Fasciolosis, caused by Fasciola hepatica, is a snail-borne zoonotic disease of major veterinary importance, responsible for significant economic losses in livestock. Its transmission is strongly influenced by environmental and climatic conditions. In northwestern Argentina, particularly in Salta and Jujuy provinces, the disease is endemic; however, the environmental and spatial determinants of its distribution remain incompletely understood. This study aimed to identify environmental risk factors and spatial patterns associated with F. hepatica infection in herbivores to better understand its epidemiological dynamics and support targeted control strategies. A retrospective analysis was conducted using coproparasitological records from 1994 to 2025 from livestock in both provinces. A total of 12,465 fecal samples from multiple host species were analyzed. The infection status was related to climatic variables, topography, and edaphic characteristics. Temporal variability and clear seasonal patterns were observed, with higher positive frequency in late winter-early spring. In the multivariate analysis, higher soil pH, sand and silt content, and cation exchange capacity were positively associated with infection, while bulk density and soil organic carbon were negatively associated. Spatial analysis identified nine significant clusters, including a main high-risk cluster in the central-western region of Salta and the centralsouthern region of Jujuy provinces, as well as several smaller focal clusters with increased relative risk. These findings demonstrate that fasciolosis distribution is non-random and driven by the interaction between soil properties, climate, host species, and spatial heterogeneity. The results provide a basis for risk-based surveillance and targeted control strategies adapted to local environmental conditions.
Perceptual multistability, where constant sensory input yields alternating interpretations, reveals the brain’s inferential processes under ambiguity. Here we review evidence positioning multistability within the predictive coding framework, which models perception as hierarchical inference minimizing prediction errors between sensory input and top-down expectations. Neuroimaging, electrophysiology, and computational models indicate that perceptual alternations arise from dynamic cycles of prediction and error correction, mediated by oscillatory cortical interactions. Individual differences in switching dynamics correlate with cognitive traits and clinical conditions, reflecting variability in the precision weighting of sensory evidence and prior information. These findings suggest that multistable perception provides a valuable paradigm to investigate the neural and computational mechanisms of perception, cognition, and psychopathology. Understanding these dynamics may inform unified models bridging neuroscience, psychology, and clinical research, and guide future studies employing falsifiable predictive coding hypotheses.
A partir de la sistematización de una experiencia investigativa longitudinal (2013-2025) en barrios populares, el presente artículo problematiza la formación psicológica hegemónica en Argentina, históricamente marcada por un predominio clínico individualista y su extrapolación acrítica hacia lo social. Se propone la necesidad de una ruptura ontológica y epistemológica para la acción comunitaria en contextos de segregación urbana y pobreza estructural. A través de un diseño de investigación cualitativo de tipo estudio de caso instrumental, se exponen resultados que evidencian las respuestas comunitarias ante una presencia estatal intermitente a partir de experiencias en los barrios populares de la ciudad de Salta (Argentina). Los hallazgos destacan la feminización de la gestión comunitaria, la disonancia cartográfica entre el territorio vivido y el mapa normativo, y la emergencia de una comunidad en lucha como respuesta política. La discusión articula estos hallazgos con los aportes de la psicología social comunitaria, las epistemologías del sur y la economía feminista, concluyendo que la disciplina debe abandonar el rol de experto para adoptar una praxis sentipensante que politice el malestar, valide los saberes locales y acompañe la restitución de derechos vulnerados.
Ecological reconstruction of mine dump sites in cold-region environments is frequently constrained by limited availability of natural topsoil and harsh climatic conditions that hinder soil development and biological succession. In such settings, artificial soils derived from mineral substrates are increasingly used as alternatives to surface soil; however, their biological maturation relies strongly on microbial community establishment and evolution. This data article presents a microbial diversity dataset derived from black-clay-based artificial soils applied in a mine dump restoration system located in a cold and arid desert grassland. Soil samples were collected from restoration zones subjected to different microbial inoculation regimes, including full-process application of an ecological restoration bacteria consortium, single application, and untreated controls. To capture spatial and vertical heterogeneity, samples were obtained independently from upper aerobic layers and lower anaerobic layers across multiple sampling batches corresponding to different restoration stages. Microbial community composition was characterized using high-throughput sequencing of the bacterial 16S rRNA gene, generating raw sequence reads and a suite of processed datasets. These include taxonomic abundance tables, alpha- and beta-diversity metrics, distance matrices, hierarchical clustering outputs, shared operational taxonomic unit profiles, ecological niche breadth indices, beta-deviation measurements, and core community identification based on prevalence criteria. Network topology metrics derived from Zi-Pi analysis are also provided to support structural assessments of microbial associations. In addition, functional profiles were inferred from 16S rRNA gene data using PICRUSt2, producing pathway- and category-level functional prediction tables. All data files are organized with standardized metadata and fully documented analytical parameters to facilitate independent reuse. This dataset supports reanalysis of microbial community assembly, stratification, and temporal variation in artificial soil systems and can be applied in comparative studies, methodological benchmarking, and synthesis efforts related to mine-site restoration, artificial soil development, and microbial ecology in cold-region environments.
