SGLT2 Inhibitors and the Diabetic Kidney

Diabetic nephropathy (DN) is the most common cause of end-stage renal disease worldwide. Blood glucose and blood pressure control reduce the risk of developing this complication; however, once DN is established, it is only possible to slow progression. Sodium-glucose cotransporter 2 (SGLT2) inhibitors, the most recent glucose-lowering oral agents, may have the potential to exert nephroprotection not only through improving glycemic control but also through glucose-independent effects, such as blood pressure-lowering and direct renal effects. It is important to consider, however, that in patients with impaired renal function, given their mode of action, SGLT2 inhibitors are less effective in lowering blood glucose. In patients with high cardiovascular risk, the SGLT2 inhibitor empagliflozin lowered the rate of cardiovascular events, especially cardiovascular death, and substantially reduced important renal outcomes. Such benefits on DN could derive from effects beyond glycemia. Glomerular hyperfiltration is a potential risk factor for DN. In addition to the activation of the renin-angiotensin-aldosterone system, renal tubular factors, including SGLT2, contribute to glomerular hyperfiltration in diabetes. SGLT2 inhibitors reduce sodium reabsorption in the proximal tubule, causing, through tubuloglomerular feedback, afferent arteriole vasoconstriction and reduction in hyperfiltration. Experimental studies showed that SGLT2 inhibitors reduced hyperfiltration and decreased inflammatory and fibrotic responses of proximal tubular cells. SGLT2 inhibitors reduced glomerular hyperfiltration in patients with type 1 diabetes, and in patients with type 2 diabetes, they caused transient acute reductions in glomerular filtration rate, followed by a progressive recovery and stabilization of renal function. Interestingly, recent studies consistently demonstrated a reduction in albuminuria. Although these data are promising, only dedicated renal outcome trials will clarify whether SGLT2 inhibitors, in addition to their glycemic and blood pressure benefits, may provide nephroprotective effects

Obesity management: at the forefront against disease stigma and therapeutic inertia

Obesity is a complex chronic relapsing disease, resulting from the interaction between multiple environmental, genetic and epigenetic causes, and supported by changes in the neuroendocrine mechanisms regulating energy balance and body weight. Adipose tissue dysfunction contributes to obesity-related complications. However, the prevalent narrative about the causes and mechanisms of obesity remains a much more simplistic one, based on the false assumption that individuals can fully control their body weight through appropriate behavioural choices. According to this narrative, obesity is simply reversible "persuading" the patient to follow healthier and more virtuous individual behaviours (moral judgement). This persistent narrative forms the deep root of the stigmatisation of people with obesity at the individual level and creates a clear discrepancy on how obesity prevention and cure are designed in comparison with the case of other non-communicable chronic diseases (clinical stigma). The promotion of systemic preventive measures against obesity is not supported at a political and social level by the persistence of a narrative of obesity as the simple consequence of individual failures and lack of willpower. The simplistic narrative of obesity as a self-imposed condition with an easy way-out ("eat less and move more") creates a clear discrepancy on how obesity is managed by health care systems in comparison with other NCDs. The over-estimation of the efficacy of therapeutic intervention solely based on patients education and lifestyle modification is responsible of therapeutic inertia in health care professionals and in clinical guidelines, limiting or delaying the adoption of more effective therapeutic strategies, like anti-obesity medications and bariatric surgery. In conclusion, the persistence of a narrative describing obesity as a self-induced easily reversible condition has profound consequences on how obesity prevention and management are build, including the design and implementation of obesity management guidelines and a tendency to therapeutic inertia.Level of evidence: No level of evidence

Obesity, Male Reproductive Function and Bariatric Surgery

Overweight and obesity are associated with several chronic complications, such as type 2 diabetes, arterial hypertension and atherosclerotic cardiovascular diseases, with relevant consequences for patients and public health systems. Reproductive function abnormalities, such as obesity-related secondary hypogonadism, erectile dysfunction and infertility, represent other abnormalities negatively affecting the quality of life of men suffering from obesity but, despite their high prevalence, these are often understated because of a general lack of awareness in clinical practice. Obesity and gonadal function are closely related, with obesity being associated with hypogonadism that is reversed by body weight reduction thus ameliorating reproductive and sexual health. Clinical studies specifically evaluating the impact of non-surgical weight loss on testosterone levels sometimes showed conflicting results, whereas extensive literature has demonstrated that weight loss after bariatric surgery is correlated with an increase in testosterone levels greater than that obtained with only lifestyle interventions, suggesting the role of surgery also for the treatment of hypogonadism in obese male. However, studies concerning the consequences of bariatric surgery on overall reproductive function in the male, including also sexual activity and fertility, are limited and data regarding long-term effects are lacking. Here we present a brief review summarizing the evidence regarding the interplay between obesity and reproductive abnormalities in the obese male, together with the role of bariatric surgery for the treatment of these complications, describing both the positive effects and the limitations of this procedure

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

This paper presents a method for mapping the nitrogen (N) status in a maize field using hyperspectral remote sensing imagery. An airborne survey was conducted with an AISA Eagle hyperspectral sensor over an experimental farm where maize (Zea mays L.) was grown with two N fertilization levels (0 and 100 kg N ha-1) in four replicates. Leaf and canopy field data were collected during the flight. The nitrogen (N) status has been estimated in this work based on the Nitrogen Nutrition Index (NNI) defined as the ratio between the leaf actual N concentration (%Na) of the crop and the minimum N content required for the maximum biomass production (critical N concentration (%Nc)) calculated through the dry mass at the time of the flight (Wflight). The inputs required to calculate the NNI (i.e. %Na and Wflight) have been estimated through regression analyses between field data and remotely sensed vegetation indices. MCARI/MTVI2 (Modified Chlorophyll Absorption Ratio Index / Modified Triangular Vegetation Index 2) showed the best performances in estimating the %Na (R2 = 0.59) and MTVI2 in estimating the Wflight (R2 = 0.80). The %Na and the Wflight were then mapped and used to compute the NNI map over the entire field. The NNI map agreed with the NNI estimated using field data through traditional destructive measurements (R2 = 0.70) confirming the potential of using remotely sensed indices to assess the crop N condition. Finally, a method to derive a pixel based variable rate N fertilization map was proposed as the difference between the actual N content and the optimal N content. We think that the proposed operational methodology is promising for precision farming since it represents an innovative attempt to derive from an aerial hyperspectral image a variable rate N fertilization map based on the actual crop N status.JRC.H.4-Monitoring Agricultural Resource

Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery

JRC.H.4-Monitoring Agricultural Resource

Remote sensing-based estimation of gross primary production in a subalpine grassland

This study investigates the performances in a terrestrial ecosystem of gross primary production (GPP) estimation of a suite of spectral vegetation indexes (VIs) that can be computed from currently orbiting platforms. Vegetation indexes were computed from near-surface field spectroscopy measurements collected using an automatic system designed for high temporal frequency acquisition of spectral measurements in the visible near-infrared region. Spectral observations were collected for two consecutive years in Italy in a subalpine grassland equipped with an eddy covariance (EC) flux tower that provides continuous measurements of net ecosystem carbon dioxide (CO2) exchange (NEE) and the derived GPP. Different VIs were calculated based on ESA-MERIS and NASA-MODIS spectral bands and correlated with biophysical (Leaf area index, LAI; fraction of photosynthetically active radiation intercepted by green vegetation, f IPARg), biochemical (chlorophyll concentration) and ecophysiological (green light-use efficiency, LUEg) canopy variables. In this study, the normalized difference vegetation index (NDVI) was the index best correlated with LAI and f IPARg (r = 0.90 and 0.95, respectively), the MERIS terrestrial chlorophyll index (MTCI) with leaf chlorophyll content (r = 0.91) and the photochemical reflectance index (PRI551), computed as (R531 −R551)/(R531 +R551) with LUEg (r = 0.64). Subsequently, these VIs were used to estimate GPP using different modelling solutions based on Monteith’s lightuse efficiency model describing the GPP as driven by the photosynthetically active radiation absorbed by green vegetation (APARg) and by the efficiency (") with which plants use the absorbed radiation to fix carbon via photosynthesis. Results show that GPP can be successfully modelled with a combination of VIs and meteorological data or VIs only. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterised by a strong seasonal dynamic of GPP. Accuracy in GPP estimation slightly improves when taking into account high frequency modulations of GPP driven by incident PAR or modelling LUEg with the PRI in model formulation. Similar results were obtained for both measured daily VIs and VIs obtained as 16-day composite time series and then downscaled from the compositing period to daily scale (resampled data). However, the use of resampled data rather than measured daily input data decreases the accuracy of the total GPP estimation on an annual basis.JRC.H.4-Monitoring Agricultural Resource

Analysis of multi-year near-surface ozone observations at the WMO/GAW "Concordia" station (75°06′S, 123°20′E, 3280 m a.s.l. – Antarctica)

Abstract This work focuses on the near-surface O3 variability over the eastern Antarctic Plateau. In particular, eight years (2006–2013) of continuous observations at the WMO/GAW contributing station "Concordia" (Dome C–DMC: 75°06′S, 123°20′E, 3280 m) are presented, in the framework of the Italian Antarctic Research Programme (PNRA). First, the characterization of seasonal and diurnal O3 variability at DMC is provided. Then, for the period of highest data coverage (2008–2013), we investigated the role of specific atmospheric processes in affecting near-surface summer O3 variability, when O3 enhancement events (OEEs) are systematically observed at DMC (average monthly frequency peaking up to 60% in December). As deduced by a statistical selection methodology, these OEEs are affected by a significant interannual variability, both in their average O3 values and in their frequency. To explain part of this variability, we analyzed OEEs as a function of specific atmospheric variables and processes: (i) total column of O3 (TCO) and UV-A irradiance, (ii) long-range transport of air masses over the Antarctic Plateau (by Lagrangian back-trajectory analysis – LAGRANTO), (iii) occurrence of "deep" stratospheric intrusion events (by using the Lagrangian tool STLEFLUX). The overall near-surface O3 variability at DMC is controlled by a day-to-day pattern, which strongly points towards a dominating influence of processes occurring at "synoptic" scales rather than "local" processes. Even if previous studies suggested an inverse relationship between OEEs and TCO, we found a slight tendency for the annual frequency of OEEs to be higher when TCO values are higher over DMC. The annual occurrence of OEEs at DMC seems related to the total time spent by air masses over the Antarctic plateau before their arrival to DMC, suggesting the accumulation of photochemically-produced O3 during the transport, rather than a more efficient local production. Moreover, the identification of recent (i.e., 4-day old) stratospheric intrusion events by STEFLUX suggested only a minor influence (up to 3% of the period, in November) of "deep" events on the variability of near-surface summer O3 at DMC