Nano eggshell lime for expansive soil stabilization: Trade-offs between material efficiency and environmental performance - Guilherme de Araújo Rochedo; Rodrigo Beck Saldanha; Nilo Cesar Consoli; Cindy Johanna Moncaleano Acosta; Andres Lotero; Cecília Gravina da Rocha (Transportation Geotechnics, 2026)

Characterization of the cemented matrix formed by alkali-activated ground granulated blast furnace slag in stabilized filtered gold tailings - Victor Nunez; Andres Lotero; Cindy Johanna Moncaleano; Nilo Cesar Consoli (Transportation Geotechnics, 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.

Influence of Moisture and Cement Content on the Undrained Shear Response of Iron Ore Tailings - Nilo Cesar Consoli; Aziz Tebechrani Neto; Alexia Cindy Wagner; João Vítor de Azambuja Carvalho; Lessandro de Almeida Franco; João Pedro Camelo Guedes; João Paulo de Sousa Silva (Geotechnical and Geological Engineering, 2025)

Mechanical Behaviour of Cemented Copper Tailings Under Isotropic Compression and Drained Triaxial Shearing for Filtered Stacking - Nilo Cesar Consoli; Carlos Alberto Simões Pires Wayhs; Hugo Carlos Scheuermann Filho; João Vítor Azambuja Carvalho; Alexia Cindy Wagner; João Paulo Sousa Silva; Matthew Richard Coop (Geotechnical and Geological Engineering, 2025)

Evaluation of Iron Ore Tailings During Dam Closure Using Instrumentation, Field Testing, and Numerical Modelling - Nilo Cesar Consoli; Alexia Cindy Wagner; Thatyane Martins Gonçalves; Gino Omar Calderón Vizcarra; Frank Pereira; João Vítor de Azambuja Carvalho (Geotechnical and Geological Engineering, 2025)

Mechanical Behavior of Artificially Cemented Iron Ore Tailings Under High Confining Pressures - Nilo Cesar Consoli; João Pedro Camelo Guedes; João Vítor de Azambuja Carvalho; Alexia Cindy Wagner; Hugo Carlos Scheuermann Filho; Inácio Diniz Carvalho; Bruno Guimarães Delgado; João Paulo de Sousa Silva; Matthew Richard Coop (Geotechnical and Geological Engineering, 2025)

Resilience of Compacted Iron Ore Tailings-Binder Blends for Dry Stacking - Nilo Cesar Consoli; Décio Collatto; João Vítor de Azambuja Carvalho; Alexia Cindy Wagner; João Paulo de Sousa Silva; Gustavo Marçal de Sousa; Hugo Carlos Scheuermann Filho (Geotechnical and Geological Engineering, 2025)

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.

Acclimation procedure: a neglected good management practice to mitigate post-transport stress in fish - Peterson Emmanuel Guimarães Paixão; Ricardo Marques Nogueira Filho; Cindy Caroline Moura Santos; Rubens Riscala Madi; Higo Andrade Abe; Márcia Valéria Silva do Couto; Hugo Leandro Santos; Fabricio Sa Santana; Amanda Silva Carvalho; Juliana Matos Araujo; Paulo Cesar Falanghe Carneiro; Rodrigo Yudi Fujimoto (Aquaculture International, 2024)

Potential Reuse of Andean Highlands Tin Tailings in Geotechnical Works Through Geopolymer Binder Stabilization - Durval Párraga Morales; Eduardo Orellana Rivera; Andres Lotero; Cindy Johanna Moncaleano; Nilo Cesar Consoli (Geotechnical and Geological Engineering, 2024)

Mechanical Behaviour of Fibre-Reinforced Cemented Iron Ore Tailings Across the Compaction Curve - João Pedro Camelo Guedes; Carina Silvani; João Vítor de Azambuja Carvalho; Alexia Cindy Wagner; João Paulo de Sousa Silva; Nilo Cesar Consoli (Geotechnical and Geological Engineering, 2024)

Dry Stacking of Filtered Iron Ore Tailings: Comparing On-Field Performance of Two Drying Methods - Ana Luisa Cesar Rissoli; Géssica Soares Pereira; Anselmo José Coelho Mendes; Hugo Carlos Scheuermann Filho; João Vítor de Azambuja Carvalho; Alexia Cindy Wagner; João Paulo de Sousa Silva; Nilo Cesar Consoli (Geotechnical and Geological Engineering, 2024)

Vulval apocrine adenocarcinoma with tumour-associated eosinophilia in a cat - Francisco O. Conrado; Lesli Kibler; Cindy Cesar; Cesar Piedra-Mora; Theresa G. Taylor (Journal of Comparative Pathology, 2023)

Pile Groups and Piled Footings Bearing in Weakly Cemented Residual Soil - Larissa Fernandes Sasso; Alexia Cindy Wagner; Cesar Alberto Ruver; Luizmar da Silva Lopes; Nilo Cesar Consoli (Geotechnical and Geological Engineering, 2023)

The Effect of Heavy Tamping on Structured Residual Clay Site - Matheus Miotto Rizzon; Alexia Cindy Wagner; Vinicius Batista Godoy; Eclesielter Batista Moreira; Nilo Cesar Consoli (Geotechnical and Geological Engineering, 2021)

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics - Mariana Nagy‐Reis; Júlia Emi de Faria Oshima; Claudia Zukeran Kanda; Francesca Belem Lopes Palmeira; Fabiano Rodrigues de Melo; Ronaldo Gonçalves Morato; Lilian Bonjorne; Marcelo Magioli; Caroline Leuchtenberger; Fabio Rohe; Frederico Gemesio Lemos; Felipe Martello; et al. (Ecology, 2020)
Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non‐detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non‐governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer‐reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non‐detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio‐temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large‐scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data.

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics - Clarissa Alves da Rosa; Bruno R. Ribeiro; Vanesa Bejarano; Fernando Henrique Puertas; Adriana Bocchiglieri; Adriana Loeser dos Santos Barbosa; Adriano Garcia Chiarello; Adriano Pereira Paglia; Adriele Aparecida Pereira; Adryelle Francisca de Souza Moreira; Agnis Cristiane de Souza; Aiesca Pellegrin; et al. (Ecology, 2020)
Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal‐central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus , Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. ( n = 37,782), Sus scrofa ( n = 6,730), and Canis familiaris ( n = 10,084); 17 species were represented by only one record (e.g., S yncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans ). Primates have the highest number of species in the data set ( n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata , and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation‐related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data.

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics - Paloma Marques Santos; Adriana Bocchiglieri; Adriano Garcia Chiarello; Adriano Pereira Paglia; Adryelle Moreira; Agnis Cristiane de Souza; Agustin Manuel Abba; Agustin Paviolo; Ailin Gatica; Akyllan Zoppi Medeiro; Alan Nilo Costa; Alberto Gonzalez Gallina; et al. (Ecology, 2019)
Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records ( n = 5,941), and Cyclopes sp. have the fewest ( n = 240). The armadillo species with the most data is Dasypus novemcinctus ( n = 11,588), and the fewest data are recorded for Calyptophractus retusus ( n = 33). With regard to sloth species, Bradypus variegatus has the most records ( n = 962), and Bradypus pygmaeus has the fewest ( n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data.