Unenhanced whole-body MRI versus PET-CT for the detection of prostate cancer metastases after primary treatment

The aim of this study was to evaluate the accuracy of unenhanced whole-body MRI, including whole-body Diffusion Weighted Imaging (DWI), used as a diagnostic modality to detect  pathologic lymph nodes and skeletal metastases in patients with prostate cancer (PCa) undergoing restaging after primary treatment

Network intelligence vs. jamming in underwater networks: how learning can cope with misbehavior

In this paper, we present a machine-learning technique to counteract jamming attacks in underwater networks. Indeed, this is relevant in security applications where sensor devices are located in critical regions, for example, in the case of national border surveillance or for identifying any unauthorized intrusion. To this aim, a multi-hop routing protocol that relies on the exploitation of a Q-learning methodology is presented with a focus on increasing reliability in data communication and network lifetime. Performance results assess the effectiveness of the proposed solution as compared to other efficient state-of-the-art approaches

Drug–drug interactions and pharmacogenomic evaluation in colorectal cancer patients. The new drug-pin® system comprehensive approach

Drug–drug interactions (DDIs) can affect both treatment efficacy and toxicity. We used Drug-PIN® (Personalized Interactions Network) software in colorectal cancer (CRC) patients to evaluate drug–drug–gene interactions (DDGIs), defined as the combination of DDIs and individual genetic polymorphisms. Inclusion criteria were: (i) stage II-IV CRC; (ii) ECOG PS (Performance status sec. Eastern coperative oncology group) ≤2; (iii) ≥5 concomitant drugs; and (iv) adequate renal, hepatic, and bone marrow function. The Drug-PIN® system analyzes interactions between active and/or pro-drug forms by integrating biochemical, demographic, and genomic data from 110 SNPs. We selected DDI, DrugPin1, and DrugPin2 scores, resulting from concomitant medication interactions, concomitant medications, and SNP profiles, and DrugPin1 added to chemotherapy drugs, respectively. Thirty-four patients, taking a median of seven concomitant medications, were included. The median DrugPin1 and DrugPin2 scores were 42.6 and 77.7, respectively. In 13 patients, the DrugPin2 score was two-fold higher than the DrugPin1 score, with 7 (54%) of these patients experiencing severe toxicity that required hospitalization. On chi-squared testing for any toxic-ity, a doubled DrugPin2 score (p = 0.001) was significantly related to G3–G4 toxicity. Drug-PIN® software may prevent severe adverse events, decrease hospitalizations, and improve survival in cancer patients

Turning round the telescope. Centre-right parties and immigration and integration policy in Europe

This is an Author's Original Manuscript of 'Turning round the telescope. Centre-right parties and immigration and integration policy in Europe', whose final and definitive form, the Version of Record, has been published in the Journal of European Public Policy 15(3):315-330, 2008 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/doi.org/10.1080/13501760701847341

Evaluation of Methods for Estimating Time to Steady State with Examples from Phase 1 Studies

An overview is provided of the methodologies used in determining the time to steady state for Phase 1 multiple dose studies. These methods include NOSTASOT (no-statistical-significance-of-trend), Helmert contrasts, spline (quadratic) regression, effective half life for accumulation, nonlinear mixed effects modeling, and Bayesian approach using Markov Chain Monte Carlo (MCMC) methods. For each methodology we describe its advantages and disadvantages. The first two methods do not require any distributional assumptions for the pharmacokinetic (PK) parameters and are limited to average assessment of steady state. Also spline regression which provides both average and individual assessment of time to steady state does not require any distributional assumptions for the PK parameters. On the other hand, nonlinear mixed effects modeling and Bayesian hierarchical modeling which allow for the estimation of both population and subject-specific estimates of time to steady state do require distributional assumptions on PK parameters. The current investigation presents eight case studies for which the time to steady state was assessed using the above mentioned methodologies. The time to steady state estimates obtained from nonlinear mixed effects modeling, Bayesian hierarchal approach, effective half life, and spline regression were generally similar

Second-line chemotherapy in advanced pancreatic cancer patients before nab-paclitaxel introduction. Retrospective study in Reggio Emilia Clinical Cancer Centre

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