9 research outputs found

    Quantum Mirrors and Crossing Symmetry as Heart of Ghost Imaging

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    In this paper it is proved that the key to understanding the ghost imaging mystery are the crossing symmetric photon reactions in the nonlinear media. Hence, the laws of the plane quantum mirror (QM) and that of spherical quantum mirror, observed in the ghost imaging experiments, are obtained as natural consequences of the energy-momentum conservation laws. So, it is shown that the ghost imaging laws depend only on the energy-momentum conservation and not on the photons entanglement. The extension of these results to the ghost imaging with other kind of light is discussed. Some fundamental experiments for a decisive tests of the [SPDC-DFG]-quantum mirror are suggested.Comment: 11 pages, 9 figure

    REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

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    Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity

    Burden and risk factors for Pseudomonas aeruginosa community-acquired pneumonia:a Multinational Point Prevalence Study of Hospitalised Patients

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    Pseudornonas aeruginosa is a challenging bacterium to treat due to its intrinsic resistance to the antibiotics used most frequently in patients with community-acquired pneumonia (CAP). Data about the global burden and risk factors associated with P. aeruginosa-CAP are limited. We assessed the multinational burden and specific risk factors associated with P. aeruginosa-CAP. We enrolled 3193 patients in 54 countries with confirmed diagnosis of CAP who underwent microbiological testing at admission. Prevalence was calculated according to the identification of P. aeruginosa. Logistic regression analysis was used to identify risk factors for antibiotic-susceptible and antibiotic-resistant P. aeruginosa-CAP. The prevalence of P. aeruginosa and antibiotic-resistant P. aeruginosa-CAP was 4.2% and 2.0%, respectively. The rate of P. aeruginosa CAP in patients with prior infection/colonisation due to P. aeruginosa and at least one of the three independently associated chronic lung diseases (i.e. tracheostomy, bronchiectasis and/or very severe chronic obstructive pulmonary disease) was 67%. In contrast, the rate of P. aeruginosa-CAP was 2% in patients without prior P. aeruginosa infection/colonisation and none of the selected chronic lung diseases. The multinational prevalence of P. aeruginosa-CAP is low. The risk factors identified in this study may guide healthcare professionals in deciding empirical antibiotic coverage for CAP patients

    Hybrid Semantics of Stochastic Programs with Dynamic Reconfiguration

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    We begin by reviewing a technique to approximate the dynamics of stochastic programs --written in a stochastic process algebra-- by a hybrid system, suitable to capture a mixed discrete/continuous evolution. In a nutshell, the discrete dynamics is kept stochastic while the continuous evolution is given in terms of ODEs, and the overall technique, therefore, naturally associates a Piecewise Deterministic Markov Process with a stochastic program. The specific contribution in this work consists in an increase of the flexibility of the translation scheme, obtained by allowing a dynamic reconfiguration of the degree of discreteness/continuity of the semantics. We also discuss the relationships of this approach with other hybrid simulation strategies for biochemical systems

    Development of a method for generating SNP interaction-aware polygenic risk scores for radiotherapy toxicity

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    Aim: To identify the effect of single nucleotide polymorphism (SNP) interactions on the risk of toxicity following radiotherapy (RT) for prostate cancer (PCa) and propose a new method for polygenic risk score incorporating SNP-SNP interactions (PRSi). Materials and methods: Analysis included the REQUITE PCa cohort that received external beam RT and was followed for 2 years. Late toxicity endpoints were: rectal bleeding, urinary frequency, haematuria, nocturia, decreased urinary stream. Among 43 literature-identified SNPs, the 30% most strongly associated with each toxicity were tested. SNP-SNP combinations (named SNP-allele sets) seen in >= 10% of the cohort were condensed into risk (RS) and protection (PS) scores, respectively indicating increased or decreased toxicity risk. Performance of RS and PS was evaluated by logistic regression. RS and PS were then combined into a single PRSi evaluated by area under the receiver operating characteristic curve (AUC). Results: Among 1,387 analysed patients, toxicity rates were 11.7% (rectal bleeding), 4.0% (urinary frequency), 5.5% (haematuria), 7.8% (nocturia) and 17.1% (decreased urinary stream). RS and PS combined 8 to 15 different SNP-allele sets, depending on the toxicity endpoint. Distributions of PRSi differed significantly in patients with/without toxicity with AUCs ranging from 0.61 to 0.78. PRSi was better than the classical summed PRS, particularly for the urinary frequency, haematuria and decreased urinary stream endpoints. Conclusions: Our method incorporates SNP-SNP interactions when calculating PRS for radiotherapy toxicity. Our approach is better than classical summation in discriminating patients with toxicity and should enable incorporating genetic information to improve normal tissue complication probability models. (C) 2021 The Authors. Published by Elsevier B.V

    Prevalence and risk factors for Enterobacteriaceae in patients hospitalized with community-acquired pneumonia

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    Background and objective Enterobacteriaceae (EB) spp. family is known to include potentially multidrug-resistant (MDR) microorganisms, and remains as an important cause of community-acquired pneumonia (CAP) associated with high mortality. The aim of this study was to determine the prevalence and specific risk factors associated with EB and MDR-EB in a cohort of hospitalized adults with CAP. Methods We performed a multinational, point-prevalence study of adult patients hospitalized with CAP. MDR-EB was defined when >= 3 antimicrobial classes were identified as non-susceptible. Risk factors assessment was also performed for patients with EB and MDR-EB infection. Results Of the 3193 patients enrolled with CAP, 197 (6%) had a positive culture with EB. Fifty-one percent (n = 100) of EB were resistant to at least one antibiotic and 19% (n = 38) had MDR-EB. The most commonly EB identified were Klebsiella pneumoniae (n = 111, 56%) and Escherichia coli (n = 56, 28%). The risk factors that were independently associated with EB CAP were male gender, severe CAP, underweight (body mass index (BMI) < 18.5) and prior extended-spectrum beta-lactamase (ESBL) infection. Additionally, prior ESBL infection, being underweight, cardiovascular diseases and hospitalization in the last 12 months were independently associated with MDR-EB CAP. Conclusion This study of adults hospitalized with CAP found a prevalence of EB of 6% and MDR-EB of 1.2%, respectively. The presence of specific risk factors, such as prior ESBL infection and being underweight, should raise the clinical suspicion for EB and MDR-EB in patients hospitalized with CAP

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