DPRAODV: A Dynamic Learning System Against Blackhole Attack In AODV Based MANET

Security is an essential requirement in mobile ad hoc networks to provide protected communication between mobile nodes. Due to unique characteristics of MANETS, it creates a number of consequential challenges to its security design. To overcome the challenges, there is a need to build a multifence security solution that achieves both broad protection and desirable network performance. MANETs are vulnerable to various attacks, blackhole, is one of the possible attacks. Black hole is a type of routing attack where a malicious node advertise itself as having the shortest path to all nodes in the environment by sending fake route reply. By doing this, the malicious node can deprive the traffic from the source node. It can be used as a denial-of-service attack where it can drop the packets later. In this paper, we proposed a DPRAODV (Detection, Prevention and Reactive AODV) to prevent security threats of blackhole by notifying other nodes in the network of the incident. The simulation results in ns2 (ver-2.33) demonstrate that our protocol not only prevents blackhole attack but consequently improves the overall performance of (normal) AODV in presence of black hole attack

A patient-derived explant (PDE) model of hormone-dependent cancer.

Breast and prostate cancer research to date has largely been predicated on the use of cell lines in vitro or in vivo. These limitations have led to the development of more clinically relevant models, such as organoids or murine xenografts that utilize patient-derived material; however, issues related to low take rate, long duration of establishment, and the associated costs constrain use of these models. This study demonstrates that ex vivo culture of freshly resected breast and prostate tumor specimens obtained from surgery, termed patient-derived explants (PDEs), provides a high-throughput and cost-effective model that retains the native tissue architecture, microenvironment, cell viability, and key oncogenic drivers. The PDE model provides a unique approach for direct evaluation of drug responses on an individual patient's tumor, which is amenable to analysis using contemporary genomic technologies. The ability to rapidly evaluate drug efficacy in patient-derived material has high potential to facilitate implementation of personalized medicine approaches.Cancer Research UK and ERC

A patient-derived explant (PDE) model of hormone-dependent cancer.

Breast and prostate cancer research to date has largely been predicated on the use of cell lines in vitro or in vivo. These limitations have led to the development of more clinically relevant models, such as organoids or murine xenografts that utilize patient-derived material; however, issues related to low take rate, long duration of establishment, and the associated costs constrain use of these models. This study demonstrates that ex vivo culture of freshly resected breast and prostate tumor specimens obtained from surgery, termed patient-derived explants (PDEs), provides a high-throughput and cost-effective model that retains the native tissue architecture, microenvironment, cell viability, and key oncogenic drivers. The PDE model provides a unique approach for direct evaluation of drug responses on an individual patient's tumor, which is amenable to analysis using contemporary genomic technologies. The ability to rapidly evaluate drug efficacy in patient-derived material has high potential to facilitate implementation of personalized medicine approaches.Cancer Research UK and ERC