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BackgroundCystic echinococcosis (CE) is an important neglected zoonotic parasitic infection belonging to the subgroup of seven Neglected Zoonotic Disease (NZDs) included in the World Health Organization’s official list of 18 Neglected Tropical Diseases (NTDs). CE causes serious global human health concerns and leads to significant economic losses arising from the costs of medical treatment, morbidity, life impairments and fatality rates in human cases. Moreover, CE is endemic in several Italian Regions. The aim of this study is to perform a detailed analysis of the economic burden of hospitalization and treatment costs and to estimate the Disability Adjusted Life Years (DALYs) of CE in Italy.Methods and findingsIn the period from 2001 to 2014, the direct costs of 21,050 Hospital Discharge Records (HDRs) belonging to 12,619 patients with at least one CE-related diagnosis codes were analyzed in order to quantify the economic burden of CE. CE cases average per annum are 901 (min—max = 480–1,583). Direct costs include expenses for hospitalizations, medical and surgical treatment incurred by public and private hospitals and were computed on an individual basis according to Italian Health Ministry legislation. Moreover, we estimated the DALYs for each patient. The Italian financial burden of CE is around € 53 million; the national average economic burden per annum is around € 4 million; the DALYs of the population from 2001 to 2014 are 223.35 annually and 5.26 DALYs per 105 inhabitants.ConclusionIn Italy, human CE is responsible for significant economic losses in the public health sector. In humans, costs associated with CE have been shown to have a great impact on affected individuals, their families and the community as a whole. This study could be used as a tool to prioritize and make decisions with regard to a surveillance system for this largely preventable yet neglected disease. It demonstrates the need of implementing a CE control program aimed at preventing the considerable economic and social losses it causes in high incidence areas.

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The brain exhibits capabilities of fast incremental learning from few noisy examples, as well as the ability to associate similar memories in autonomously-created categories and to combine contextual hints with sensory perceptions. Together with sleep, these mechanisms are thought to be key components of many high-level cognitive functions. Yet, little is known about the underlying processes and the specific roles of different brain states. In this work, we exploited the combination of context and perception in a thalamo-cortical model based on a soft winner-take-all circuit of excitatory and inhibitory spiking neurons. After calibrating this model to express awake and deep-sleep states with features comparable with biological measures, we demonstrate the model capability of fast incremental learning from few examples, its resilience when proposed with noisy perceptions and contextual signals, and an improvement in visual classification after sleep due to induced synaptic homeostasis and association of similar memories.

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