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Landscape analysis and Connectivity Index to assess debris flows susceptibility of recently deglaciated catchment (Presanella Group, Rhaetian Alps)
No full textHigh-altitude Alpine regions are highly sensitive to ongoing climate change, which affects cryosphere dynamics and intensifies slope processes. Since the Last Glacial Maximum, deglaciation has expanded paraglacial environments, increasing susceptibility to mass-wasting processes. Debris flows are particularly frequent and hazardous at higher recently deglaciated elevations but also affect lower catchment areas. We present a debris flow susceptibility map of Valpiana valley (Adamello-Presanella Group, Rhaetian Alps) based on landscape analysis and statistical selection of causal factors. Given the key role of debris flows in sediment transport, we assess connectivity between source areas and downstream sectors. Results indicate a significant rise in debris flow susceptibility from 1983 to 2015, with higher susceptibility classes expanding across 35% of the study area. This increase is pronounced on screes and debris cones, and has substantially intensified on Holocene glacial deposits as well, where 50% of the area belongs to the highest susceptibility class. High-susceptibility zones are increasingly concentrated along debris flow channels and in unconsolidated debris areas, while exposed bedrock sectors show reduced susceptibility. This spatial pattern appears strongly influenced by positive feedback associated with channel evolution following extreme rainfall in 1987, which triggered debris flows in specific areas, and is confirmed by statistical analysis. Among key causal factors, the contributing area remains the primary driver, exerting a growing impact over time. These findings highlight the increasing geomorphic instability of high-altitude Alpine landscapes due to climate-driven changes and emphasize the rising significance of debris flow processes in shaping paraglacial environments
Activity of chemotherapy in mesenchymal chondrosarcoma: a multicentre retrospective analysis within the Italian Sarcoma Group network
No full textBackground: Mesenchymal chondrosarcoma (MCS) is an ultra-rare sarcoma, molecularly defined by the HEY1::NCOA2 fusion, and characterized by a poor prognosis in the advanced phase. Data on the activity of systemic agents in MCS are only retrospective and limited to case reports or heterogeneous series. We report the results of an Italian, multicentric, retrospective study on the activity of cytotoxic chemotherapy in patients with MCS. Patients and methods: This retrospective, multicentre Italian Sarcoma Group study included patients with molecularly confirmed MCS, treated with anthracycline-based chemotherapy, high-dose ifosfamide (HD-IFX), or trabectedin between 2000 and 2022. Response to treatment was assessed retrospectively through imaging review. Survival outcomes were estimated by the Kaplan-Meier method. Results: Thirty-five patients were identified (19 = localized disease, 16 = advanced disease). Anthracycline-based regimens yielded an overall response rate (ORR) of 26% [95% confidence interval (CI) 15% to 50%]. Among patients with localized disease, Ewing-like regimens showed an ORR of 33.3% (95% CI 9.9% to 65.1%), median relapse-free survival (mRFS) of 86.9 months, and 5-year overall survival of 95%; other anthracycline combinations had an ORR of 40% (95% CI 5.3% to 85.3%) and mRFS of 32.6 months. In advanced disease, Ewing-like regimens yielded an ORR of 16.7% (95% CI 0.4% to 64.1%) and median progression-free survival (mPFS) of 13.2 months, while other anthracycline regimens resulted in an ORR of 22.2% (95% CI 15% to 50%) and mPFS of 9.3 months. HD-IFX showed no responses, with early progression in all cases. Trabectedin achieved stable disease in all four treated patients, with a median PFS of 16.9 months. Conclusions: This multicentre study confirms that anthracycline-based regimens show activity in MCS, with responses more in line with soft tissue sarcoma than Ewing sarcoma. Their benefit in localized disease remains uncertain, but (neo)adjuvant chemotherapy with Ewing-like regimens should be considered for patients eligible for surgery. In advanced disease, trabectedin may provide prolonged disease control after anthracyclines
The impact of albumin conjugation on the cytotoxic properties of cisplatin, oxaliplatin and auranofin in cancer cells
No full textThe role of human serum albumin (HSA) in the delivery of anticancer metallodrugs remains unclear and requires further investigation. To this end, bioconjugates of HSA with the metallodrugs cisplatin (CIS), oxaliplatin (OXA) and auranofin (AF) were prepared, characterised by ESI-MS and ICP, and tested for their cytotoxic properties in A2780 and HCT116 cancer cells. Significant differences in the biological activities of the two Pt bioconjugates compared to that of the Au bioconjugate emerged, and they are interpreted and discussed in the context of the available literature
Fossil Shark Tooth Classification Using Deep Learning for Paleontological Heritage
No full textThe paradigm of Deep Learning is entering all domains of knowledge, allowing for the creation of data analysis tools that assist subject matter experts. Paleontology is also experiencing this trend. In this study we investigated the ability of Convolutional Neural Networks (CNNs), a particular class of Deep Learning algorithms specifically crafted for computer vision tasks, to classify images of fossil shark teeth collected from various images datasets. We developed and trained from scratch a CNN, named SharkNet, for classification of images containing a single shark tooth, customizing its complexity to our needs. A specific dataset was built in order to train our CNN, composed by more than one thousands images representing 10 species of shark teeth. Images come from online datasets as well as from the paleoichthyological collection of the G.A.M.P.S. Geopaleontological Museum (Italy). SharkNet showed good performance, reaching a mean accuracy of 88%. The goal of the present project is two-fold: on the one hand, we aim to demonstrate how Deep Learning algorithms can be applied to assist in the creation of tools for use in research settings; on the other hand, we hope to stimulate reflection on how this technology can be exploited to find new ways for fruition by paleontological exhibits, for example by developing mobile app to be used by visitors
Interpretation of National Trends in Obstetric Anal Sphincter Injuries (Letter-to-the-Editor)
No full text
Triggering electron capture supernovae: Dark matter effects in degenerate white-dwarf-like cores of super-asymptotic giant branch stars
No full textElectron-capture supernovae (ECSNe) have emerged as a compelling formation channel for low-mass neutron stars, bolstered by decades of theoretical work and increasingly supported by observational evidence, including the recent identification of SN 2018zd. Motivated by this, we investigate the influence of fermionic asymmetric dark matter (ADM) on the equilibrium structure of progenitor cores and the formation of their neutron star remnants. Using a general relativistic two-fluid formalism, we model the coupled evolution of ordinary matter (OM) and ADM, treated as separately conserved fluids interacting solely through gravity. Our analysis focuses on neon-rich white dwarfs (Ne WDs), which are typical progenitor cores for ECSNe. We assume conservation of both baryon number (NB) and DM particle number (ND) during collapse, allowing for a consistent mapping between progenitor and remnant configurations. We find that ADM significantly enhances the central density of the WD progenitor. This lowers the threshold gravitational mass M⁎ required to initiate electron capture, enabling ECSNe from lower-mass progenitors. The resulting remnants are stable, DM-admixed neutron stars with gravitational masses potentially well below current observational bounds. Moreover, we find that the conversion energy during the WD-to-NS conversion is also significantly reduced for higher ADM particle masses and fractions, suggesting that unusually low-energy ECSNe may serve as potential indicators of ADM involvement in stellar collapse
Analysis and Forecasting of Energy Consumption of Innovative Heating and Cooling Generation Systems in Existing Healthcare Facilities
No full textItalian healthcare facilities are generally obsolete and energy-intensive buildings. It is essential to employ advanced technologies and predictive energy consumption estimates to optimize the use of energy resources, prevent inefficiencies and ensure continuous and high-quality service. This study describes the interventions aimed at energy saving in a group of 13 healthcare facilities managed by the Azienda USL Toscana Nord-Ovest, through the modernization of heat generation and cooling systems and the implementation of an advanced energy management system, within the framework of an Energy Performance Contract. This system is based on a large network of sensors, controllers, servers and a centralized control center, allowing remote and real-time management of energy production and distribution systems. An adaptive data-driven Grey-box model is being developed and is planned for implementation by the University of Pisa to identify the major sources of energy consumption in order to optimize energy performance. The results show a significant reduction in overall thermal and electrical consumption: after just one year, a 40% reduction was recorded compared to previous levels. The improvement interventions and the integrated remote management system have also led to increased environmental sustainability of the facilities, with a 41% reduction in CO2 emissions. The application of a centralized energy control system on large, complex and distributed facilities on such a vast territory represents is unprecedented in Europe. The results demonstrate the potential of this approach for improving energy efficiency and reducing the environmental impact of large-scale healthcare facilities
Bridging Gaps in Landslide Mapping: A Semi-Quantitative Empirical Framework for Delineating Key Areas to Improve Collection of Essential Field-Based and Supplementary Remote-Based Data
No full textAccurate landslide mapping near critical infrastructure requires not only data on landslide characteristics but also clear definitions of the spatial extent of surveyed areas. While national projects like Italian Landslide Inventory (IFFI) and Italian Guidelines for the classification and management of risk, safety assessment and monitoring of existing bridges (LLG 2022) provide a list of data to collect during a field visit survey, they lack clear specifications for buffer zones, limiting data comparability and risk assessment reliability. This study refines a hierarchical framework developed by the FABRE Geo Working Group, in alignment with LLG 2022, introducing five key zones—Landslide Inventory Reference Area, Diagnostic Area, Geomorphological Significant Area, Relevant Area and the Approach Zone, plus a newly defined Geomorphological Significant Area—Close Zone. By explicitly quantifying buffer zones and their hierarchical roles, the framework ensures consistent data collection across varied terrains and reduces ambiguity in landslide risk evaluation. Applied to 95 bridges in Tuscany and Basilicata, the framework offers standardized definitions and dimensions for Diagnostic Area, Geomorphological Significant Area and Relevant Area, based on detailed field surveys. Approach Zone and Geomorphological Significant Area—Close Zone are quantified as percentages of Relevant Area and Geomorphological Significant Area, supporting efficient, reproducible inspections using both manual and UAV-assisted methods. The Geomorphological Significant Area—Close Zone distinguishes core data, which requires direct surveys, from supplementary data that can be analyzed remotely or in the office. This distinction ensures that essential hazards are observed directly, while supplementary insights are efficiently integrated, enhancing field reliability and desk-based analysis. This integrated approach enhances the accuracy of landslide susceptibility assessment and the classification of attention levels, supporting the maintenance of the national IFFI. Ultimately, the comparison of IFFI catalog data, available in the Diagnostic Area, Geomorphological Significant Area, and Relevant Area, revealed previously unrecorded landslides in Matera and confirmed the reliability of the catalog in Lucca, highlighting that inventories can be systematically integrated only by using standardized areas with field verification to improve risk and infrastructure management. The structured framework bridges gaps between national inventory standards and localized survey needs, ensuring that both previously recorded and new landslide events are systematically captured
The ALPINE-CRISTAL-JWST Survey: JWST/IFU Optical Observations for 18 Main-sequence Galaxies at z = 4─6
No full textTo fully characterize the formation and evolution of galaxies, we need to observe their stars, gas, and dust on resolved spatial scales. We present the ALPINE-CRISTAL-JWST survey, which combines kiloparsec-resolved imaging and spectroscopy from the Hubble Space Telescope, JWST, and Atacama Large Millimeter/submillimeter Array for 18 representative main-sequence galaxies at z = 4-6 and log(M-*/M-circle dot)>9.5 to study their star formation, chemical properties, and extended gas reservoirs. The cospatial measurements resolving the ionized gas, molecular gas, stars, and dust on 1-2 kpc scales make this a unique benchmark sample for the study of galaxy formation and evolution at z similar to 5, connecting the Epoch of Reionization with the cosmic noon. In this paper, we outline the survey goals and sample selection, and present a summary of the available data for the 18 galaxies. In addition, we measure spatially integrated quantities (such as global gas metallicity), test different star formation rate indicators, and quantify the presence of H alpha halos. Our targeted galaxies are relatively metal rich (10%-70% solar), complementary to JWST samples at lower stellar mass, and there is broad agreement between different star formation indicators. One galaxy has the signature of an active galactic nuclei (AGN) based on its emission-line ratios. Six show broad H alpha emission suggesting type 1 AGN candidates. We conclude with an outlook on the exciting science that will be pursued with this unique sample in forthcoming papers