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  • 1
    Keywords: SPECTRA ; CANCER ; Germany ; human ; SUPPORT ; COHORT ; GENOME ; PATIENT ; DNA ; INFECTION ; SKIN ; PCR ; HPV ; BETA ; PREVALENCE ; immunosuppression ; SKIN-CANCER ; papillomaviruses ; GAMMA ; RECIPIENTS ; VIRAL LOAD ; allergy ; cutaneous HPV ; HUMAN PAPILLOMAVIRUSES ; HPV types ; 33 ; ALLERGIES ; organ transplant recipients ; RANGE ; cutaneous warts
    Abstract: BACKGROUND: A broad spectrum of human papillomaviruses (HPV) has been detected in warts from immunocompetent patients and a much more diverse range from immunosuppressed organ transplant recipients (OTR). OBJECTIVES: To determine the HPV types in warts from OTR, we assessed present infections of mucosal (alpha-PV), wart-associated (alpha-, micro- and nu-PV) and cutaneous HPV types (beta-/gamma-PV) in immunocompetent patients and OTR. Patients/methods Forty-one warts from 29 immunocompetent patients (non-OTR) and 53 warts from 33 OTR were analysed for DNA of human alpha-, beta-, gamma-, micro- and nu-PV. For frequent types viral load was determined by quantitative real-time PCR. RESULTS: Compared with non-OTR prevalence of cutaneous HPV (79% vs. 49%, P 〈 0.01) and the number of multiple infections (62% vs. 17%, P 〈 0.0001) were significantly increased. The mean viral load of the wart-associated HPV was more than 10(5)-fold higher compared with human beta-PV in both cohorts. CONCLUSIONS: The high load of wart-associated HPV suggests an active role of these viruses rather than cutaneous types in warts independent of immunosuppression; however, the substantial fraction of warts with low HPV genome copies remains to be explained.
    Type of Publication: Journal article published
    PubMed ID: 19519829
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  • 2
    Keywords: OPTIMIZATION ; PEPTIDE ; INHIBITOR ; tumor ; CELL ; INHIBITION ; KINASE ; MICROSCOPY ; MODEL ; MODELS ; SUPPORT ; SYSTEM ; SYSTEMS ; TOOL ; TUMORS ; ACTIVATION ; cell signaling ; DOMAIN ; BIOLOGY ; CYCLE ; ASSAY ; DESIGN ; PARAMETERS ; RECRUITMENT ; STRATEGIES ; lipids ; UNCERTAINTY ; parameter estimation ; systems biology ; BEHAVIOR ; AFFINITY ; AKT ; REPRESENTATION ; signaling ; PROTOCOL ; FLUORESCENCE MICROSCOPY ; PROFILES ; USA ; COMPOUND ; KINASE INHIBITOR ; lipid ; CALIFORNIA ; STATE ; STRATEGY ; A KINASE ; EXPERIMENTAL-DESIGN ; RANGE ; PI3K ; chemically induced
    Abstract: Differential equation models that describe the dynamic changes of biochemical signaling states are important tools to understand cellular behavior. An essential task in building such representations is to infer the affinities, rate constants, and other parameters of a model from actual measurement data. However, intuitive measurement protocols often fail to generate data that restrict the range of possible parameter values. Here we utilized a numerical method to iteratively design optimal live-cell fluorescence microscopy experiments in order to reveal pharmacological and kinetic parameters of a phosphatidylinositol 3,4,5-trisphosphate (PIP(3)) second messenger signaling process that is deregulated in many tumors. The experimental approach included the activation of endogenous phosphoinositide 3-kinase (PI3K) by chemically induced recruitment of a regulatory peptide, reversible inhibition of PI3K using a kinase inhibitor, and monitoring of the PI3K-mediated production of PIP(3) lipids using the pleckstrin homology (PH) domain of Akt. We found that an intuitively planned and established experimental protocol did not yield data from which relevant parameters could be inferred. Starting from a set of poorly defined model parameters derived from the intuitively planned experiment, we calculated concentration-time profiles for both the inducing and the inhibitory compound that would minimize the predicted uncertainty of parameter estimates. Two cycles of optimization and experimentation were sufficient to narrowly confine the model parameters, with the mean variance of estimates dropping more than sixty-fold. Thus, optimal experimental design proved to be a powerful strategy to minimize the number of experiments needed to infer biological parameters from a cell signaling assay.
    Type of Publication: Journal article published
    PubMed ID: 19911077
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