Decarbonizing the maritime sector: cold ironing and e-fuels. Case study: Gran Canaria - Pablo Yánez-Rosales; Paula Ferreira; Julieta Schallenberg-Rodriguez; Alexis Lozano-Medina; B.del Rio-Gamero (Transportation Research Part D: Transport and Environment, 2026)

Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

A fast powerful X-ray transient from possible tidal disruption of a white dwarf - Dongyue Li; Wenda Zhang; Jun Yang; Jin-Hong Chen; Weimin Yuan; Huaqing Cheng; Fan Xu; Xinwen Shu; Rong-Feng Shen; Ning Jiang; Jiazheng Zhu; Chang Zhou; et al. (Science Bulletin, 2026)

Reconstructing ocean-atmosphere interactions in La Guajira upwelling system through organic and mineral proxies over the past 1800 years - Aura María Rodriguez-Burgos; Francisco Javier Briceño-Zuluaga; Heitor Evangelista; Valentina Flores-Aqueveque; Juliana Nogueira; Alexis Castillo; William Esteban Quiroga-Camargo; Mercedes Mendez-Millan; Abdelfettah Sifeddine (Palaeogeography, Palaeoclimatology, Palaeoecology, 2026)

Soft Range Limits Shape Sensitivity to Forest Cover More Strongly Than Hard Range Limits - Natasha R. Granville; Alex L. Pigot; Benjamin Howes; Luiz dos Anjos; Victor Arroyo‐Rodriguez; Luc Barbaro; Jos Barlow; Matthew G. Betts; Alexis Cerezo; Pedro F. Develey; Jack H. Hatfield; Hervé Jactel; et al. (Global Ecology and Biogeography, 2025)
Aim Land‐use change is a major threat to biodiversity, yet there remains considerable unexplained variation in how it affects different populations of the same species. Here, we examine how sensitivity to forest cover changes depending on proximity to different limits of a species' range. By comparing responses as species approach their coastal (‘hard’) and inland (‘soft’) range limits, we aim to provide insight into the relative influence of mass effects, as compared to abiotic and biotic environmental suitability in shaping population sensitivity. Location Global. Time Period 1996–2019. Major Taxa Studied Birds. Methods We combined data from several large databases to obtain a dataset of 2543 bird species surveyed across 116 studies, spanning six continents. Using expert‐verified range maps, we calculated the position of populations relative to their species' nearest inland (‘soft’) and coastal (‘hard’) range limits and categorised the inland limits as equatorward‐ or poleward‐ facing. We investigated how distance to range limits and forest cover, derived from a 30 m‐resolution global dataset, affect the probability of species' incidence. Results We found that bird populations are more sensitive to forest cover when located closer to their species' inland (‘soft’) range limits, whereas this was not the case at coastal (‘hard’) range limits. The heightened sensitivity to forest cover at soft range limits was similar regardless of whether the range limit faced equatorward or poleward. Main Conclusions These results highlight how populations close to the soft limits of their species' ranges are at higher risk of extirpation resulting from loss of forest cover. This suggests that environmental conditions (e.g., climate), which become more challenging away from the core of the species' range, drive variability in sensitivity to forest cover.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Calcium-based catalyst prepared in the presence of biopolymer/biomass for biodiesel production: Elucidating their influence on the catalytic efficiency - Yuliana Rodriguez; Sebastian Ponce; Mateus H. Keller; Karla Vizuete; Alexis Debut; Bruno S. Souza; José R. Mora (Biomass and Bioenergy, 2024)

Oligodeoxynucleotide IMT504: Effects on Central Nervous System Repair Following Demyelination - Patricia A. Mathieu; Yim Rodriguez Sampertegui; Fernanda Elias; Alexis Silva Silva; María de Luján Calcagno; Ricardo López; Ana M. Adamo (Molecular Neurobiology, 2024)

Tree-ring wood density reveals differentiated hydroclimatic interactions in species along a bioclimatic gradient - Marín Pompa-García; Eduardo Daniel Vivar-Vivar; Bruna Hornink; José Alexis Martínez-Rivas; Daigard Ricardo Ortega-Rodriguez; Mario Tomazello-Filho (Dendrochronologia, 2024)

Aluminum-based catalysts prepared in the presence of pectin for low-energy biodiesel production - Sebastian Ponce; Pablo A. Gangotena; Cahuenas Anthony; Yuliana Rodriguez; Heitor A.G. Bazani; Mateus H. Keller; Bruno S. Souza; Karla Vizuete; Alexis Debut; José R. Mora (Fuel, 2024)

MaPPeRTrac: A Massively Parallel, Portable, and Reproducible Tractography Pipeline - Lanya T. Cai; Joseph Moon; Paul B. Camacho; Aaron T. Anderson; Won Jong Chwa; Bradley P. Sutton; Amy J. Markowitz; Eva M. Palacios; Alexis Rodriguez; Geoffrey T. Manley; Shivsundaram Shankar; Peer-Timo Bremer; et al. (Neuroinformatics, 2024)

Unveiling Sticholysin II and plasmid DNA interaction: Implications for developing non-viral vectors - Felipe A. Escalona-Rodriguez; Yoelys Cruz-Leal; Javier La O-Bonet; Julio A. Pérez-Erviti; Mario Ernesto Valdés-Tresanco; Ada L. Rivero-Hernández; Maricary Sifontes-Niebla; Alexis Manso-Vargas; Belinda Sánchez; Carlos Alvarez; Leandro R.S. Barbosa; Rosangela Itri; et al. (Toxicon, 2024)

Kinetic study of the catalytic cracking of waste motor oil using biomass-derived heterogeneous catalysts - Yuliana Rodriguez; Renato Guerra; Karla Vizuete; Alexis Debut; Daniela Almeida Streitwieser; Jose R. Mora; Sebastian Ponce (Waste Management, 2023)

Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling - Mark A. Bourassa; Thomas Meissner; Ivana Cerovecki; Paul S. Chang; Xiaolong Dong; Giovanna De Chiara; Craig Donlon; Dmitry S. Dukhovskoy; Jocelyn Elya; Alexander Fore; Melanie R. Fewings; Ralph C. Foster; et al. (Frontiers in Marine Science, 2019)

Integrated Observations of Global Surface Winds, Currents, and Waves: Requirements and Challenges for the Next Decade - Ana B. Villas Bôas; Fabrice Ardhuin; Alex Ayet; Mark A. Bourassa; Peter Brandt; Betrand Chapron; Bruce D. Cornuelle; J. T. Farrar; Melanie R. Fewings; Baylor Fox-Kemper; Sarah T. Gille; Christine Gommenginger; et al. (Frontiers in Marine Science, 2019)

Measuring currents, ice drift, and waves from space: the Sea surface KInematics Multiscale monitoring (SKIM) concept - Fabrice Ardhuin; Yevgueny Aksenov; Alvise Benetazzo; Laurent Bertino; Peter Brandt; Eric Caubet; Bertrand Chapron; Fabrice Collard; Sophie Cravatte; Jean-Marc Delouis; Frederic Dias; Gérald Dibarboure; et al. (Ocean Science, 2018)
We propose a satellite mission that uses a near-nadir Ka-band Doppler radar to measure surface currents, ice drift and ocean waves at spatial scales of 40 km and more, with snapshots at least every day for latitudes 75 to 82°, and every few days for other latitudes. The use of incidence angles of 6 and 12° allows for measurement of the directional wave spectrum, which yields accurate corrections of the wave-induced bias in the current measurements. The instrument's design, an algorithm for current vector retrieval and the expected mission performance are presented here. The instrument proposed can reveal features of tropical ocean and marginal ice zone (MIZ) dynamics that are inaccessible to other measurement systems, and providing global monitoring of the ocean mesoscale that surpasses the capability of today's nadir altimeters. Measuring ocean wave properties has many applications, including examining wave–current interactions, air–sea fluxes, the transport and convergence of marine plastic debris and assessment of marine and coastal hazards.

Novel Formulation Strategy to Improve the Feasibility of Amifostine Administration - Kavitha Ranganathan; Eric Simon; Jeremy Lynn; Alicia Snider; Yu Zhang; Noah Nelson; Alexis Donneys; Jose Rodriguez; Lauren Buchman; Dawn Reyna; Elke Lipka; Steven R. Buchman (Pharmaceutical Research, 2018)

Rice ecosystem services in South-east Asia - Josef Settele; Kong Luen Heong; Ingolf Kühn; Stefan Klotz; Joachim H. Spangenberg; Gertrudo Arida; Alexis Beaurepaire; Silke Beck; Erwin Bergmeier; Benjamin Burkhard; Roland Brandl; Jesus Victor Bustamante; et al. (Paddy and Water Environment, 2018)

Tobacco and Cardiovascular Health - Prajeena Mainali; Sadip Pant; Alexis Phillip Rodriguez; Abhishek Deshmukh; Jawahar L. Mehta (Cardiovascular Toxicology, 2015)

Season and size effects: changes in the quality of gilthead sea bream (Sparus aurata L.) - R. RODRIGUEZ; E. FOUNTOULAKI; K. GRIGORAKIS; M. ALEXIS; R. FLOS (Mediterranean Marine Science, 2010)
The aim of this study was to investigate the potential effects of the harvesting season and fish size on the final quality of cage farmed gilthead sea bream (Sparus aurata). Morphometric analysis, fat stores estimation, fillet composition analysis, fillet fatty acids profile determination and sensory analysis were carried out on a commercially-sized cage farmed gilthead sea bream (Sparus aurata L.) population in April, June, July and November. Both season and size had a significant effect in morphometric characteristics. The most pronounced size effect was the change of fish shape, becoming rounder with fish growth, the increase of filleting yield and condition index. An increase of both peritoneal and perivisceral fat was observed in summer months. In general size had little effect on muscle composition. A significant size effect was observed in the fillet lipid content, which increased with it. Fillet lipid content was unexpected lower in the warm period (June-July). This can be possibly attributed to feeding restrictions that may have occurred, due to anoxic incidents related to high temperatures.Slight seasonal differentiations occurred in the muscle fatty acids. No significant differences were found in the organoleptic characteristics of the two size groups compared.

Abstracts of the 6th FECS Conference 1998 Lectures - F. Sherwood Rowland; Donald R. Blake; B. R. Larsen; Anne Lindskog; Peter J. Peterson; W. Peter Williams; T. J. Wallington; M. J. Pilling; N. Carslaw; D. J. Creasey; D. E. Heard; P. Jacobs; et al. (Environmental Science and Pollution Research, 1998)