Innovative 3D proteome-wide scale identification of ALKBH5 target for MV1035 small molecule able to reduce migration and invasiveness in U87 glioblastoma cell lines by SPILLO-PBSS

The innovative in silico technologies developed at SPILLOproject,1 e.g., the SPILLO potential binding sites searcher (SPILLO-PBSS) software,2,3 allow to identify targets and off-targets of any small molecule on a multiple-organism proteomewide scale, and to perform an accurate multilevel cross-organism transferability analysis (MCOTA) aimed at rationalising animal testing. SPILLO-PBSS has been successfully used in several research projects, such as a study in which a compound (MV1035) was found to reduce migration and invasiveness in U87 glioblastoma (GBM) cell lines: the human structural proteome was analyzed and the RNA demethylase ALKBH5 has been identified as a target responsible for the observed effects (target experimentally validated). Another top-ranked target identified by SPILLO-PBSS, the DNA repair protein AlkB homolog 2 (ALKBH2), abundantly expressed in GBM cell lines, resulted particularly interesting for its pivotal role in the onset of resistance to Temozolomide (TMZ), the standard firstline treatment for GBM.

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions

Regionalization of flow-duration curves through catchment classification with streamflow signatures and physiographic-climate indices

This study addresses the estimation of flow-duration curves (FDC) in ungauged sites through the catchment classification. Forty-six catchments in the Upper Po river basin (Italy) were analyzed and classified through two different frameworks: the first scheme consists of the application of two clustering methods in a series considering six streamflow signatures, and the second one treats indexes of climate, physiography, soil, and land-use with the same clustering procedure. Catchments have been classified into three homogeneous groups: the first one is characterized by the lowest runoff and flash-flood events, the second one includes maximum runoff, and the third one shows intermediate behaviour. The estimation of FDCs was done using a lognormal distribution, whereas the regionalization was constructed applying a stepwise multiple linear regression, followed by a leave-one-out cross-validation. The results show great performance improvement when the regionalization model is found by taking account of the three different hydrological classes, with a mean absolute percentage error that decreases from 11% for the single region case to 7% in the three homogeneous regions cas

Exploring Correlation between Stand Structural Indices and Parameters across Three Forest Types of the Southeastern Italian Alps

Forest stand structure can be described through stand structural parameters as well as using stand structural indices. However, to date, there is still much uncertainty regarding how stand structural indices and parameters are intercorrelated. The analysis of correlation can guide their selection in research applications and forest management, avoiding redundancies and loss of time during data collection. In this study, using a sample of forest stands belonging to three forest types of the southeastern Italian Alps, we explored the correlation among stand structural indices, and then we checked the relationships between stand structural indices and stand structural parameters. The results indicate that the stand structural indices vary among the sampled forest types. Moreover, the correlation among stand structural indices indicates that some of them are strongly intercorrelated and, thus, they can give redundant information. Strong correlations have been found between the Shannon index and the Mingling index, between the Gini index and the Diameter differentiation index, and between size dominance indices. Correlations between stand structural indices and stand structural parameters were weak, and, therefore, we cannot recommend the exclusive use of stand structural indices as alternative to the common stand structural parameters. Instead, the combined use of stand structural indices and parameters can be a robust solution for describing forest stand structure

Towards a better understanding of river dynamics in semi-urbanised areas: a machine learning analysis on time-series satellite images

River channels and floodplains have been highly modified over the last 70 years to mitigate flood risk and to gain lands for agricultural activities, settlements and soft infrastructures (e.g., cycle paths). River engineering measures simplified the geomorphologic complexity of river system, usually from braided or wandering channels to highly-confined single-thread channel. Meanwhile, rivers naturally adjust and self-organise the geomorphologic function as response of all the disturbances (e.g., flood events, river-bed degradation, narrowing, control works) altering sediment and water transfer, exacerbating bank erosion processes and streambank failures, and exposing bare sediment that can be subsequently colonized by pioneer species. In this context, river management has to address river dynamics planning sustainable practices with the aim to combine hydraulic safety, river functionality, and ecological/environmental quality. These actions require the detection of river processes by monitoring the geomorphological changes over time, both over the active riverbank and the close floodplains. Thus, remote sensing technology combined with machine learning algorithms offers a viable decision-making instrument (Piégay et al., 2020).This study proposes a procedure that consists in applying image segmentation and classification algorithms (i.e., Random Forest and dendrogram-based method) over time-series high resolution RGB-NIR satellite-images, to identify the fluvial forms (bars and islands), the vegetation patches and the active riverbed. The study focuses on three different reaches of Oglio River (Valcamonica, North Italy), representative of the most common geomorphic changes in Alpine rivers.The results clearly show the temporal evolution/dynamics of vegetated and non-vegetated bars and islands, as consequence of human and natural disturbances (flood events, riparian vegetation clear-cutting, and bank-protection works). Moreover, the procedure allows to distinguish two stages of riparian vegetation (i.e., pioneer and mature vegetated areas) and to quantify the timing of colonization and growth. Finally, the study proposes a practical application of the described methodology for river managers indicating which river management activity (including timing, intensity and economic costs) is more appropriate and sustainable for each studied reach

Towards More Sustainable Materials for Geo-Environmental Engineering: The Case of Geogrids

Plastic materials are widely used in geotechnical engineering, especially as geosynthetics. The use of plastic-based products involves serious environmental risks caused by their degradation. Innovative research has been focusing on biodegradable polymers of natural origin, especially on poly(lactic acid) (PLA), to reduce the use of plastics. This study aims to explore the potentiality of biopolymers for the production of geogrids, measuring the chemical and mechanical characteristics of raw materials and of prototype samples, similar to those available on the market. First, chemical composition and optical purity were determined by hydrogen nuclear magnetic resonance (1H-NMR) and polarimetry. Furthermore, samples of uniaxial and biaxial geogrids were custom-molded using a professional 3D printer. Mechanical properties were measured both on the filament and on the prototype geogrids. The maximum tensile resistance was 6.76 kN/m for the neat-PLA filament and 10.14 kN/m for uniaxial prototype geogrids produced with PLA-based polymer mixed with titanium dioxide. PLA-based materials showed higher tensile properties than polypropylene (PP), the most common petroleum derivative. Conversely, such biomaterials seem to be more brittle and with scarce elongation rate respect PP. Nonetheless, these results are encouraging and can support the use of PLA-based materials for innovative biodegradable geosynthetics production, especially if used in combination with live plants

Field Measurements of Passive Earth Forces in Steep, Shallow, Landslide‐Prone Areas

Passive earth resistance plays an important role in slope stability analyses for predicting shallow landslide susceptibility. Three‐dimensional models estimate the contribution of this factor to slope stability using geotechnical theories designed for retaining structures and add it to the resistive forces. Systematic investigations have not been conducted to quantify this resistance in soils experiencing compression during the triggering of shallow landslides. This study presents field‐scale experimental data of passive earth force for cohesive and frictional clayey gravel evaluated at different combinations of soil depths and slopes. The experimental setup included a specialized device composed of a steel structure and a stiff plate that moved toward a mass of soil. In both dynamic and quasi‐static states, force‐displacement curves and maximum compression resistance were determined for several water content conditions induced by a rainfall simulator. The maximum dynamic force ranged from 8.49 to 31.67 kN for soil depths ranging between 0.36 and 0.50 m, whereas the quasi‐static force corresponded to 60% of the dynamic force. Furthermore, rainfall generated an additional decrease of compression resistance compared to that measured in the field. A comparison of measured data with theoretical models of passive earth force indicated that Rankine's solution provided the best estimate, whereas the logarithmic spiral approach significantly overestimated passive earth force by up to 70%. Therefore, the correct choice of geotechnical formulation or the direct use of field measurements to estimate passive earth force may significantly improve the accuracy of 3‐D limit equilibrium models for assessing slope stability over natural landscapes

Towards More Sustainable Materials for Geo-Environmental Engineering: The Case of Geogrids

Plastic materials are widely used in geotechnical engineering, especially as geosynthetics. The use of plastic-based products involves serious environmental risks caused by their degradation. Innovative research has been focusing on biodegradable polymers of natural origin, especially on poly(lactic acid) (PLA), to reduce the use of plastics. This study aims to explore the potentiality of biopolymers for the production of geogrids, measuring the chemical and mechanical characteristics of raw materials and of prototype samples, similar to those available on the market. First, chemical composition and optical purity were determined by hydrogen nuclear magnetic resonance (1H-NMR) and polarimetry. Furthermore, samples of uniaxial and biaxial geogrids were custom-molded using a professional 3D printer. Mechanical properties were measured both on the filament and on the prototype geogrids. The maximum tensile resistance was 6.76 kN/m for the neat-PLA filament and 10.14 kN/m for uniaxial prototype geogrids produced with PLA-based polymer mixed with titanium dioxide. PLA-based materials showed higher tensile properties than polypropylene (PP), the most common petroleum derivative. Conversely, such biomaterials seem to be more brittle and with scarce elongation rate respect PP. Nonetheless, these results are encouraging and can support the use of PLA-based materials for innovative biodegradable geosynthetics production, especially if used in combination with live plants

Assessment of Reed Grasses (Phragmites australis) Performance in PFAS Removal from Water: A Phytoremediation Pilot Plant Study

Per- and polyfluoroalkyl substances (PFASs) have multiple emission sources, from industrial to domestic, and their high persistence and mobility help them to spread in all the networks of watercourses. Diffuse pollution of these compounds can be potentially mitigated by the application of green infrastructures, which are a pillar of the EU Green Deal. In this context, a phytoremediation pilot plant was realised and supplied by a contaminated well-located in Lonigo (Veneto Region, Italy) where surface and groundwaters were significantly impacted by perfluoroalkyl acids (PFAAs) discharges from a fluorochemical factory. The investigation involved the detection of perfluorobutanoic acid (PFBA), perfluorooctanoic acid (PFOA), perfluorobutanesulfonic acid (PFBS) and perfluorooctanesulfonic acid (PFOS) inside the inlet and outlet waters of the phytoremediation pilot plant as well as in reed grasses grown into its main tank. The obtained results demonstrate that the pilot plant is able to reduce up to 50% of considered PFAAs in terms of mass flow without an evident dependence on physico-chemical characteristics of these contaminants. Moreover, PFAAs were found in the exposed reed grasses at concentrations up to 13 ng g−1 ww. A positive correlation between PFAA concentration in plants and exposure time was also observed. In conclusion, this paper highlights the potential efficiency of phytodepuration in PFAS removal and recommends improving the knowledge about its application in constructed wetlands as a highly sustainable choice in wastewater remediation