MOTIVATION: Vaccines represent the most effective and cost-efficient weapons against a wide range of diseases. Nowadays new generation vaccines based on subunit antigens reduce adverse effects in high risk individuals. However, vaccine antigens are often poor immunogens when administered alone. Adjuvants represent a good strategy to overcome such hurdles, indeed they are able to: enhance the immune response; allow antigens sparing; accelerate the specific immune response; and increase vaccine efficacy in vulnerable groups such as newborns, elderly or immuno-compromised people. However, due to safety concerns and adverse reactions, there are only a few adjuvants approved for use in humans. Moreover, in practice current adjuvants sometimes fail to confer adequate stimulation. Hence, there is an imperative need to develop novel adjuvants that overcome the limitations of the currently available licensed adjuvants. RESULTS: We developed a computational framework that provides a complete pipeline capable of predicting the best citrus-derived adjuvants for enhancing the immune system response using, as a target disease model, influenza A infection. In silico simulations suggested a good immune efficacy of specific citrus-derived adjuvant (Beta Sitosterol) that was then confirmed in vivoAvailability: The model is available visiting the following URL: http://vaima.dmi.unict.it/AdjSim CONTACT: [email protected]; [email protected].

One of the main targets related to Wireless Sensor Networks (WSNs) is to reduce power consumption of nodes and of the whole network. An ideal WSN should be networked, scalable, fault-tolerant, energy-aware, and also smart and efficient. Unfortunately, however, this is not always true. The basic idea of the proposal is that senders use a heuristic approach to select the sub-optimal next hop in order to reach just one sink, considering some key requirements such as general performance (QoS and security), efficiency, trust ability, high computational power and energy-aware behaviour. Our model tries to satisfy the need for reaching the nearest sink node, considering a trade-off between the shortest path and heuristic decisions, in a top-level strategy based on a heuristic approach in order to reduce the overall power consumption of nodes of the network.