154 research outputs found

    Gene expression profile of cervical and skin tissues from human papillomavirus type 16 E6 transgenic mice

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    <p>Abstract</p> <p>Background</p> <p>Although K14E6 transgenic mice develop spontaneous tumors of the skin epithelium, no spontaneous reproductive tract malignancies arise, unless the transgenic mice were treated chronically with 17β-estradiol. These findings suggest that E6 performs critical functions in normal adult cervix and skin, highlighting the need to define E6-controlled transcriptional programs in these tissues.</p> <p>Methods</p> <p>We evaluated the expression profile of 14,000 genes in skin or cervix from young K14E6 transgenic mice compared with nontransgenic. To identify differentially expressed genes a linear model was implemented using R and the LIMMA package. Two criteria were used to select the set of relevant genes. First a set of genes with a Log-odds ≥ 3 were selected. Then, a hierarchical search of genes was based on Log Fold Changes.</p> <p>Results</p> <p>Microarray analysis identified a total of 676 and 1154 genes that were significantly up and down-regulated, respectively, in skin from K14E6 transgenic mice. On the other hand, in the cervix from K14E6 transgenic mice we found that only 97 and 252 genes were significantly up and down-regulated, respectively. One of the most affected processes in the skin from K14E6 transgenic mice was the cell cycle. We also found that skin from transgenic mice showed down-regulation of pro-apoptotic genes and genes related to the immune response. In the cervix of K14E6 transgenic mice, we could not find affected any gene related to the cell cycle and apoptosis pathways but did observe alterations in the expression of immune response genes. Pathways such as angiogenesis, cell junction and epidermis development, also were altered in their gene expression profiles in both tissues.</p> <p>Conclusion</p> <p>Expression of the HPV16 E6 oncoprotein in our model alters expression of genes that fell into several functional groups providing insights into pathways by which E6 deregulate cell cycle progression, apoptosis, the host resistance to infection and immune function, providing new opportunities for early diagnostic markers and therapeutic drug targets.</p

    How long do nosocomial pathogens persist on inanimate surfaces? A systematic review

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    BACKGROUND: Inanimate surfaces have often been described as the source for outbreaks of nosocomial infections. The aim of this review is to summarize data on the persistence of different nosocomial pathogens on inanimate surfaces. METHODS: The literature was systematically reviewed in MedLine without language restrictions. In addition, cited articles in a report were assessed and standard textbooks on the topic were reviewed. All reports with experimental evidence on the duration of persistence of a nosocomial pathogen on any type of surface were included. RESULTS: Most gram-positive bacteria, such as Enterococcus spp. (including VRE), Staphylococcus aureus (including MRSA), or Streptococcus pyogenes, survive for months on dry surfaces. Many gram-negative species, such as Acinetobacter spp., Escherichia coli, Klebsiella spp., Pseudomonas aeruginosa, Serratia marcescens, or Shigella spp., can also survive for months. A few others, such as Bordetella pertussis, Haemophilus influenzae, Proteus vulgaris, or Vibrio cholerae, however, persist only for days. Mycobacteria, including Mycobacterium tuberculosis, and spore-forming bacteria, including Clostridium difficile, can also survive for months on surfaces. Candida albicans as the most important nosocomial fungal pathogen can survive up to 4 months on surfaces. Persistence of other yeasts, such as Torulopsis glabrata, was described to be similar (5 months) or shorter (Candida parapsilosis, 14 days). Most viruses from the respiratory tract, such as corona, coxsackie, influenza, SARS or rhino virus, can persist on surfaces for a few days. Viruses from the gastrointestinal tract, such as astrovirus, HAV, polio- or rota virus, persist for approximately 2 months. Blood-borne viruses, such as HBV or HIV, can persist for more than one week. Herpes viruses, such as CMV or HSV type 1 and 2, have been shown to persist from only a few hours up to 7 days. CONCLUSION: The most common nosocomial pathogens may well survive or persist on surfaces for months and can thereby be a continuous source of transmission if no regular preventive surface disinfection is performed

    Combined Tevatron upper limit on gg->H->W+W- and constraints on the Higgs boson mass in fourth-generation fermion models

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    Report number: FERMILAB-PUB-10-125-EWe combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg->H->W+W- in p=pbar collisions at the Fermilab Tevatron Collider at sqrt{s}=1.96 TeV. With 4.8 fb-1 of integrated luminosity analyzed at CDF and 5.4 fb-1 at D0, the 95% Confidence Level upper limit on \sigma(gg->H) x B(H->W+W-) is 1.75 pb at m_H=120 GeV, 0.38 pb at m_H=165 GeV, and 0.83 pb at m_H=200 GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% Confidence Level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.We combine results from searches by the CDF and D0 collaborations for a standard model Higgs boson (H) in the process gg→H→W+W- in pp̅ collisions at the Fermilab Tevatron Collider at √s=1.96  TeV. With 4.8  fb-1 of integrated luminosity analyzed at CDF and 5.4  fb-1 at D0, the 95% confidence level upper limit on σ(gg→H)×B(H→W+W-) is 1.75 pb at mH=120  GeV, 0.38 pb at mH=165  GeV, and 0.83 pb at mH=200  GeV. Assuming the presence of a fourth sequential generation of fermions with large masses, we exclude at the 95% confidence level a standard-model-like Higgs boson with a mass between 131 and 204 GeV.Peer reviewe

    Jet energy measurement and its systematic uncertainty in proton–proton collisions at √s=7 TeV with the ATLAS detector

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    The jet energy scale (JES) and its systematic uncertainty are determined for jets measured with the ATLAS detector using proton–proton collision data with a centre-of-mass energy of √s=7 TeV corresponding to an integrated luminosity of 4.7 fb −1. Jets are reconstructed from energy deposits forming topological clusters of calorimeter cells using the anti-kt algorithm with distance parameters R=0.4 or R=0.6, and are calibrated using MC simulations. A residual JES correction is applied to account for differences between data and MC simulations. This correction and its systematic uncertainty are estimated using a combination of in situ techniques exploiting the transverse momentum balance between a jet and a reference object such as a photon or a Z boson, for 20≤pTjet1 TeV. The calibration of forward jets is derived from dijet pT balance measurements. The resulting uncertainty reaches its largest value of 6 % for low-pT jets at |η|=4.5. Additional JES uncertainties due to specific event topologies, such as close-by jets or selections of event samples with an enhanced content of jets originating from light quarks or gluons, are also discussed. The magnitude of these uncertainties depends on the event sample used in a given physics analysis, but typically amounts to 0.5–3 %
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