Efficacia e sicurezza del trattamento con un impianto sottocutaneo di octreotide in pazienti con acromegalia

Gli impianti sottocutanei di octreotide hanno un’efficacia terapeutica paragonabile a quella dell’octreotide LAR, avvalendosi però di un rilascio continuo del farmaco. Pertanto, il dispositivo sottocutaneo può essere considerato un’opzione terapeutica aggiuntiva, specie nei pazienti candidati al trattamento prolungato con octreotide

Integrating mobility data sources to define and quantify a vehicle-level congestion indicator: an application for the city of Turin

Abstract Purpose Traffic congestion is a large-scale problem in urban areas all over the world that can lead to substantial costs for travellers and business operations. This paper focus on how to measure the way in which congestion selectively affects different traffic streams, with special emphasis on light duty vehicles travelling around a city. Methods The idea is to integrate a dataset collecting Global Positioning System (GPS) vehicle traces with road side data sources related to traffic conditions in a road network, which on the other hand usually lack focus on specific traffic streams. The core of the data integration method is the creation of a specific indicator focusing on the time lost in congestion. This is a Key Performance Indicator (KPI) of an urban network that is of paramount importance as a decision support tool for policy makers, also because it has an impact on other key issues such as air pollution, noise emissions, energy efficiency and health problems. Then, a method is proposed to quantify the congestion KPI in a highly disaggregated fashion (each single vehicle travelling on each single link or street segment). Results This KPI can be used to inform a wide range of policy actions within the transport sector, both from the viewpoint of a city and from that of an individual actor of the transport system, such as the operator of a fleet of vehicles for urban freight deliveries. Some preliminary examples of how the aggregation of the KPI at different scales can provide insights into the transport system are presented

A study of tour-based mode choice based on a Support Vector Machine classifier

A new approach in recognizing travel mode choice patterns is proposed, based on the Support Vector Machine classification technique. The tour-based travel demand dataset that is analysed is for New York State, derived from the 2009 U.S. National Household Travel Survey. The main features characterizing each tour are the means used, travel-related variables and socioeconomic aspects. Results obtained demonstrate the ability to predict to some extent, in real settings where car use dominates, which tours are likely to be made by public transport or non-motorized means. Moreover, the flexibility of the technique allows assessing the predictive power of each feature according to the combination of travel means used in different tours. Potential applications range from activity-based travel choice simulators to search engines supporting personalized travel planners – in general, whenever ‘best guesses’ on mode choice patterns have to be made quickly on large amounts of data prejudicing the possibility of setting up a statistical model

Stated interest, actual use or indifference towards car sharing: profiling students and staff of a university campus in Turin (Italy)

A mobility survey was proposed to the staff and to the students of Politecnico di Torino (a technical university located in Turin, Italy) in autumn 2016 with a focus on the interest and on the current use of car sharing. Turin is in fact offering a relatively broad variety of such services, with several different operators and a fleet of about 700 vehicles. A data mining technique, named co-clustering, is then applied to the dataset of 1314 answers in order to characterise respondents’ profiles and assess to which extent specific combinations of variables describing personal, travel-related or satisfaction with travel aspects are associated with the actual use, the interest or the lack of interest in car sharing. Early adopters of car sharing are more frequently encountered among students than among staff and show more multimodal behaviours. The levels of use of different modes can be helpful in discriminating between mere positive attitudes towards car sharing and actual intention to use it, while travel related satisfaction ratings are rather indicating the interest or lack of interest in this service. Among university workers, younger females living in the outer part of the metropolitan city showed a good interest in car sharing, although the service is not available in the place where they live. Policy implications of such findings within a mobility management perspective are discussed

A comparative assessment of synthetic indices to measure multimodality behaviours

The study of how people jointly use different travel means is one of the key issues in contemporary transport research. However, measuring multimodality behaviours presents some intricacies that deserve more attention in order to come up with an instrument that is effective both on a modelling and on a policy viewpoint. The present work considers some methods that have been proposed in different disciplinary ambits to measure diversity and assesses to what extent they are useful to measure multimodality. A broad set of indices is then analysed, ranging from welfare economics (Gini, Dalton and Atkinson indices) to information theory and ecology (entropy, Herfindahl index). Theoretical investigations and empirical experiments on the properties of such indices show that there is not a measure of multimodality that consistently outperforms all the others in any circumstance. On the other hand, it emerged that some methods are clearly preferable for specific problem instances, as discussed in the conclusions

Endocannabinoids and the Processing of Value-Related Signals

Endocannabinoids serve as retrograde signaling molecules at many synapses within the CNS, particularly GABAergic and glutamatergic synapses. Synapses onto midbrain dopamine (DA) neurons in the ventral tegmental area (VTA) make no exception to this rule. In fact, the effects of cannabinoids on dopamine transmission as well as DA-related behaviors are generally exerted through the modulation of inhibitory and excitatory afferents impinging onto DA neurons. Endocannabinoids, by regulating different forms of synaptic plasticity in the VTA, provide a critical modulation of the DA neuron output and, ultimately, of the systems driving and regulating motivated behaviors. Because DA cells exhibit diverse states of activity, which crucially depend on their intrinsic properties and afferent drive, the understanding of the role played by endocannabinoids in synaptic modulations is critical for their overall functions. Particularly, endocannabinoids by selectively inhibiting afferent activity may alter the functional states of DA neurons and potentiate the responsiveness of the reward system to phasic DA

Photocurrent-based detection of Terahertz radiation in graphene

Graphene is a promising candidate for the development of detectors of Terahertz (THz) radiation. A well-known detection scheme due to Dyakonov and Shur exploits the confinement of plasma waves in a field-effect transistor (FET), whereby a dc photovoltage is generated in response to a THz field. This scheme has already been experimentally studied in a graphene FET [L. Vicarelli et al., Nature Mat. 11, 865 (2012)]. In the quest for devices with a better signal-to-noise ratio, we theoretically investigate a plasma-wave photodetector in which a dc photocurrent is generated in a graphene FET. The rectified current features a peculiar change of sign when the frequency of the incoming radiation matches an even multiple of the fundamental frequency of plasma waves in the FET channel. The noise equivalent power per unit bandwidth of our device is shown to be much smaller than that of a Dyakonov-Shur detector in a wide spectral range.Comment: 5 pages, 4 figure

Hashimoto's thyroiditis and autoimmune gastritis

The term "thyrogastric syndrome" defines the association between autoimmune thyroid disease and chronic autoimmune gastritis (CAG), and it was first described in the early 1960s. More recently, this association has been included in polyglandular autoimmune syndrome type IIIb, in which autoimmune thyroiditis represents the pivotal disorder. Hashimoto's thyroiditis (HT) is the most frequent autoimmune disease, and it has been reported to be associated with gastric disorders in 10-40% of patients while about 40% of patients with autoimmune gastritis also present HT. Some intriguing similarities have been described about the pathogenic mechanism of these two disorders, involving a complex interaction among genetic, embryological, immunologic, and environmental factors. CAG is characterized by a partial or total disappearance of parietal cells implying the impairment of both hydrochloric acid and intrinsic factor production. The clinical outcome of this gastric damage is the occurrence of a hypochlorhydric-dependent iron-deficient anemia, followed by pernicious anemia concomitant with the progression to a severe gastric atrophy. Malabsorption of levothyroxine may occur as well. We have briefly summarized in this minireview the most recent achievements on this peculiar association of diseases that, in the last years, have been increasingly diagnosed