Cooperative Cellular UAV-to-Everything (C-U2X) communication based on 5G sidelink for UAV swarms

A swarm of cellular-connected Unmanned Aerial Vehicles (UAVs) enables new possibilities for emerging services and applications as the UAVs can autonomously coordinate their activities and cooperate to accomplish a given task. Because of spatio-temporal dynamics of swarm topology, robust and reliable network formation with seamless connectivity among UAVs is highly critical for any successful mission. This work focuses on the problem of cooperative and communication-aware UAV channel scheduling of data transmission from a set of target points of interests (PoIs) towards a cellular base station (BS). A novel, cooperative multi-hop communication model based on the C-V2X (Cellular Vehicle-to-Everything) Mode 4 cellular sidelink (PC5) radio interface is presented for efficient UAV data flow scheduling within the swarm. The model design aims at optimizing the cellular communications on UAV-to-UAV (U2U) and UAV-to-Infrastructure (U2I) links via a novel interference-aware scheduling, hence envisioning a new Cellular UAV-to-Everything (C-U2X) communication paradigm. An optimization model is used to solve the centralized version of the problem, while a distributed Dynamic Consensus-Based Bundle Algorithm (D-CBBA) is proposed to generate the best subchannel scheduling for maximizing data transmission in a distributed setting. Extensive simulation results demonstrate that the proposed distributed algorithm is able to extend the cellular infrastructure coverage while improving the multi-hop communications by autonomously adapting to the network conditions

Dissecting Immunotherapy Strategies for Small Cell Lung Cancer: Antibodies, Ionizing Radiation and CAR-T

Small cell lung cancer (SCLC) is a highly aggressive malignancy that accounts for about 14% of all lung cancers. Platinum-based chemotherapy has been the only available treatment for a long time, until the introduction of immune checkpoint inhibitors (ICIs) recently changed first-line standard of care and shed light on the pivotal role of the immune system. Despite improved survival in a subset of patients, a lot of them still do not benefit from first-line chemo-immunotherapy, and several studies are investigating whether different combination strategies (with both systemic and local treatments, such as radiotherapy) may improve patient outcomes. Moreover, research of biomarkers that may be used to predict patients’ outcomes is ongoing. In addition to ICIs, immunotherapy offers other different strategies, including naked monoclonal antibodies targeting tumor associated antigens, conjugated antibody, bispecific antibodies and cellular therapies. In this review, we summarize the main evidence available about the use of immunotherapy in SCLC, the rationale behind combination strategies and the studies that are currently ongoing in this setting, in order to give the reader a clear and complete view of this rapidly expanding topic

A fast ILP-based Heuristic for the robust design of Body Wireless Sensor Networks

We consider the problem of optimally designing a body wireless sensor network, while taking into account the uncertainty of data generation of biosensors. Since the related min-max robustness Integer Linear Programming (ILP) problem can be difficult to solve even for state-of-the-art commercial optimization solvers, we propose an original heuristic for its solution. The heuristic combines deterministic and probabilistic variable fixing strategies, guided by the information coming from strengthened linear relaxations of the ILP robust model, and includes a very large neighborhood search for reparation and improvement of generated solutions, formulated as an ILP problem solved exactly. Computational tests on realistic instances show that our heuristic finds solutions of much higher quality than a state-of-the-art solver and than an effective benchmark heuristic.Comment: This is the authors' final version of the paper published in G. Squillero and K. Sim (Eds.): EvoApplications 2017, Part I, LNCS 10199, pp. 1-17, 2017. DOI: 10.1007/978-3-319-55849-3\_16. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-55849-3_1

Concomitant administration of proton pump inhibitors does not significantly affect clinical outcomes in metastatic breast cancer patients treated with ribociclib

Background: Gastric pH changes by proton-pump-inhibitors (PPIs) were found to affect progression-free survival (PFS) in metastatic breast cancer (mBC) patients treated with palbociclib. The current study was aimed at investigating whether the same effect could occur in patients treated with ribociclib. Patients and methods: Patients with hormone-positive/HER-2-negative mBC candidates for first-line treatment with ribociclib were enrolled in this retrospective-cohort study. Patients were classified as "no concomitant PPIs" or "concomitant PPIs"; PPI administration covered the entire or not less than 2/3 of treatment with ribociclib. All clinical interventions were made according to clinical practice. Results: A total of 128 patients were consecutively enrolled in the study; 78 belonged to the "no concomitant PPIs" group and 50 to the "concomitant PPIs" group. One hundred and six patients were endocrine-sensitive and received ribociclib and letrozole, while 22 were endocrine-resistant and were treated with ribociclib and ful-vestrant. The most prescribed PPI was lansoprazole. According to PFS, patients taking PPIs had a PFS almost superimposable to those assuming ribociclib and endocrine therapy alone (35.3 vs. 49.2 months, p = 0.594). No difference in PFS was observed in estrogen-sensitive or estrogen-resistant mBC in the presence or absence of concomitant PPI treatment (p = 0.852). No correlation with adverse events was found including grade>2 he-matological toxicities. Conclusions: The present study supports the hypothesis that the concomitant use of PPIs does not compromise the efficacy of ribociclib in a real-life setting

Forwarder Smart Selection Protocol for Limitation of Broadcast Storm Problem

In this paper we introduce a novel routing protocol for efficiently broadcasting packets in vehicular ad hoc networks, while limiting multiple copies of the same packet, and avoiding collisions. In high-congested traffic scenarios, the increase of packet collisions and medium contentions among vehicles affects the inter-vehicular communications, and causes a degradation of quality-of-service (QoS). The effect also results in a very high number of message copies and collisions within the vehicular network. This is the well-known broadcast storm problem. Our proposed technique, namely Selective Reliable Broadcast protocol (SRB), is intended to limit the number of packet transmissions. Through an opportunistic vehicle selection, packets are retransmitted towards a next hop, in order to strongly reduce the number of forwarder vehicles, while preserving an acceptable level of QoS. SRB belongs to the class of broadcast protocols, as well as cluster-based approaches. It exploits the partitioning behavior, as typical from vehicular ad hoc networks, in order to automatically detect vehicular clusters, intended as "zones of interest". Packets will be then forwarded only to selected vehicles, opportunistically elected as cluster-heads. SRB performances have been assessed in different vehicular scenarios, mostly realistic environments, such as urban and highway scenarios. The limitation of the broadcast storm problem, as provided by SRB, is expressed in terms of a reduction of number of next-hop forwarders. The effectiveness of SRB has been also compared to (i) the traditional broadcast protocol, since in respect of traditional broadcasting, the main strengths of SRB are the efficiency of detecting clusters and selecting forwarders in a fast way, as well as (ii) a content-based dissemination approach, due to its ability to determine clusters of vehicles having common interests