The complementary role of imaging and tumor biomarkers in gynecological cancers: an update of the literature

Gynecological tumors, including endometrial, cervical and ovarian cancer, have increased in incidence over time. The widespread introduction of screening programs and advances in diagnostic imaging methods has lead to a progressive increase in gynecological cancer detection. Accurate diagnosis and proper monitoring of disease remain the primary target for a successful treatment. In the last years, knowledge about cancer biomarkers has considerably increased providing great opportunities for improving cancer detection and treatment. In addition, in the last few years there has been an important development of imaging techniques. Nowadays, a multimodal approach including the evaluation of serum tumor biomarkers combined with imaging techniques, seems to be the best strategy for assessing tumor presence, spread, recurrence, and/or the response to treatment in female cancer patients In this review we provide an overview of the application of biomarkers combined with novel imaging methods and highlight their roles in female cancer diagnosis and follow-up

JA-trie: Entropy-based packet classification

Any improvement in packet classification performance is crucial to ensure Internet functions continue to track the ever-increasing link capacities. Packet classification is the foundation of many Internet functions: from fundamental packet-forwarding to advanced features such as Quality of Service en-forcement, monitoring and security functions. This work proposes a novel trie-based classification algorithm, named Jump-Ahead Trie (JA-trie), utilizing an entropy-based pre-processing phase and a novel approach to wildcard matching. Through extensive experimental tests, we demonstrate that our proposed algorithm is able to outperform a range of state-of-the-art classification algorithms.This work was jointly supported by the EPSRC INTERNET Project EP/H040536/1, by the National Science Foundation under Grant No. CNS-0855268, and by the MIUR project GreenNet (FIRB 2010).This is the accepted manuscript. The final version is available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6900878

Transient plasma cell dyscrasia in COVID-19 patients linked to IL-6 triggering

An unusual clonal gammopathy was reported in COVID-19 patient but whether this anomaly is related or not to the disease has not yet been clarified. To this aim, we selected a cohort of 35 COVID-19 patients swab positive and investigated serological levels of IL-6, immune response to major viral antigens and electrophoretic profile. Elevated levels of IL-6 were accompanied by a significative humoral response to viral Spike protein, revealing an altered electrophoretic profile in the gamma region. We can conclude that elevated levels of IL-6 triggers humoral response inducing a transient plasma cell dyscrasia in severe COVID-19 patients

Optimized energy and air quality management of shared smart buildings in the covid-19 scenario

Worldwide increasing awareness of energy sustainability issues has been the main driver in developing the concepts of (Nearly) Zero Energy Buildings, where the reduced energy consumptions are (nearly) fully covered by power locally generated by renewable sources. At the same time, recent advances in Internet of Things technologies are among the main enablers of Smart Homes and Buildings. The transition of conventional buildings into active environments that process, elaborate and react to online measured environmental quantities is being accelerated by the aspects related to COVID-19, most notably in terms of air exchange and the monitoring of the density of occupants. In this paper, we address the problem of maximizing the energy efficiency and comfort perceived by occupants, defined in terms of thermal comfort, visual comfort and air quality. The case study of the University of Pisa is considered as a practical example to show preliminary results of the aggregation of environmental data