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Stroke is a leading cause of death and disability globally, with frequent cognitive sequelae affecting up to 60% of stroke survivors. Despite the high prevalence of post-stroke cognitive impairment (PSCI), early detection remains underemphasized in clinical practice, with limited focus on broader neuropsychological and affective symptoms. Stroke elevates dementia risk and may act as a trigger for progressive neurodegenerative diseases. However, the underlying neurobiological mechanisms and the interaction between vascular and degenerative pathways are poorly understood. The ICTUSCOG study aims to address these gaps by determining the incidence, predictors and progression factors of PSCI in a prospective, multicenter cohort of nondisabling stroke patients. The work will explore distinct patient profiles, evaluate the role of biomarkers, and develop a predictive model to identify at risk individuals. ICTUSCOG is a five-year observational project involving four Spanish centres. Recruitment began in 2022 and includes consecutive patients aged 18-75 with no prior cognitive impairment and nondisabling stroke. Participants undergo detailed neuropsychological, functional, and neuroimaging assessments at baseline, 3, 6, and 12 months, and annually thereafter. Key data include stroke characteristics, vascular risk factors, advanced neuroimaging metrics, and biological biomarkers. Neuropsychological assessments incorporate domain-specific validated tools tailored for stroke patients. The study will quantify the incidence of early and late PSCI, identify predictors of progression, and characterise cognitive profiles. Multivariate models and clustering techniques will explore interactions among clinical, biological and imaging data. A predictive model will be developed and validated for clinical use. ICTUSCOG will provide critical insights into the mechanisms and trajectories of PSCI, informing prevention, early intervention, and rehabilitation strategies. The work aims to establish predictive tools and care pathways to mitigate the burden of cognitive impairment in stroke survivors.

Stroke is a leading cause of death and disability globally, with frequent cognitive sequelae affecting up to 60% of stroke survivors. Despite the high prevalence of post-stroke cognitive impairment (PSCI), early detection remains underemphasized in clinical practice, with limited focus on broader neuropsychological and affective symptoms. Stroke elevates dementia risk and may act as a trigger for progressive neurodegenerative diseases. However, the underlying neurobiological mechanisms and the interaction between vascular and degenerative pathways are poorly understood. The ICTUSCOG study aims to address these gaps by determining the incidence, predictors and progression factors of PSCI in a prospective, multicenter cohort of nondisabling stroke patients. The work will explore distinct patient profiles, evaluate the role of biomarkers, and develop a predictive model to identify at risk individuals. ICTUSCOG is a five-year observational project involving four Spanish centres. Recruitment began in 2022 and includes consecutive patients aged 18-75 with no prior cognitive impairment and nondisabling stroke. Participants undergo detailed neuropsychological, functional, and neuroimaging assessments at baseline, 3, 6, and 12 months, and annually thereafter. Key data include stroke characteristics, vascular risk factors, advanced neuroimaging metrics, and biological biomarkers. Neuropsychological assessments incorporate domain-specific validated tools tailored for stroke patients. The study will quantify the incidence of early and late PSCI, identify predictors of progression, and characterise cognitive profiles. Multivariate models and clustering techniques will explore interactions among clinical, biological and imaging data. A predictive model will be developed and validated for clinical use. ICTUSCOG will provide critical insights into the mechanisms and trajectories of PSCI, informing prevention, early intervention, and rehabilitation strategies. The work aims to establish predictive tools and care pathways to mitigate the burden of cognitive impairment in stroke survivors.

Polar lows (PLs), which are intense maritime polar mesoscale cyclones, are associated with severe weather conditions. Due to their small size and rapid development, PL forecasting remains a challenge. Convection-permitting models are adequate to forecast PLs since, compared to coarser models, they provide a better representation of convection as well as surface and near-surface processes. A PL that formed over the Norwegian Sea on 25 March 2019 was simulated using the convection-permitting Canadian Regional Climate Model version 6 (CRCM6/GEM4, using a grid mesh of 2.5 km) driven by the reanalysis ERA5. The objectives of this study were to quantify the impact of the initial conditions on the simulation of the PL, and to assess the skill of the CRCM6/GEM4 at reproducing the PL. The results show that the skill of the CRCM6/GEM4 at reproducing the PL strongly depends on the initial conditions. Although in all simulations the synoptic environment is favourable for PL development, with a strong low-level temperature gradient and an upper-level through, only the low-level atmospheric fields of three of the simulations lead to PL development through baroclinic instability. The two simulations that best captured the PL represent a PL deeper than the observed one, and they show higher temperature mean bias compared to the other simulations, indicating that the ocean surface fluxes may be too strong. In general, ERA5 has more skill than the simulations at reproducing the observed PL, but the CRCM6/GEM4 simulation with initialisation time closer to the genesis time of the PL reproduces quite well small scale features as low-level baroclinic instability during the PL development phase.

Glial-origin brain tumors, including glioblastomas (GBM), have one of the worst prognoses due to their rapid and fatal progression. From an oncological point of view, advances in complete surgical resection fail to eliminate the entire tumor and the remaining cells allow a rapid recurrence, which does not respond to traditional therapeutic treatments. Here, we have reviewed new immunotherapy strategies in association with the knowledge of the immune micro-environment. To understand the best lines for the future, we address the advances in the design of neoantigen vaccines and possible new immune modulators. Recently, the efficacy and availability of vaccine development with different formulations, especially liposome plus mRNA vaccines, has been observed. We believe that the application of new strategies used with mRNA vaccines in combination with personalized medicine (guided by different omic’s strategies) could give good results in glioma therapy. In addition, a large part of the possible advances in new immunotherapy strategies focused on GBM may be key improving current therapies of immune checkpoint inhibitors (ICI), given the fact that this type of tumor has been highly refractory to ICI.

Polar lows (PLs) are high-latitude intense maritime mesoscale weather systems that develop over open water near the sea ice margin or near snow-covered continents during cold air outbreaks. PLs pose a threat to coastal and island communities, transportation and offshore drilling platforms. PLs mainly develop during the cold season and their frequency exhibits a large interannual variability. Observations from polar-orbiting satellites are the main source of observational data to study PLs since conventional observations are sparse and unevenly distributed in high latitudes. PL forecasting has long remained a challenge due to the small size and short lifetime of these systems. Nevertheless, the representation of PLs in numerical models has significantly improved with the advent of high-resolution atmospheric models. Several studies have shown that baroclinic instability and convection play an important role in the development of PLs, but a thorough understanding of the physical mechanisms involved in the formation and intensification of PLs is yet to be developed. The relevant role of surface sensible heat flux and latent heat release in PL development has often been highlighted. The diabatic fluxes from the oceanic surface and associated with PLs can cause a decrease in the sea surface temperature (SST), whereas the strong wind speeds can lead to upper-ocean mixing in regions where an ocean temperature inversion is present. It is expected that global warming associated with anthropogenic climate changes may lead to an increase in the static stability of the atmosphere, thus affecting the climatology of PLs. In the North Atlantic the regions of PL activity will shift northwards as seasonal sea-ice margins migrate towards higher latitudes areas, and the frequency of PLs will decrease. Although our knowledge about PLs has significantly increased during the last decades, the are still many unanswered questions. Among the most pressing issues in PL research are the need to determine the objective criteria that define PLs and to devise an international intercomparison project of PL detection and tracking.

Demands for tomato local varieties are increasing worldwide, especially in organic farming mainly for their high sensory value and attractive appearance. This is the case of the “Moruno” tomato type, widely grown in the Mediterranean countries and greatly due to its highly appreciated organoleptic attributes but low yield or a short postharvest period. For this reason, the study aimed to assess if grafting of local “Moruno” populations (Mor-62, Mor-204) using commercial rootstocks (King-Kong F1, K; Multifort F1, M; Spirit F1, S) affects yield, fruit nutritional and functional composition, postharvest storage and consumer acceptance. Results showed differences between both populations, while rootstocks were only different for the glucose content and the flavour quality. Grafting improved the marketable yield (~43%), fruit number (~22%) and mean fruit weight (~12%), but had no incidence on the blossom-end rot disorder. This technique increased the carotenoid (lycopene, β-carotene and total carotene) content but decreased the organic acids (malic and citric) and sugar (fructose and glucose) rates, while ascorbic acid was not affected. The fruit postharvest storage was not practically modified. However, the overall flavour preference and visual appearance varied depending on the scion.

Polar lows (PLs) are intense maritime mesoscale cyclones that often form during marine cold air outbreaks. The objective of this study is to determine the atmospheric model horizontal resolution needed to correctly represent PLs for climate modelling. Three simulations have been conducted with the Weather Research and Forecasting (WRF) model using grid spacings of 50, 25 and 12.5 km. PLs have been tracked using a combination of objective and subjective tracking methods. The number of PLs detected in each simulation increases, and their average equivalent radius decreases, as the model resolution increases. A comparison against three PL track climatologies shows that the hit rate increases with increasing resolution of the atmospheric model. The lifetime maxima of the area‐maximum 10‐m wind speed and area‐average surface sensible heat fluxes associated with PLs are on average 12% and 20% larger, respectively, in the higher‐resolution simulations than in the lower‐resolution one. The lifetime maximum of the area‐maximum 1‐h accumulated precipitation is 67% and 133% larger in the 25‐ and 12.5‐km simulations, respectively, than in the lower‐resolution one. We conclude that a better representation of PLs can be obtained by increasing the resolution of atmospheric models from 50 to 25 km, but further increasing the resolution to 12.5 km will not result in a substantial improvement. Climate studies are needed to determine how polar lows affect the ocean circulation. Here, we determine the model resolution needed to represent such polar lows considering grid spacings of 12.5, 25 and 50 km. Their number increases with resolution and the surface winds, associated sensible surface fluxes and precipitation are significantly higher in the two finest compared to the coarsest‐resolution simulations. However, there are smaller differences between the two finest‐resolution simulations implying that increasing model resolution beyond 25‐km spacing may not lead to substantial additional benefits.

Stroke is a leading cause of death and disability globally, with frequent cognitive sequelae affecting up to 60% of stroke survivors. Despite the high prevalence of post-stroke cognitive impairment (PSCI), early detection remains underemphasized in clinical practice, with limited focus on broader neuropsychological and affective symptoms. Stroke elevates dementia risk and may act as a trigger for progressive neurodegenerative diseases. However, the underlying neurobiological mechanisms and the interaction between vascular and degenerative pathways are poorly understood. The ICTUSCOG study aims to address these gaps by determining the incidence, predictors and progression factors of PSCI in a prospective, multicenter cohort of nondisabling stroke patients. The work will explore distinct patient profiles, evaluate the role of biomarkers, and develop a predictive model to identify at risk individuals. ICTUSCOG is a five-year observational project involving four Spanish centres. Recruitment began in 2022 and includes consecutive patients aged 18-75 with no prior cognitive impairment and nondisabling stroke. Participants undergo detailed neuropsychological, functional, and neuroimaging assessments at baseline, 3, 6, and 12 months, and annually thereafter. Key data include stroke characteristics, vascular risk factors, advanced neuroimaging metrics, and biological biomarkers. Neuropsychological assessments incorporate domain-specific validated tools tailored for stroke patients. The study will quantify the incidence of early and late PSCI, identify predictors of progression, and characterise cognitive profiles. Multivariate models and clustering techniques will explore interactions among clinical, biological and imaging data. A predictive model will be developed and validated for clinical use. ICTUSCOG will provide critical insights into the mechanisms and trajectories of PSCI, informing prevention, early intervention, and rehabilitation strategies. The work aims to establish predictive tools and care pathways to mitigate the burden of cognitive impairment in stroke survivors.

In recent years, global health security has been threatened by the geographical expansion of vector-borne infectious diseases such as malaria, dengue, yellow fever, Zika and chikungunya. For a range of these vector-borne diseases, an increase in residual (exophagic) transmission together with ecological heterogeneity in everything from weather to local human migration and housing to mosquito species’ behaviours presents many challenges to effective mosquito control. The novel use of drones (or uncrewed aerial vehicles) may play a major role in the success of mosquito surveillance and control programmes in the coming decades since the global landscape of mosquito-borne diseases and disease dynamics fluctuates frequently and there could be serious public health consequences if the issues of insecticide resistance and outdoor transmission are not adequately addressed. For controlling both aquatic and adult stages, for several years now remote sensing data have been used together with predictive modelling for risk, incidence and detection of transmission hot spots and landscape profiles in relation to mosquito-borne pathogens. The field of drone-based remote sensing is under continuous change due to new technology development, operation regulations and innovative applications. In this review we outline the opportunities and challenges for integrating drones into vector surveillance (i.e. identification of breeding sites or mapping micro-environmental composition) and control strategies (i.e. applying larval source management activities or deploying genetically modified agents) across the mosquito life-cycle. We present a five-step systematic environmental mapping strategy that we recommend be undertaken in locations where a drone is expected to be used, outline the key considerations for incorporating drone or other Earth Observation data into vector surveillance and provide two case studies of the advantages of using drones equipped with multispectral cameras. In conclusion, recent developments mean that drones can be effective for accurately conducting surveillance, assessing habitat suitability for larval and/or adult mosquitoes and implementing interventions. In addition, we briefly discuss the need to consider permissions, costs, safety/privacy perceptions and community acceptance for deploying drone activities. Graphical Abstract