Obesity is characterized by increased leptin levels and insulin resistance, whereas blunted GH secretion is paired with normal, low, or high plasma IGF-I levels. To investigate body composition in human obesity and the interactions among the GH-IGF-I axis, leptin, and insulin resistance [measured with the homeostasis model assessment (HOMA) score], we studied 15 obese females, aged 23-54 yr (mean age, 42.7 +/- 2.6), with a body mass index (BMI) of 44.02 +/- 1.45 kg/m(2), who underwent treatment by biliopancreatic diversion (BPD), before and after surgery (16-24 months; BMI, 28.29 +/- 0.89 kg/m(2)). Our controls were 15 normal females, aged 28-54 yr (mean age, 40.8 +/- 2.3 yr), with a BMI of 27.52 +/- 0.53 kg/m(2). Insulin and leptin levels and HOMA scores were higher pre-BPD than in the controls. The GH response to GHRH was blunted, with a GH peak and GH area under the curve (AUC) significantly lower than those in controls. IGF-I and IGF-binding protein-3 (IGFBP-3) were also lower than control values. After surgery, BMI, fat mass, lean body mass, HOMA, insulin, and leptin significantly decreased. Furthermore, the GH response to GHRH severely increased; IGF-I and IGFBP-3 levels did not significantly vary. Considering all subjects, correlation analysis showed a strong positive correlation between insulin and leptin, and a negative correlation between insulin and GH peak and between insulin and GH AUC. Regression analysis performed grouping pre- and post-BPD indicated that leptin and GH peak or AUC could best be predicted from insulin levels. The surgical treatment of severe obesity after stabilization of body weight decreases BMI and fat mass while preserving normal lean body mass as well as positively influencing insulin sensitivity and thus aiding the normalization of leptin levels. The insulin reduction may be mainly involved in the increase in the GH response to GHRH through various possible central and peripheral mechanisms while decreasing the peripheral sensitivity to GH itself, as shown by the stable nature of the IGF-I and IGFBP-3 values. Our findings suggest that the changes in insulin levels are the starting point for changes in both leptin levels and the somatotrope axis after BPD.

Aims Patients with cardiac disease are considered high risk for poor outcomes following hospitalization with COVID-19. The primary aim of this study was to evaluate heterogeneity in associations between various heart disease subtypes and in-hospital mortality. Methods and results We used data from the CAPACITY-COVID registry and LEOSS study. Multivariable Poisson regression models were fitted to assess the association between different types of pre-existing heart disease and in-hospital mortality. A total of 16 511 patients with COVID-19 were included (21.1% aged 66–75 years; 40.2% female) and 31.5% had a history of heart disease. Patients with heart disease were older, predominantly male, and often had other comorbid conditions when compared with those without. Mortality was higher in patients with cardiac disease (29.7%; n = 1545 vs. 15.9%; n = 1797). However, following multivariable adjustment, this difference was not significant [adjusted risk ratio (aRR) 1.08, 95% confidence interval (CI) 1.02–1.15; P = 0.12 (corrected for multiple testing)]. Associations with in-hospital mortality by heart disease subtypes differed considerably, with the strongest association for heart failure (aRR 1.19, 95% CI 1.10–1.30; P < 0.018) particularly for severe (New York Heart Association class III/IV) heart failure (aRR 1.41, 95% CI 1.20–1.64; P < 0.018). None of the other heart disease subtypes, including ischaemic heart disease, remained significant after multivariable adjustment. Serious cardiac complications were diagnosed in <1% of patients. Conclusion Considerable heterogeneity exists in the strength of association between heart disease subtypes and in-hospital mortality. Of all patients with heart disease, those with heart failure are at greatest risk of death when hospitalized with COVID-19. Serious cardiac complications are rare during hospitalization.

For the monitoring of large landslides, total stations equipped with an Electronic Distance Meter (EDM) are widely used. To obtain the atmospheric parameters, required along the line of sight of every measure, the data collected by a weather station close to the instrument are usually adopted. Even after these corrections, the results obtained in the monitoring of areas with complex topography don't reach the accuracies theoretically attainable by the high-end instruments. The article proposes a method for removing the errors due to the influence of microclimate on the measurements obtained by a high-end EDM, in order to get the maximum accuracy obtainable from such instruments. The method is based on an atmospheric model, set up by using the climatic data and a digital terrain model (DTM) of the landslide area. The methodology has been applied to a landslide in southern Italy. Over 38,000 distances, acquired for each monitored point, were used. The results demonstrate the effectiveness of the method: the standard deviations of the distances after their correction, show a reduction, ranging from 20% to 50%, with respect to the most diffused procedures; furthermore, the obtained accuracy equals the one declared by the manufacturer of the instrument for measurements in optimal conditions.

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An integrated sensor for the measurement and monitoring of position and inclination, characterized by low cost, small size and low weight, has been designed, realized and calibrated at the Geomatics Lab of the University of Calabria. The design of the prototype, devoted to the monitoring of landslides and structures, was aiming at realizing a fully automated monitoring instrument, able to send the data acquired periodically or upon request by a control center through a bidirectional transmission protocol. The sensor can be released with different accuracy and range of measurement, by choosing bubble vials with different characteristics. The instrument is provided with a computer, which can be programmed so as to independently perform the processing of the data collected by a single sensor or a by a sensor network, and to transmit, consequently, alert signals if the thresholds determined by the monitoring center are exceeded. The bidirectional transmission also allows the users to vary the set of the monitoring parameters (time of acquisition, duration of satellite acquisitions, thresholds for the observed data). In the paper, hardware and software of the sensor are described, along with the calibration, the results of laboratory tests and of the first in field acquisitions.