Urine proteome in animals of veterinary interest: species comparison and new biomarkers of nephropathy

Urine is considered an ideal source of biomarkers, however in veterinary medicine a complete study on the urine proteome is still lacking. The present work aimed to apply proteomic techniques to the separation of the urine proteome in dogs, cats, horses, cows and some non-conventional species. High resolution electrophoresis (HRE) was also validated for the quantification of albuminuria in dogs and cats. In healthy cats, applying SDS-PAGE and 2DE coupled to mass spectrometry (MS), was produced a reference map of the urine proteome. Moreover, 13 differentially represented urine proteins were linked with CKD, suggesting uromodulin, cauxin, CFAD, Apo-H, RBP and CYSM as candidate biomarkers to be investigated further. In dogs, applying SDS-PAGE coupled to MS, was highlighted a specific pattern in healthy animals showing important differences in patients affected by leishmaniasis. In particular, uromodulin could be a putative biomarker of tubular damage while arginine esterase and low MW proteins needs to be investigated further. In cows, applying SDS-PAGE, were highlighted different patterns between heifers and cows showing some interesting changes during pregnancy. In particular, putative alpha-fetoprotein and b-PAP needs to be further investigated. In horses, applying SDS-PAGE, was produced a reference profile characterized by 13±4 protein bands and the most represented one was the putative uromodulin. Proteinuric horses showed the decrease of the putative uromodulin band and the appearance of 2 to 4 protein bands at higher MW and a greater variability in the range of MW between 49 and 17 kDa. In felids and giraffes was quantified proteinuria reporting the first data for UTP and UPC. Moreover, by means of SDS-PAGE, were highlighted species-specific electrophoretic patterns in big felids and giraffes.

Quality assessment of a landslide inventory map and its application to land‐use planning. A case study in the Northern Apennines (Emilia‐Romagna region, Italy)

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land‐use planning represents a powerful tool to manage this socio‐economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land‐use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land‐use planning. In this sense, I proceeded according to a two‐steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi‐temporal landslide inventory map. Conversely, long‐ and short‐term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end‐users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land‐use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision‐support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.