28, 2026
    Stay In Touch
    • Facebook
    • Instagram
    About Us

    At GeekFence, we are a team of tech-enthusiasts, industry watchers and content creators who believe that technology isn’t just about gadgets—it’s about how innovation transforms our lives, work and society. We’ve come together to build a place where readers, thinkers and industry insiders can converge to explore what’s next in tech.

    Our Picks

    Just 3 in 10 Workers Believe Their Role Is Safe from AI Over the Next Decade

    July 28, 2026

    Teaching Coding When AI Can Write the Code – O’Reilly

    July 28, 2026

    Subscribe to Updates

    Please enable JavaScript in your browser to complete this form.
    Loading
    • About Us
    • Contact Us
    • Disclaimer
    • Privacy Policy
    • Terms and Conditions
    © 2026 Geekfence.All Rigt Reserved.

    Type above and press Enter to search. Press Esc to cancel.