Tumour-derived PGD2 and NKp30-B7H6 engagement drives an immunosuppressive ILC2-MDSC axis.

Group 2 innate lymphoid cells (ILC2s) are involved in human diseases, such as allergy, atopic dermatitis and nasal polyposis, but their function in human cancer remains unclear. Here we show that, in acute promyelocytic leukaemia (APL), ILC2s are increased and hyper-activated through the interaction of CRTH2 and NKp30 with elevated tumour-derived PGD2 and B7H6, respectively. ILC2s, in turn, activate monocytic myeloid-derived suppressor cells (M-MDSCs) via IL-13 secretion. Upon treating APL with all-trans retinoic acid and achieving complete remission, the levels of PGD2, NKp30, ILC2s, IL-13 and M-MDSCs are restored. Similarly, disruption of this tumour immunosuppressive axis by specifically blocking PGD2, IL-13 and NKp30 partially restores ILC2 and M-MDSC levels and results in increased survival. Thus, using APL as a model, we uncover a tolerogenic pathway that may represent a relevant immunosuppressive, therapeutic targetable, mechanism operating in various human tumour types, as supported by our observations in prostate cancer.Group 2 innate lymphoid cells (ILC2s) modulate inflammatory and allergic responses, but their function in cancer immunity is still unclear. Here the authors show that, in acute promyelocytic leukaemia, tumour-activated ILC2s secrete IL-13 to induce myeloid-derived suppressor cells and support tumour growth

Introducing Automated Reasoning in Network Management

This paper proposes the adoption of Artificial Intelligence techniques in the field of network management and monitoring. In order to allow automated reasoning on networking topics, we constructed an accurate ontological model capable of fitting as more as possible networking concepts. The thoroughly representation of the domain knowledge is used by a Logical Reasoner, which is an expert system capable of performing management tasks typically executed by human experts. The Logical Reasoner is integrated in a distributed multi-agent architecture for network management, which exploits the dynamic reasoning capabilities of the Situation Calculus formalism to provide a powerful system capable of performing high-level management tasks in order to deal with network fault situations. The system exploits programmable network technology to make possible the deployment of code which implements teleo-reactive agents, distributed across the whole network. The information related to network events, generated by programmable sensors deployed on the network devices, is collected by the logical entity where it is merged with general domain knowledge, with a view to identifying the root causes of faults, and to decide on reparative actions