Biology subjects

D'Amico, G.

Publications and source records attributed to D'Amico, G..

4 recordsLinked to original sources

bioRxiv2026

β3-Integrin controls pericyte metabolic states and shapes tumour-stromal metabolic crosstalk in breast cancer

Pericytes are emerging as dynamic regulators of the tumour microenvironment. Yet, their role in tumour metabolism remains elusive. Here, we investigate whether {beta}3-integrin regulates pericyte metabolic state and shapes stromal-tumour metabolic interactions in breast cancer. By integrating spatial and single-cell transcriptomics from human breast tumours with multi-omics profiling of tumour-derived pericytes in vitro, we identify two {beta}3-integrin-dependent metabolic states. {beta}3-integrin-high pericytes display a metabolically active phenotype characterised by increased glycolysis and enhanced de novo serine/glycine synthesis, supporting collagen production. In contrast, {beta}3-integrin loss induces a lipid-associated state, marked by neutral lipid accumulation and lipid droplets. Mechanistically, {beta}3-integrin regulates this metabolic switch via mTOR signalling. Importantly, these states extend beyond pericytes, with adjacent cancer cells shifting towards fatty acid oxidation and lipid use near {beta}3-integrin-low pericytes. Together, our findings establish {beta}3-integrin as a key metabolic switch in pericytes and highlight their role in driving tumour metabolic plasticity.

cancer biology↗

bioRxiv2026

Investigating climate-phenology relationships among the most common Italian forest species using Sentinel-2-derived vegetation phenology and productivity products

Climate change is profoundly altering forest phenology and productivity across Europe, with particularly strong impacts in Mediterranean regions characterized by high climatic heterogeneity. Understanding how climatic and site-specific drivers regulate the start, end, and length of the growing season, and how these phenological shifts translate into productivity responses, remains a key challenge for predicting forest carbon dynamics. In this study, we investigate phenological timing and total seasonal productivity across multiple Italian forest species spanning Mediterranean, temperate, and mountain environments, leveraging the new High-Resolution Vegetation Productivity and Phenology product from the Copernicus Land Monitoring Service, machine learning (random forests) modeling, and explainable artificial intelligence analysis (SHAP). Our results confirm a general lengthening of the growing season driven mainly by chilling accumulation and spring temperatures. Warmer conditions advance the start of the season by 1-10 days across species, while the combined effects of temperature, radiation, and moisture can extend the growing season by up to 20-30 days. End-of-season dynamics and season length are more strongly controlled by light and water availability than by temperature alone. In several Mediterranean species, the end of the season can advance by up to 40 days due to summer drought, high vapor pressure deficit, and site exposure. Mediterranean species often show compensatory shifts between season onset and senescence, maintaining a relatively stable length of the season, whereas mountain species exhibit a tighter coupling between delayed onset and shortened season length. Phenological shifts are frequently decoupled from productivity, which is mainly regulated by energy and water availability, highlighting species- and site-specific responses to climate change. The findings of this study highlight the substantial advantage of remote sensing data, coupled with machine learning approaches, for advancing the understanding of forest phenology and productivity across broad spatial and climatic gradients.

ecology↗

bioRxiv2026

Integrating Earth Observation and Graph Theory to Evaluate Urban Green Spaces Connectivity Across European Capitals

ContextAs global urbanization intensifies, Urban Green Spaces (UGS) are pivotal for biodiversity conservation and climate change mitigation. However, comparative assessments of UGS spatial configuration and connectivity across diverse urban landscapes remain limited. ObjectivesThis study aims to assess the spatial arrangement and connectivity of UGS across 28 European capital cities. Additionally, we evaluate how Network Science metrics derived from Graph Theory can complement traditional landscape ecology metrics to provide a more comprehensive understanding of UGS at a large scale. MethodsWe developed a European Urban Vegetation Map using Earth observation data to classify UGS at 10m resolution across the selected capitals. We then analyzed UGS connectivity for each city utilizing 40 traditional landscape metrics and a Graph-Theory-based approach. ResultsWhile traditional landscape metrics effectively quantified fragmentation, they often remain strongly correlated with total vegetation abundance. In contrast, Network Science metrics provided specific insights into UGS functional connectivity, distinguishing the quality of ecological links beyond spatial proximity. This integration allowed us to cluster European capitals into three distinct typologies: unconnected compact cities, large metropolises with complex peri-urban dynamics, and high-connectivity cities with robust networks. These findings demonstrate that graph-based indices effectively complement traditional metrics, highlighting that relying solely on green space percentage is insufficient for assessing the ecological resilience of urban environments. ConclusionsThese results underscore the relevance of Earth observation-based UGS assessment and demonstrate that graph-based landscape connectivity analysis outperforms simple abundance metrics. Therefore, effective assessment requires integrating structural metrics with graph-based connectivity to support resilient urban biodiversity.

ecology↗

bioRxiv2024

Stand Age and Climate Change Effects on Carbon Increments and Stock Dynamics

Carbon assimilation and wood production are influenced by environmental conditions and endogenous factors, such as species auto-ecology, age, and hierarchical position within the forest structure. Disentangling the intricate relationships between those factors is more pressing than ever due to climate changes pressure. We employed the 3D-CMCC-FEM model to simulate undisturbed forests of different ages under four climate change scenarios (plus one no climate change) from five Earth System Models. In this context, carbon stocks and increment were simulated via total car-bon woody stocks and mean annual increment, which depends mainly on climate trends. We find greater differences among different age cohorts under the same scenario than in different climate scenarios under the same age class. Increasing temperature and changes in precipitation patterns led to a decline in above-ground biomass in spruce stands, espe-cially in the older age classes. On the contrary, the results show that beech forests at DK-Sor will maintain and even increase C-storage rates under most RCP scenarios. Scots pine forests show an intermediate behavior with a stable stock capacity over time and in different scenarios but with decreasing mean volume annual increment. These results confirm current observations worldwide that indicate a stronger climate-related decline in conifers forests than in broadleaves.

ecology↗