Specific miRNAs Change After 3 Months of GH treatment and Contribute to Explain the Growth Response After 12 Months

Context: There is growing evidence of the role of epigenetic regulation of growth, and miRNAs potentially play a role. Objective: The aim of this study is to identify changes in circulating miRNAs following GH treatment in subjects with isolated idiopathic GH deficiency (IIGHD) after the first 3 months of treatment, and verify whether these early changes can predict growth response. Design and methods: The expression profiles of 384 miRNAs were analyzed in serum in 10 prepubertal patients with IIGHD (5 M, 5 F) at two time points before starting GH treatment (t-3, t0), and at 3 months on treatment (t+3). MiRNAs with a fold change (FC) >+1.5 or <-1.5 at t+3 were considered as differentially expressed. In silico analysis of target genes and pathways led to a validation step on 8 miRNAs in 25 patients. Clinical and biochemical parameters were collected at baseline, and at 6 and 12 months. Simple linear regression analysis and multiple stepwise linear regression models were used to explain the growth response. Results: Sixteen miRNAs were upregulated and 2 were downregulated at t+3 months. MiR-199a-5p (p = 0.020), miR-335-5p (p = 0.001), and miR-494-3p (p = 0.026) were confirmed to be upregulated at t+3. Changes were independent of GH peak values at testing, and levels stabilized after 12 months. The predicted growth response at 12 months was considerably improved compared with models using the common clinical and biochemical parameters. Conclusions: MiR-199a-5p, miR-335-5p, and miR-494-3p changed after 3 months of GH treatment and likely reflected both the degree of GH deficiency and the sensitivity to treatment. Furthermore, they were of considerable importance to predict growth response.Context: There is growing evidence of the role of epigenetic regulation of growth, and miRNAs potentially play a role. Objective: The aim of this study is to identify changes in circulating miRNAs following GH treatment in subjects with isolated idiopathic GH deficiency (IIGHD) after the first 3 months of treatment, and verify whether these early changes can predict growth response. Design and methods: The expression profiles of 384 miRNAs were analyzed in serum in 10 prepubertal patients with IIGHD (5 M, 5 F) at two time points before starting GH treatment (t-3, t0), and at 3 months on treatment (t+3). MiRNAs with a fold change (FC) >+1.5 or <-1.5 at t+3 were considered as differentially expressed. In silico analysis of target genes and pathways led to a validation step on 8 miRNAs in 25 patients. Clinical and biochemical parameters were collected at baseline, and at 6 and 12 months. Simple linear regression analysis and multiple stepwise linear regression models were used to explain the growth response. Results: Sixteen miRNAs were upregulated and 2 were downregulated at t+3 months. MiR-199a-5p (p = 0.020), miR-335-5p (p = 0.001), and miR-494-3p (p = 0.026) were confirmed to be upregulated at t+3. Changes were independent of GH peak values at testing, and levels stabilized after 12 months. The predicted growth response at 12 months was considerably improved compared with models using the common clinical and biochemical parameters. Conclusions: MiR-199a-5p, miR-335-5p, and miR-494-3p changed after 3 months of GH treatment and likely reflected both the degree of GH deficiency and the sensitivity to treatment. Furthermore, they were of considerable importance to predict growth response

Exploring mobile network data for tourism statistics: the collaboration between Istat and Vodafone Business Italia

The paper describes the collaboration between Istat and Vodafone Business Italia to innovate and enhance tourism statistics. The common goal is to evaluate the potential uses of mobile phone data in current surveys and to investigate new outputs for official statistics, such as visiting routes and means of transport. The analysis concerned inbound tourism (foreigners in Italy), domestic tourism (Italians in Italy), and outbound tourism (Italians abroad). The work presents analyses and results for the Province of Rimini and the Municipality of Roma, referred to August 2019/2020 and April 2020, and a trial of the use of the “Welcome SMS” for the estimate of the residents in Italy who travel to foreign countries. Phone data required specific treatments to meet the definitions of official statistics. Some aspects related to the location and definition of overnight stays will require further investigation

An Operations Research Model For The Evaluation Of An Airport Terminal: SLAM (Simple Landside Aggregate Model

The Simple Landside Aggregate Model (SLAM) is a model for estimating capacity and delays in airport passenger terminals. SLAM is designed to answer “what if ” questions about alternative configurations of the various processing and holding facilities in a terminal. It consists of a network of modules, one for each facility of the terminal. These modules are based on a set of quite simple mathematical formulas to be used for the estimation of the capacity of each facility (in terms of passengers per hour) and the level of service (LOS) associated with it. LOS is quantified both in terms of “space available per facility occupant ” and waiting time for being processed. Key Words: Strategic, tactical and aggregate models, level of service. The modelling of airport terminal operations has advanced significantly over the last 15 years (Tosic, 1992). Available models have improved in detail and fidelity, as well as “user friendliness”. As a result, their use as decision support aids or design tools in terminal development projects has been steadily increasing. Some existing models are “strategic ” in nature sacrificing level of detail in exchange for speed and flexibility, while others are primarily “tactical ” incorporating high levels of detail in data and system definition. The lack of a satisfactory strategic model of landside operation

Evaluating Terminal Management Performances Using SLAM: The Case Of Athens International Airport

Athens in Greece is the city selected to host the 2004 Olympic Games. Many simulations and analyses have been performed in order to properly approach the logistics problems arising from such an event. In this paper we address one of these problems. More precisely, we present a model for analyzing the terminal of AIA (Athens International Airport) under three different scenarios: (i) a historic scenario, based on a typical \u201cbusy day\u201d, (ii) a foreseeable scenario with AIA becoming a hub and increasing its traffic volume, and (iii) a traffic intense scenario, as expected during the 2004 Olympic Games. The airport simulation is performed through the OPAL platform. While the airside analysis does not evidence any major cause of congestion, the landside, evaluated through an enhanced version of the Simple Landside Aggregate Model (SLAM), shows possible situations of congestion with a consequent degradation in the level of service provided. The use of SLAM allows signaling out the bottlenecks and the corresponding possible causes. A simple modification in the airport policies is sufficient to significantly improve the overall performance