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Recent Developments in Magnetic Diagnostic Systems
Lee, Hakho,Shin, Tae-Hyun,Cheon, Jinwoo,Weissleder, Ralph American Chemical Society 2015 Chemical reviews Vol.115 No.19
<P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/chreay/2015/chreay.2015.115.issue-19/cr500698d/production/images/medium/cr-2014-00698d_0025.gif'></P>
Rapid detection and profiling of cancer cells in fine-needle aspirates.
Lee, Hakho,Yoon, Tae-Jong,Figueiredo, Jose-Luiz,Swirski, Filip K,Weissleder, Ralph National Academy of Sciences 2009 PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF Vol.106 No.30
<P>There is a growing need for fast, highly sensitive and quantitative technologies to detect and profile unaltered cells in biological samples. Technologies in current clinical use are often time consuming, expensive, or require considerable sample sizes. Here, we report a diagnostic magnetic resonance (DMR) sensor that combines a miniaturized NMR probe with targeted magnetic nanoparticles for detection and molecular profiling of cancer cells. The sensor measures the transverse relaxation rate of water molecules in biological samples in which target cells of interest are labeled with magnetic nanoparticles. We achieved remarkable sensitivity improvements over our prior DMR prototypes by synthesizing new nanoparticles with higher transverse relaxivity and by optimizing assay protocols. We detected as few as 2 cancer cells in 1-microL sample volumes of unprocessed fine-needle aspirates of tumors and profiled the expression of several cellular markers in <15 min.</P>
Jeun, Minhong,Park, Sungwook,Lee, Hakho,Lee, Kwan Hyi Dove Medical Press 2016 INTERNATIONAL JOURNAL OF NANOMEDICINE Vol.11 No.-
<P>Magnetic-based biosensors are attractive for on-site detection of biomarkers due to the low magnetic susceptibility of biological samples. Here, we report a highly sensitive magnetic-based biosensing system that is composed of a miniaturized nuclear magnetic resonance (NMR) device and magnetically engineered nanoferrite particles (NFPs). The sensing performance, also identified as the transverse relaxation (<I>R</I><SUB>2</SUB>) rate, of the NMR device is directly related to the magnetic properties of the NFPs. Therefore, we developed magnetically engineered NFPs (MnMg-NFP) and used them as NMR agents to exhibit a significantly improved <I>R</I><SUB>2</SUB> rate. The magnetization of the MnMg-NFPs was increased by controlling the Mn and Mg cation concentration and distribution during the synthesis process. This modification of the Mn and Mg cation directly contributed to improving the <I>R</I><SUB>2</SUB> rate. The miniaturized NMR system, combined with the magnetically engineered MnMg-NFPs, successfully detected a small amount of infectious influenza A H1N1 nucleoprotein with high sensitivity and stability.</P>
Integrated Magneto–Electrochemical Sensor for Exosome Analysis
Jeong, Sangmoo,Park, Jongmin,Pathania, Divya,Castro, Cesar M.,Weissleder, Ralph,Lee, Hakho American Chemical Society 2016 ACS NANO Vol.10 No.2
<P>Extracellular vesicles, including exosomes, are nanoscale membrane particles that carry molecular information on parental cells. They are being pursued as biomarkers of cancers that are difficult to detect or serially follow. Here we present a compact sensor technology for rapid, on-site exosome screening. The sensor is based on an integrated magneto–electrochemical assay: exosomes are immunomagnetically captured from patient samples and profiled through electrochemical reaction. By combining magnetic enrichment and enzymatic amplification, the approach enables (i) highly sensitive, cell-specific exosome detection and (ii) sensor miniaturization and scale-up for high-throughput measurements. As a proof-of-concept, we implemented a portable, eight-channel device and applied it to screen extracellular vesicles in plasma samples from ovarian cancer patients. The sensor allowed for the simultaneous profiling of multiple protein markers within an hour, outperforming conventional methods in assay sensitivity and speed.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancac3/2016/ancac3.2016.10.issue-2/acsnano.5b07584/production/images/medium/nn-2015-07584h_0006.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/nn5b07584'>ACS Electronic Supporting Info</A></P>
Integrated Biosensor for Rapid and Point-of-Care Sepsis Diagnosis
Min, Jouha,Nothing, Maria,Coble, Ben,Zheng, Hui,Park, Jongmin,Im, Hyungsoon,Weber, Georg F.,Castro, Cesar M.,Swirski, Filip K.,Weissleder, Ralph,Lee, Hakho American Chemical Society 2018 ACS NANO Vol.12 No.4
<P>Sepsis is an often fatal condition that arises when the immune response to an infection causes widespread systemic organ injury. A critical unmet need in combating sepsis is the lack of accurate early biomarkers that produce actionable results in busy clinical settings. Here, we report the development of a point-of-care platform for rapid sepsis detection. Termed IBS (integrated biosensor for sepsis), our approach leverages (i) the pathophysiological role of cytokine interleukin-3 (IL-3) in early sepsis and (ii) a hybrid magneto-electrochemical sensor for IL-3 detection. The developed platform produces test results within 1 h from native blood samples and detects IL-3 at a sensitivity of <10 pg/mL; this performance is >5-times faster and >10-times more sensitive than conventional enzyme-linked immunoadsorbent assays, the current gold standard. Using clinical samples, we show that elevated plasma IL-3 levels are associated with high organ failure rate and thus greater risk of mortality, confirming the potential of IL-3 as a sepsis diagnostic biomarker. With further system development (<I>e</I>.<I>g</I>., full automation, data security measures) and rigorous validation studies, the compact and fast IBS could be a practical clinical tool for timely diagnosis and proactive treatment of sepsis.</P> [FIG OMISSION]</BR>
Computational Optics Enables Breast Cancer Profiling in Point-of-Care Settings
Min, Jouha,Im, Hyungsoon,Allen, Matthew,McFarland, Phillip J.,Degani, Ismail,Yu, Hojeong,Normandin, Erica,Pathania, Divya,Patel, Jaymin M.,Castro, Cesar M.,Weissleder, Ralph,Lee, Hakho American Chemical Society 2018 ACS NANO Vol.12 No.9
<P>The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded health care systems are fueling the need for inexpensive, rapid, and treatment-informative diagnostics. On the basis of advances in computational optics and deep learning, we have developed a low-cost digital system, termed AIDA (artificial intelligence diffraction analysis), for breast cancer diagnosis of fine needle aspirates. Here, we show high accuracy (>90%) in (i) recognizing cells directly from diffraction patterns and (ii) classifying breast cancer types using deep-learning-based analysis of sample aspirates. The image algorithm is fast, enabling cellular analyses at high throughput (∼3 s per 1000 cells), and the unsupervised processing allows use by lower skill health care workers. AIDA can perform quantitative molecular profiling on individual cells, revealing intratumor molecular heterogeneity, and has the potential to improve cancer diagnosis and treatment. The system could be further developed for other cancers and thus find widespread use in global health.</P> [FIG OMISSION]</BR>