An Improved Model for Relativistic Solar Proton Acceleration applied to the 2005 January 20 and Earlier Events

This paper presents results on modelling the ground level response of the higher energy protons for the 2005 January 20 ground level enhancement (GLE). This event, known as GLE 69, produced the highest intensity of relativistic solar particles since the famous event on 1956 February 23. The location of recent X-ray and gamma-ray emission (N14 W61) was near to Sun-Earth connecting magnetic field lines, thus providing the opportunity to directly observe the acceleration source from Earth. We restrict our analysis to protons of energy greater than 450 MeV to avoid complications arising from transport processes that can affect the propagation of low energy protons. In light of this revised approach we have reinvestigated two previous GLEs: those of 2000 July 14 (GLE 59) and 2001 April 15 (GLE 60). Within the limitations of the spectral forms employed, we find that from the peak (06:55 UT) to the decline (07:30 UT) phases of GLE 69, neutron monitor observations from 450 MeV to 10 GeV are best fitted by the Gallegos-Cruz & Perez-Peraza stochastic acceleration model. In contrast, the Ellison & Ramaty spectra did not fit the neutron monitor observations as well. This result suggests that for GLE 69, a stochastic process cannot be discounted as a mechanism for relativistic particle acceleration, particularly during the initial stages of this solar event. For GLE 59 we find evidence that more than one acceleration mechanism was present, consistent with both shock and stochastic acceleration processes dominating at different times of the event. For GLE 60 we find that Ellison & Ramaty spectra better represent the neutron monitor observations compared to stochastic acceleration spectra. The results for GLEs 59 and 60 are in agreement with our previous work.Comment: 42 pages, 10 figures, 10 tables, published in ApJ, August 200

Cellular Arrays (US Patent Application)

The present invention relates to characterizing transcription within cells. In particular, the present invention provides transfected cell arrays (e.g., two-dimensional and/or three-dimensional arrays) and systems, kits and methods utilizing the same (e.g., for transcriptional activity characterization). Compositions and methods of the present invention find use in, among other things, research, drug discovery and clinical (e.g., diagnostic, preventative and therapeutic) applications

Relativistic Proton Production During the 14 July 2000 Solar Event: The Case for Multiple Source Mechanisms

Protons accelerated to relativistic energies by transient solar and interplanetary phenomena caused a ground-level cosmic ray enhancement on 14 July 2000, Bastille Day. Near-Earth spacecraft measured the proton flux directly and ground-based observatories measured the secondary responses to higher energy protons. We have modelled the arrival of these relativistic protons at Earth using a technique which deduces the spectrum, arrival direction and anisotropy of the high-energy protons that produce increased responses in neutron monitors. To investigate the acceleration processes involved we have employed theoretical shock and stochastic acceleration spectral forms in our fits to spacecraft and neutron monitor data. During the rising phase of the event (10:45 UT and 10:50 UT) we find that the spectrum between 140 MeV and 4 GeV is best fitted by a shock acceleration spectrum. In contrast, the spectrum at the peak (10:55 UT and 11:00 UT) and in the declining phase (11:40 UT) is best fitted with a stochastic acceleration spectrum. We propose that at least two acceleration processes were responsible for the production of relativistic protons during the Bastille Day solar event: (1) protons were accelerated to relativistic energies by a shock, presumably a coronal mass ejection (CME). (2) protons were also accelerated to relativistic energies by stochastic processes initiated by magnetohydrodynamic (MHD) turbulence.Comment: 38 pages, 9 figures, accepted for publication in the Astrophysical Journal, January, 200

Dynamics of An Underdamped Josephson Junction Ladder

We show analytically that the dynamical equations for an underdamped ladder of coupled small Josephson junctions can be approximately reduced to the discrete sine-Gordon equation. As numerical confirmation, we solve the coupled Josephson equations for such a ladder in a magnetic field. We obtain discrete-sine-Gordon-like IV characteristics, including a flux flow and a ``whirling'' regime at low and high currents, and voltage steps which represent a lock-in between the vortex motion and linear ``phasons'', and which are quantitatively predicted by a simple formula. At sufficiently high anisotropy, the fluxons on the steps propagate ballistically.Comment: 11pages, latex, no figure

Bioluminescence Imaging for Assessment and Normalization in Transfected Cell Arrays

Transfected cell arrays (TCAs) represent a high-throughput technique to correlate gene expression with functional cell responses. Despite advances in TCAs, improvements are needed for the widespread application of this technology. We have developed a TCA that combines a two-plasmid system and dual-bioluminescence imaging to quantitatively normalize for variability in transfection and increase sensitivity. The two-plasmids consist of: (i) normalization plasmid present within each spot, and (ii) functional plasmid that varies between spots, responsible for the functional endpoint of the array. Bioluminescence imaging of dual-luciferase reporters (renilla, firefly luciferase) provides sensitive and quantitative detection of cellular response, with minimal post-transfection processing. The array was applied to quantify estrogen receptor α (ERα) activity in MCF-7 breast cancer cells. A plasmid containing an ERα-regulated promoter directing firefly luciferase expression was mixed with a normalization plasmid, complexed with cationic lipids and deposited into an array. ER induction mimicked results obtained through traditional assays methods, with estrogen inducing luciferase expression 10-fold over the antiestrogen fulvestrant or vehicle. Furthermore, the array captured a dose response to estrogen, demonstrating the sensitivity of bioluminescence quantification. This system provides a tool for basic science research, with potential application for the development of patient specific therapies

Bioluminescence Imaging for Assessment and Normalization in Transfected Cell Arrays

Transfected cell arrays (TCAs) represent a high-throughput technique to correlate gene expression with functional cell responses. Despite advances in TCAs, improvements are needed for the widespread application of this technology. We have developed a TCA that combines a two-plasmid system and dual-bioluminescence imaging to quantitatively normalize for variability in transfection and increase sensitivity. The two-plasmids consist of: (i) normalization plasmid present within each spot, and (ii) functional plasmid that varies between spots, responsible for the functional endpoint of the array. Bioluminescence imaging of dual-luciferase reporters (renilla, firefly luciferase) provides sensitive and quantitative detection of cellular response, with minimal post-transfection processing. The array was applied to quantify estrogen receptor α (ERα) activity in MCF-7 breast cancer cells. A plasmid containing an ERα-regulated promoter directing firefly luciferase expression was mixed with a normalization plasmid, complexed with cationic lipids and deposited into an array. ER induction mimicked results obtained through traditional assays methods, with estrogen inducing luciferase expression 10-fold over the antiestrogen fulvestrant or vehicle. Furthermore, the array captured a dose response to estrogen, demonstrating the sensitivity of bioluminescence quantification. This system provides a tool for basic science research, with potential application for the development of patient specific therapies

Docosatetraenoyl LPA is elevated in exhaled breath condensate in idiopathic pulmonary fibrosis

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal disease with no effective medical therapies. Recent research has focused on identifying the biological processes essential to the development and progression of fibrosis, and on the mediators driving these processes. Lysophosphatidic acid (LPA), a biologically active lysophospholipid, is one such mediator. LPA has been found to be elevated in bronchoalveolar lavage (BAL) fluid of IPF patients, and through interaction with its cell surface receptors, it has been shown to drive multiple biological processes implicated in the development of IPF. Accordingly, the first clinical trial of an LPA receptor antagonist in IPF has recently been initiated. In addition to being a therapeutic target, LPA also has potential to be a biomarker for IPF. There is increasing interest in exhaled breath condensate (EBC) analysis as a non-invasive method for biomarker detection in lung diseases, but to what extent LPA is present in EBC is not known. Methods: In this study, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess for the presence of LPA in the EBC and plasma from 11 IPF subjects and 11 controls. Results: A total of 9 different LPA species were detectable in EBC. Of these, docosatetraenoyl (22:4) LPA was significantly elevated in the EBC of IPF subjects when compared to controls (9.18 pM vs. 0.34 pM; p = 0.001). A total of 13 different LPA species were detectable in the plasma, but in contrast to the EBC, there were no statistically significant differences in plasma LPA species between IPF subjects and controls. Conclusions: These results demonstrate that multiple LPA species are detectable in EBC, and that 22:4 LPA levels are elevated in the EBC of IPF patients. Further research is needed to determine the significance of this elevation of 22:4 LPA in IPF EBC, as well as its potential to serve as a biomarker for disease severity and/or progression

Analytical results for coupled map lattices with long-range interactions

We obtain exact analytical results for lattices of maps with couplings that decay with distance as $r^{-\alpha}$. We analyze the effect of the coupling range on the system dynamics through the Lyapunov spectrum. For lattices whose elements are piecewise linear maps, we get an algebraic expression for the Lyapunov spectrum. When the local dynamics is given by a nonlinear map, the Lyapunov spectrum for a completely synchronized state is analytically obtained. The critical lines characterizing the synchronization transition are determined from the expression for the largest transversal Lyapunov exponent. In particular, it is shown that in the thermodynamical limit, such transition is only possible for sufficiently long-range interactions, namely, for $\alpha\le alpha_c<d$, where $d$ is the lattice dimension.Comment: 4 pages, 2 figures, corrections included. Phys. Rev. E 68, 045202(R) (2003); correction in pres

Inter-rater reliability of the EPUAP pressure ulcer classification system using photographs

Background. Many classification systems for grading pressure ulcers are discussed in the literature. Correct identification and classification of a pressure ulcer is important for accurate reporting of the magnitude of the problem, and for timely prevention. The reliability of pressure ulcer classification systems has rarely been tested. Aims and objectives. The purpose of this paper is to examine the inter-rater reliability of classifying pressure ulcers according to the European Pressure Ulcer Advisory Panel classification system when using pressure ulcer photographs.Design. Survey was among pressure ulcer experts.Methods. Fifty-six photographs were presented to 44 pressure ulcer experts. The experts classified the lesions as normal skin, blanchable erythema, pressure ulcer (four grades) or incontinence lesion. Inter-rater reliability was calculated.Results. The multirater-Kappa for the entire group of experts was 0.80 (P &lt; 0.001).Various groups of experts obtained comparable results. Differences in classifications are mainly limited to 1 degree of difference. Incontinence lesions are most often confused with grade 2 (blisters) and grade 3 pressure ulcers (superficial pressure ulcers).Conclusions. The inter-rater reliability of the European Pressure Ulcer Advisory Panel classification appears to be good for the assessment of photographs by experts. The difference between an incontinence lesion and a blister or a superficial pressure ulcer does not always seem clear.Relevance to clinical practice. The ability to determine correctly whether a lesion is a pressure ulcer lesion is important to assess the effectiveness of preventive measures. In addition, the ability to make a correct distinction between pressure ulcers and incontinence lesions is important as they require different preventive measures. A faulty classification leads to mistaken measures and negative results. Photographs can be used as a practice instrument to learn to discern pressure ulcers from incontinence lesions and to get to know the different grades of pressure ulcers. The Pressure Ulcer Classification software package has been developed to facilitate learning

Deep neural networks allow expert-level brain meningioma segmentation and present potential for improvement of clinical practice

Accurate brain meningioma segmentation and volumetric assessment are critical for serial patient follow-up, surgical planning and monitoring response to treatment. Current gold standard of manual labeling is a time-consuming process, subject to inter-user variability. Fully-automated algorithms for meningioma segmentation have the potential to bring volumetric analysis into clinical and research workflows by increasing accuracy and efficiency, reducing inter-user variability and saving time. Previous research has focused solely on segmentation tasks without assessment of impact and usability of deep learning solutions in clinical practice. Herein, we demonstrate a three-dimensional convolutional neural network (3D-CNN) that performs expert-level, automated meningioma segmentation and volume estimation on MRI scans. A 3D-CNN was initially trained by segmenting entire brain volumes using a dataset of 10,099 healthy brain MRIs. Using transfer learning, the network was then specifically trained on meningioma segmentation using 806 expert-labeled MRIs. The final model achieved a median performance of 88.2% reaching the spectrum of current inter-expert variability (82.6-91.6%). We demonstrate in a simulated clinical scenario that a deep learning approach to meningioma segmentation is feasible, highly accurate and has the potential to improve current clinical practice