135 research outputs found

    Automated Discrimination of Pathological Regions in Tissue Images: Unsupervised Clustering vs Supervised SVM Classification

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    Recognizing and isolating cancerous cells from non pathological tissue areas (e.g. connective stroma) is crucial for fast and objective immunohistochemical analysis of tissue images. This operation allows the further application of fully-automated techniques for quantitative evaluation of protein activity, since it avoids the necessity of a preventive manual selection of the representative pathological areas in the image, as well as of taking pictures only in the pure-cancerous portions of the tissue. In this paper we present a fully-automated method based on unsupervised clustering that performs tissue segmentations highly comparable with those provided by a skilled operator, achieving on average an accuracy of 90%. Experimental results on a heterogeneous dataset of immunohistochemical lung cancer tissue images demonstrate that our proposed unsupervised approach overcomes the accuracy of a theoretically superior supervised method such as Support Vector Machine (SVM) by 8%

    Measurement of the B0-anti-B0-Oscillation Frequency with Inclusive Dilepton Events

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    The B0B^0-Bˉ0\bar B^0 oscillation frequency has been measured with a sample of 23 million \B\bar B pairs collected with the BABAR detector at the PEP-II asymmetric B Factory at SLAC. In this sample, we select events in which both B mesons decay semileptonically and use the charge of the leptons to identify the flavor of each B meson. A simultaneous fit to the decay time difference distributions for opposite- and same-sign dilepton events gives Δmd=0.493±0.012(stat)±0.009(syst)\Delta m_d = 0.493 \pm 0.012{(stat)}\pm 0.009{(syst)} ps1^{-1}.Comment: 7 pages, 1 figure, submitted to Physical Review Letter

    Visualizing Cholesterol in the Brain by On-Tissue Derivatization and Quantitative Mass Spectrometry Imaging.

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    Despite being a critical molecule in the brain, mass spectrometry imaging (MSI) of cholesterol has been under-reported compared to other lipids due to the difficulty in ionizing the sterol molecule. In the present work, we have employed an on-tissue enzyme-assisted derivatization strategy to improve detection of cholesterol in brain tissue sections. We report distribution and levels of cholesterol across specific structures of the mouse brain, in a model of Niemann-Pick type C1 disease, and during brain development. MSI revealed that in the adult mouse, cholesterol is the highest in the pons and medulla and how its distribution changes during development. Cholesterol was significantly reduced in the corpus callosum and other brain regions in the Npc1 null mouse, confirming hypomyelination at the molecular level. Our study demonstrates the potential of MSI to the study of sterols in neuroscience

    Measurement of the CP-Violating Asymmetry Amplitude sin2β\beta

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    We present results on time-dependent CP-violating asymmetries in neutral B decays to several CP eigenstates. The measurements use a data sample of about 88 million Y(4S) --> B Bbar decays collected between 1999 and 2002 with the BABAR detector at the PEP-II asymmetric-energy B Factory at SLAC. We study events in which one neutral B meson is fully reconstructed in a final state containing a charmonium meson and the other B meson is determined to be either a B0 or B0bar from its decay products. The amplitude of the CP-violating asymmetry, which in the Standard Model is proportional to sin2beta, is derived from the decay-time distributions in such events. We measure sin2beta = 0.741 +/- 0.067 (stat) +/- 0.033 (syst) and |lambda| = 0.948 +/- 0.051 (stat) +/- 0.017 (syst). The magnitude of lambda is consistent with unity, in agreement with the Standard Model expectation of no direct CP violation in these modes

    Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC

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    The Physics of the B Factories

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