Bizkaia Science and Technology Park

Measuring the resilience of historic areas is challenging due to their heterogeneity in scale, heritage type, multi-hazard exposure, and socio-cultural context, creating the need for a flexible framework aligned with the latest Intergovernmental Panel on Climate Change (IPCC) approaches. This study introduces the SHELTER framework, which takes the historic area as its primary unit of analysis while enabling a cross-scalar assessment, from artefact/building scale to urban and transregional contexts. Developed through a co-creation strategy and an extensive literature review, the framework integrates indicators for multidimensional, cross-scale, and systemic resilience assessment and monitoring. The indicators span hazards such as heatwaves, earthquakes, floods, subsidence, and wildfires and capture exposure and vulnerability, the latter being understood as the sensitivity and coping, adaptive, and transformative capacities of communities. Refinement using the RACER methodology yielded a concise yet comprehensive shortlist of indicators, providing both general overviews and specific insights tailored to historic environments. The framework’s efficacy was tested across five case studies, demonstrating adaptability and suitability in diverse historic areas. Overall, SHELTER moves beyond a traditional focus on physical vulnerability and risk management, offering a replicable, holistic set of resilience indicators that supports consistent assessment and monitoring while respecting the singularities of historic settings.

Traditional perception systems in automated driving have different constraints that do not allow for complete environmental awareness. Cooperative Perception (CP) addresses these limitations by sharing information between vehicles and/or infrastructure through Vehicle-to-Everything (V2X) communications. This collaborative approach mitigates occlusions and extends sensor coverage, proving essential for Cooperative Driving Automation (CDA). However, there are remaining challenges about its application in online real-world scenarios, such as CP information transmission and communication degradations. In this cooperative context, Motion Prediction (MP) proves to be crucial, since it provides a scene representation of all the agents with their positions, velocities and future trajectories. Thus, shared information between agents can improve each agent understanding of the overall scene. This paper introduces LFF - V2V, A Late Fusion Cooperative Framework in V2V Scenarios. It combines two state-of-the-art late fusion methods, Non-Maximum Suppression (NMS) and Weighted Box Fusion (WBF), with a mapless Hierarchical Vector Transformer (HiVT) motion prediction model. We have conducted an extensive evaluation in two environments: CARLA simulator and the real-world V2X-Real dataset, analyzing different communication strategies. Our results demonstrate the effectiveness of CP in improving object detection and motion prediction, even with degraded communications.

Quercetin (QUE), a natural flavonoid found in various fruits and vegetables, has diverse biological functions, including anti-inflammatory effects, regulation of cell adhesion and oxidative stress mitigation. In this study, sol-gel materials with increasing concentrations of quercetin (0.5, 1 and 2 wt%) were synthesised and applied onto titanium (Ti) surfaces as coatings. The materials were characterised physiochemically, and in vitro responses were examined using HOb osteoblastic cells and THP-1 macrophages. Human serum protein adsorption was evaluated using nLC-MS/MS. The incorporation of quercetin did not affect the sol-gel network cross-linking, and a controlled release of quercetin was achieved. The materials exhibited no cytotoxicity at any concentration. The HOb cells cultured on quercetin-doped materials were more elongated than those grown on QUE-free coatings, with protruding lamellipodia and increased cell surface. QUE-doped surfaces enhanced the expression of BMP-2, RANKL, and cell adhesion-related genes CTNNB1 and β-actin. In the THP-1 cells, pro-inflammatory gene expression (IL-1β, MCP-1 and iNOS) was down-regulated on 0.5QUE material, while it increased on 2QUE, as did the cytokine liberation. These changes correlated with altered protein adsorption patterns. The 2QUE coatings enhanced the adsorption of acute-phase proteins (SAA1, SAA2 and SAA4), indicating an inflammatory response; this behaviour was not seen on 0.5QUE. Moreover, cell adhesion (COF1, PROF1) and oxidative stress proteins (GPX3, SEPP1, AMBP) were preferentially adsorbed onto QUE-doped coatings. These results highlight the significance of optimising quercetin concentration in sol-gel coatings to modulate the immune response and enhance cell adhesion effectively.

Abstract The extraction of bioactive compounds from food wastes or by‐products with natural deep eutectic solvents (NADES) could be an attractive alternative to traditional hydroalcoholic extraction but needs to be optimized taking advantage of modeling. This work aims to propose, develop, and discuss a new model for the extraction of phenolic compounds from spent coffee grounds (SCGs) using NADES to overcome some gaps related to the kinetic extraction models and the surface response methodology. The model presented is based on the same assumption as the kinetic model, but improving it to be able to predict phenolic extraction changing different process parameters (e.g., water content, time of extraction, temperature, etc.) using betaine: triethylene glycol (molar ratio 1:2). The model was validated on the extraction of total phenolic compounds from SCG as a function of water content of NADES ranging from 30 to 60% v/v. There was good agreement between experimental and simulated data and even, in some cases, better than with the second‐order kinetic models. In addition, the new model needs fewer parameters to be regressed concerning the specific case investigated in this work. This model and methodology can be the basis for further modeling applicable to other bioactives, and/or other NADES and feedstocks.Practical ApplicationsNatural deep eutectic solvents (NADES) can be a potential sustainable solvent for the valorization of food by‐products as they can be used to extract bioactive compounds with high added value. This extraction process needs to be optimized depending on several factors like water content in NADES solution, solids ratio, extraction time, and temperature. The model validated in this work on spent coffee ground (SCG) could be used for this purpose, improving the gaps related to the kinetic extraction models and the surface response methodology (RSM). The new model enables predicting the behavior of the process as a function of the parameters previously mentioned and reduces the number of experimental trials required compared with RSM. In particular, the new model was validated on the variation of water content in NADES solution. Certainly, this model will need to be further validated, but, once further studies are conducted, this model could be used for scale‐up calculation and design optimization of the industrial process.

An isolate of chili pepper mild mottle virus (CPMMV-Sp; GenBank OQ920979) with a 99% identity to CPMMV (GenBank MN164455.1) was found in symptomatic pepper plants in Spain. RACE analysis, performed using a stem-loop primer developed in this study to prime at the end of the introduced poly(A)/(U) tail, revealed the presence of an extra 22 nt at the 5' end, starting with a cytosine, which were essential to generate infectious clones. However, the 5' terminal cytosine was dispensable for initiating the infection. The design of two specific digoxigenin riboprobes targeting the more divergent area of CPMMV-Sp, compared to the closely related bell pepper mottle virus (BPeMV) (identity percentage of 80.6% and 75.8%, respectively), showed that both probes specifically detected CPMMV-Sp when the hybridization was performed at 68ºC and 60ºC, respectively. However, the BPeMV probe, targeting a region with an 89.4% identity percentage to CPMMV-Sp, showed cross-hybridization at 60ºC but not at 68ºC. The comparison of the detection limits between molecular hybridization and RT-PCR techniques revealed that the former was 125 times less sensitive than RT-PCR. The analysis of the vertical transmission of CPMMV-Sp using seeds from naturally or mechanically infected pepper plants revealed a transmission percentage ranging from 0.9% to 8.5%. Finally, the analysis of the resistance of capsicum species carrying different alleles of the L gene (L1, L2, L3, and L4) revealed that varieties with the L1 gene were infected by CPMMV-Sp (20–40% of inoculated plants), while varieties with the L2, L3, and L4 genes were resistant.

ABSTRACTBackgroundAn optimal and correctly balanced metabolic status is essential to improve sports performance in athletes. Recent advances in omic tools, such as the lipid profile of the mature erythrocyte membranes (LPMEM), allow to have a comprehensive vision of the nutritional and metabolic status of these individuals to provide personalized recommendations for nutrients, specifically, the essential omega-3 and omega-6 fatty acids, individuating deficiencies/unbalances that can arise from both habitual diet and sportive activity. This work aimed to study the LPMEM in professional female football players during the football season for the first time and compare it with those defined as optimal values for the general population and a control group.MethodsAn observational study was carried out on female football players from the Athletic Club (Bilbao) playing in the first division of the Spanish league. Blood samples were collected at three points: at the beginning, mid-season, and end of the season for three consecutive seasons (2019–2020, 2020–2021, and 2021–2022), providing a total of 160 samples from 40 women. The LPMEM analysis was obtained by GC-FID by published method and correlated to other individual data, such as blood biochemical parameters, body composition, and age.ResultsWe observed a significant increase in docosahexaenoic acid (DHA) (p 0.048) and total polyunsaturated fatty acid (PUFA) (p 0.021) in the first season. In the second season, we observed a buildup in the membrane arachidonic acid (AA) (p < .001) and PUFA (p < .001) contents when high training accumulated. In comparison with the benchmark of average population values, 69% of the football players showed lower levels of omega-6 dihomo-γ-linolenic acid (DGLA), whereas 88%, 44%, and 81% of the participants showed increased values of AA, eicosapentaenoic acid (EPA), and the ratio of saturated and monounsaturated fatty acids (SFA/MUFA), respectively. Regarding relationships between blood biochemical parameters, body composition, and age with LPMEM, we observed some mild negative correlations, such as AA and SFA/MUFA ratio with vitamin D levels (coefficient = -0.34 p = .0019 and coefficient = -.25 p = .042); DGLA with urea and cortisol (coefficient = -0.27 p < .006 and coefficient = .28 p < .0028) and AA with age (coefficient = -0.33 p < .001).ConclusionIn conclusion, relevant variations in several fatty acids of the membrane fatty acid profile of elite female football players were observed during the competitive season and, in comparison with the general population, increased PUFA contents were confirmed, as reported in other sportive activities, together with the new aspect of DGLA diminution, an omega-6 involved in immune and anti-inflammatory responses. Our results highlight membrane lipidomics as a tool to ascertain the molecular profile of elite female football players with a potential application for future personalized nutritional strategies (diet and supplementation) to address unbalances created during the competitive season.