Biology subjects

Navarrete, S.

Publications and source records attributed to Navarrete, S..

4 recordsLinked to original sources

bioRxiv2025

Deep White-Matter Pathways Mediate the Link Between Docosahexaenoic Acid (DHA) Status and Cognitive Performance in Adolescence

Docosahexaenoic acid (DHA) is a polyunsaturated fatty acid enriched in neuronal membranes and myelin and associated with cognitive performance. However, nutritional interventions show inconsistent cognitive effects, partly due to limited knowledge of the neural pathways linking DHA status to human cognition during sensitive periods of white-matter maturation, such as adolescence. We addressed this gap by studying 99 adolescents drawn from both extremes of performance on a national scholastic examination. Participants completed assessments of scholastic achievement (SA) and intellectual ability (IA), provided erythrocyte DHA samples, and underwent multimodal MRI, including diffusion, T1-weighted, and T2-weighted imaging. Independent component analysis and Bayesian multivariate LASSO models identified brain components jointly associated with DHA and cognition. Across four MRI modalities, a single deep white-matter component consistently emerged as the strongest shared pathway linking DHA with cognition. Tract-resolved analyses highlighted predominant contributions from the fornix and thalamus-temporal fasciculus, with additional subcortical and cortical involvement. In joint models, these components predicted SA and IA after accounting for DHA and other fatty acids, consistent with an indirect, mediation-like pathway. These findings move beyond DHA-behavior correlations by identifying specific neuroanatomical pathways through which a modifiable dietary factor relates to adolescent learning and intellectual performance, offering mechanistic insight relevant to neuroscience, nutrition, and education. Significance StatementAdolescence is a sensitive period for the maturation of white-matter pathways that support learning and reasoning. Docosahexaenoic acid (DHA), an essential dietary fatty acid enriched in neuronal membranes and myelin, has been linked to cognitive performance, yet the neural mechanisms underlying this association remain unclear. Using multimodal MRI and Bayesian multivariate modeling in adolescents with high or low scholastic performance, identify a specific deep white-matter pathway--centered on the fornix and the thalamus-temporal fasciculus--as the principal route connecting DHA status with scholastic achievement and intellectual ability. Additional subcortical and cortical contributions reveal a coordinated system-level architecture. These findings move beyond correlations by providing mechanistic insight into how a modifiable nutritional factor relates to cognitive development, with implications for neuroscience, public health, and education.

neuroscience↗

bioRxiv2023

Easy, fast and reproducible Stochastic Cellular Automata with 'chouca'

Stochastic cellular automata (SCA) are models that describe spatial dynamics using a grid of cells that switch between discrete states over time. They are widely used to understand how small-scale processes scale up to affect ecological dynamics at larger spatial scales, and have been applied to a wide diversity of theoretical and applied problems in all systems, such as arid ecosystems, coral reefs, forests, bacteria, or urban growth. Despite their wide applications, SCA implementations are often ad-hoc, lacking performance, guarantees of correctness and poorly reproducible. De novo implementation of SCA for each specific system and application also represents a major barrier for many practitioners. To provide a unifying, well-tested technical basis to this class of models and facilitate their implementation, we built chouca, an R package that translates definitions of SCA models into compiled code, and runs simulations in an efficient way. chouca supports SCA based on rectangular grids where transition probabilities are defined for each cell, with performance typically two to three orders of magnitude above typical implementations in interpreted languages (e.g. R, Python), all while maintaining an intuitive interface in the R environment. Exact and mean-field simulations can be run, and both numerical and graphical results can be easily exported. Besides providing better reproducibility and accessibility, a fast engine for SCA unlocks novel, computationally intensive statistical approaches, such as simulation-based inference of ecological interactions from field data, which represents by itself an important avenue for research. By providing an easy and efficient entry point to SCAs, chouca lowers the bar to the use of this class of models for ecologists, managers and general practitioners, providing a leveled-off reproducible platform while opening novel methodological approaches.

ecology↗

bioRxiv2023

Unifying microorganisms and macrograzers in rocky shore ecological networks

Over the past decades, our understanding of the vital role microbes play in ecosystem processes has greatly expanded. However, we still have limited knowledge about how microbial communities interact with larger organisms. Many existing representations of microbial interactions are based on co-occurrence patterns, which do not provide clear insights into trophic or non-trophic relationships. In this study, we untangled trophic and non-trophic interactions between macroscopic and microscopic organisms on a marine rocky shore. Five abundant mollusk grazers were selected, and their consumptive (grazing) and non-consumptive (grazer pedal mucus) interactions with bacteria in biofilms were measured using 16S rRNA amplicon sequencing. While no significant effects on a commonly used measure of biofilm grazing (Chlorophyll-a concentration) were observed, detailed image analysis revealed that all grazers had a detrimental impact on biofilm cover. Moreover, different grazers exhibited distinct effects on various bacterial groups. Some groups, such as Rhodobacteraceae, Saprospiraceae, Flavobacteriaceae, and Halieaceae, experienced positive effects from specific grazers, while others, like Rhizobiaceae, Rhodobacteraceae, and Flavobacteriaceae were negatively affected by certain grazers. This study presents the first attempt to construct an interaction network between macroorganisms and bacteria. It demonstrates that the strength of trophic and non-trophic interactions varies significantly depending on the mollusk grazer or bacterial group involved. Notably, certain bacterial groups exhibited a generalized response, while others showed specialized responses to specific macroorganisms in trophic or non-trophic interactions. Overall, this work highlights the potential for integrating microbes into ecological networks, providing valuable insights and methodologies for quantifying interactions across Domains. This research complements the previous ecological network, showing that mollusk grazers interact not only trophically but also non-trophically with epilithic biofilms. It identifies three drivers affecting microbial community assembly, crucial for understanding macro-microorganism dynamics in intertidal systems.

ecology↗

bioRxiv2021

Microbial communities network structure across strong environmental gradients: How do they compare to macroorganisms?

The way strong environmental gradients shape multispecific assemblages has allowed us to examine a suite of ecological and evolutionary hypotheses about structure, regulation, and community responses to fluctuating environments. But whether the highly diverse co-occurring, free-living microorganisms are shaped in similar ways as macroscopic organisms, across the same gradients, has yet to be addressed in most ecosystems. The everything is everywhere hypothesis suggests they are not, at least not to the same extent. Here we characterize the structure of intertidal microbial biofilm communities and compare the intensity of zonation at the species level, changes in taxonomic diversity and composition at the community level, and network attributes, with those observed in co-occurring macroalgae and invertebrates. At the level of species and OTUs, for dominant macro and microorganisms respectively, microbes showed less variability across the tidal gradient than macroorganisms. At the community-level, however, microbes and macro-organisms showed similarly strong patterns of tidal zonation, with major changes in composition and relative abundances across tides. Moreover, the proportion of environmental specialists in different tidal zones was remarkably similar in micro and macroscopic communities, and taxonomic richness and diversity followed similar trends, with lower values in the high intertidal zone. Network analyses showed similar connectivity and transitivity, despite the large differences in absolute richness between the groups. A high proportion of positive co-occurrences within all tidal zones and mostly negative links between the high and low tidal zones were observed among habitat specialist taxa of micro-and macro-organisms. Thus, our results provide partial support to the idea that microbes are less affected by environmental variability than macroscopic counterparts. At the species-level, the most common microbe species exhibit less variation across tides than most common macroscopic organisms, suggesting the former perceive a more homogeneous environment and/or are more resistant to the associated stress. At the community-level, most indicators of community and network structure across the gradient are similar between microbes and macro-organisms, suggesting that despite orders of magnitude differences in richness and size, these two systems respond to stress gradients, giving rise to zonation patterns.

ecology↗