Prompt atmospheric neutrino fluxes: perturbative QCD models and nuclear effects

We evaluate the prompt atmospheric neutrino flux at high energies using three different frameworks for calculating the heavy quark production cross section in QCD: NLO perturbative QCD, $k_T$ factorization including low-$x$ resummation, and the dipole model including parton saturation. We use QCD parameters, the value for the charm quark mass and the range for the factorization and renormalization scales that provide the best description of the total charm cross section measured at fixed target experiments, at RHIC and at LHC. Using these parameters we calculate differential cross sections for charm and bottom production and compare with the latest data on forward charm meson production from LHCb at $7$ TeV and at $13$ TeV, finding good agreement with the data. In addition, we investigate the role of nuclear shadowing by including nuclear parton distribution functions (PDF) for the target air nucleus using two different nuclear PDF schemes. Depending on the scheme used, we find the reduction of the flux due to nuclear effects varies from $10\%$ to $50 \%$ at the highest energies. Finally, we compare our results with the IceCube limit on the prompt neutrino flux, which is already providing valuable information about some of the QCD models.Comment: 61 pages, 25 figures, 11 table

Immunogenecity of Modified Alkane Polymers Is Mediated through TLR1/2 Activation

Background: With the advancement of biomedical technology, artificial materials have been developed to replace diseased, damaged or nonfunctional body parts. Among such materials, ultra high molecular weight alkane or modified alkyl polymers have been extensively used in heart valves, stents, pacemakers, ear implants, as well as total joint replacement devices. Although much research has been undertaken to design the most non-reactive biologically inert polyethylene derivatives, strong inflammatory responses followed by rejection and failure of the implant have been noted. Methodology/Principal Findings: Purification of the alkane polymers from the site of inflammation revealed extensive ‘‘in vivo’ ’ oxidation as detected by fourier transformed infra-red spectroscopy. Herein, we report the novel observation that oxidized alkane polymers induced activation of TLR1/2 pathway as determined by ligand dependent changes in intrinsic tyrosine fluorescence intensity and NF-kB luciferase gene assays. Oxidized polymers were very effective in activating dendritic cells and inducing secretion of pro-inflammatory cytokines. Molecular docking of the oxidized alkanes designated ligand specificity and polymeric conformations fitting into the TLR1/2 binding grooves

Loss of protein kinase C delta alters mammary gland development and apoptosis

As apoptotic pathways are commonly deregulated in breast cancer, exploring how mammary gland cell death is regulated is critical for understanding human disease. We show that primary mammary epithelial cells from protein kinase C delta (PKCδ) −/− mice have a suppressed response to apoptotic agents in vitro. In the mammary gland in vivo, apoptosis is critical for ductal morphogenesis during puberty and involution following lactation. We have explored mammary gland development in the PKCδ −/− mouse during these two critical windows. Branching morphogenesis was altered in 4- to 6-week-old PKCδ −/− mice as indicated by reduced ductal branching; however, apoptosis and proliferation in the terminal end buds was unaltered. Conversely, activation of caspase-3 during involution was delayed in PKCδ −/− mice, but involution proceeded normally. The thymus also undergoes apoptosis in response to physiological signals. A dramatic suppression of caspase-3 activation was observed in the thymus of PKCδ −/− mice treated with irradiation, but not mice treated with dexamethasone, suggesting that there are both target- and tissue-dependent differences in the execution of apoptotic pathways in vivo. These findings highlight a role for PKCδ in both apoptotic and nonapoptotic processes in the mammary gland and underscore the redundancy of apoptotic pathways in vivo

Dynamics of ampicillin-resistant Enterococcus faecium clones colonizing hospitalized patients: data from a prospective observational study

<p>Abstract</p> <p>Background</p> <p>Little is known about the dynamics of colonizing <it>Enterococcus faecium </it>clones during hospitalization, invasive infection and after discharge.</p> <p>Methods</p> <p>In a prospective observational study we compared intestinal <it>E. faecium </it>colonization in three patient cohorts: 1) Patients from the Hematology Unit at the University Hospital Basel (UHBS), Switzerland, were investigated by weekly rectal swabs (RS) during hospitalization (group 1a, n = 33) and monthly after discharge (group 1b, n = 21). 2) Patients from the Intensive Care Unit (ICU) at the University Medical Center Utrecht, the Netherlands (group 2, n = 25) were swabbed weekly. 3) Patients with invasive <it>E. faecium </it>infection at UHBS were swabbed at the time of infection (group 3, n = 22). From each RS five colonies with typical <it>E</it>. <it>faecium </it>morphology were picked. Species identification was confirmed by PCR and ampicillin-resistant <it>E. faecium </it>(ARE) isolates were typed using Multiple Locus Variable Number Tandem Repeat Analysis (MLVA). The Simpson's Index of Diversity (SID) was calculated.</p> <p>Results</p> <p>Out of 558 ARE isolates from 354 RS, MT159 was the most prevalent clone (54%, 100%, 52% and 83% of ARE in groups 1a, 1b, 2 and 3, respectively). Among hematological inpatients 13 (40%) had ARE. During hospitalization, the SID of MLVA-typed ARE decreased from 0.745 [95%CI 0.657-0.833] in week 1 to 0.513 [95%CI 0.388-0.637] in week 3. After discharge the only detected ARE was MT159 in 3 patients. In the ICU (group 2) almost all patients (84%) were colonized with ARE. The SID increased significantly from 0.373 [95%CI 0.175-0.572] at week 1 to a maximum of 0.808 [95%CI 0.768-0.849] at week 3 due to acquisition of multiple ARE clones. All 16 patients with invasive ARE were colonized with the same MLVA clone (<it>p </it>< 0.001).</p> <p>Conclusions</p> <p>In hospitalized high-risk patients MT159 is the most frequent colonizer and cause of invasive <it>E. faecium </it>infections. During hospitalization, ASE are quickly replaced by ARE. Diversity of ARE increases on units with possible cross-transmission such as ICUs. After hospitalization ARE are lost with the exception of MT159. In invasive infections, the invasive clone is the predominant gut colonizer.</p

Integrated multi-scale data analytics and machine learning for the distribution grid

We consider the field of machine learning and where it is both useful, and not useful, for the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors - such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals - such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop. This paper describes benefits and limits of present machine-learning applications for use on the grid and presents a series of case studies that illustrate the potential benefits of developing advanced local multi-variate analytics machine-learning-based applications