137 research outputs found

    An inkjet printed, roll-coated digital microfluidic device for inexpensive, miniaturized diagnostic assays

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    The diagnosis of infectious disease is typically carried out at the point-of-care (POC) using the lateral flow assay (LFA). While cost-effective and portable, LFAs often lack the clinical sensitivity and specificity required for accurate diagnoses. In response to this challenge, we introduce a new digital microfluidic (DMF) platform fabricated using a custom inkjet printing and roll-coating process that is scalable to mass production. The performance of the new devices is on par with that of traditional DMF devices fabricated in a cleanroom, with a materials cost for the new devices of only US $0.63 per device. To evaluate the usefulness of the new platform, we performed a 13-step rubella virus (RV) IgG immunoassay on the inkjet printed, roll-coated devices, which yielded a limit of detection of 0.02 IU mL^(−1), well below the diagnostic cut-off of 10 IU mL^(−1) for RV infection and immunity. We propose that this represents a breakthrough for DMF, lowering the costs to a level such that the new platforms will be an attractive alternative to LFAs for the diagnosis of infectious disease at the POC

    An inkjet printed, roll-coated digital microfluidic device for inexpensive, miniaturized diagnostic assays

    Get PDF
    The diagnosis of infectious disease is typically carried out at the point-of-care (POC) using the lateral flow assay (LFA). While cost-effective and portable, LFAs often lack the clinical sensitivity and specificity required for accurate diagnoses. In response to this challenge, we introduce a new digital microfluidic (DMF) platform fabricated using a custom inkjet printing and roll-coating process that is scalable to mass production. The performance of the new devices is on par with that of traditional DMF devices fabricated in a cleanroom, with a materials cost for the new devices of only US $0.63 per device. To evaluate the usefulness of the new platform, we performed a 13-step rubella virus (RV) IgG immunoassay on the inkjet printed, roll-coated devices, which yielded a limit of detection of 0.02 IU mL^(−1), well below the diagnostic cut-off of 10 IU mL^(−1) for RV infection and immunity. We propose that this represents a breakthrough for DMF, lowering the costs to a level such that the new platforms will be an attractive alternative to LFAs for the diagnosis of infectious disease at the POC

    Signatures of delayed detonation, asymmetry, and electron capture in the mid-infrared spectra of supernovae 2003hv and 2005df

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    We present mid-infrared (5.2-15.2 μm) spectra of the Type Ia supernovae (SNe Ia) 2003hv and 2005df observed with the Spitzer Space Telescope. These are the first observed mid-infrared spectra of thermonuclear supernovae, and show strong emission from fine-structure lines of Ni, Co, S, and Ar. The detection of Ni emission in SN 2005df 135 days after the explosion provides direct observational evidence of high-density nuclear burning forming a significant amount of stable Ni in a SN Ia. The SN 2005df Ar lines also exhibit a two-pronged emission profile, implying that the Ar emission deviates significantly from spherical symmetry. The spectrum of SN 2003hv also shows signs of asymmetry, exhibiting blueshifted [Co III], which matches the blueshift of [Fe II ] lines in nearly coeval near-infrared spectra. Finally, local thermodynamic equilibrium abundance estimates for the yield of radioactive ^(56)Ni give M^(56)Ni ≈ 0.5 M⊙, for SN 2003hv, but only M^(56)Ni ≈ 0.13-0.22 M⊙ for the apparently subluminous SN 2005df, supporting the notion that the luminosity of SNe Ia is primarily a function of the radioactive ^(56)Ni yield. The observed emission-line profiles in the SN 2005df spectrum indicate a chemically stratified ejecta structure, which matches the predictions of delayed detonation (DD) models, but is entirely incompatible with current three-dimensional deflagration models. Furthermore, the degree that this layering persists to the innermost regions of the supernova is difficult to explain even in a DD scenario, where the innermost ejecta are still the product of deflagration burning. Thus, while these results are roughly consistent with a delayed detonation, it is clear that a key piece of physics is still missing from our understanding of the earliest phases of SN Ia explosions

    Multi-Messenger Astronomy with Extremely Large Telescopes

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    The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network.Comment: White paper submitted to the Astro2020 Decadal Surve

    A Tabletop X-Ray Tomography Instrument for Nanometer-Scale Imaging: Integration of a Scanning Electron Microscope with a Transition-Edge Sensor Spectrometer

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    X-ray nanotomography is a powerful tool for the characterization of nanoscale materials and structures, but is difficult to implement due to competing requirements on X-ray flux and spot size. Due to this constraint, state-of-the-art nanotomography is predominantly performed at large synchrotron facilities. Compact X-ray nanotomography tools operated in standard analysis laboratories exist, but are limited by X-ray optics and destructive sample preparation techniques. We present a laboratory-scale nanotomography instrument that achieves nanoscale spatial resolution while changing the limitations of conventional tomography tools. The instrument combines the electron beam of a scanning electron microscope (SEM) with the precise, broadband X-ray detection of a superconducting transition-edge sensor (TES) microcalorimeter. The electron beam generates a highly focused X-ray spot in a metal target, while the TES spectrometer isolates target photons with high signal-to-noise. This combination of a focused X-ray spot, energy-resolved X-ray detection, and unique system geometry enable nanoscale, element-specific X-ray imaging in a compact footprint. The proof-of-concept for this approach to X-ray nanotomography is demonstrated by imaging 160 nm features in three dimensions in a Cu-SiO2 integrated circuit, and a path towards finer resolution and enhanced imaging capabilities is discussed.Comment: The following article has been submitted to Physical Review Applie

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment
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