38 research outputs found
Environment, vector, or host? Using machine learning to untangle the mechanisms driving arbovirus outbreaks
Climatic, landscape, and host features are critical components in shaping out-breaks of vector-borne diseases. However, the relationship between the outbreaks of vector-borne pathogens and their environmental drivers is typically complicated, nonlinear, and mayvary by taxonomic units below the species level (e.g., strain or serotype). Here, we aim tountangle how these complex forces shape the risk of outbreaks of Bluetongue virus (BTV); avector-borne pathogen that is continuously emerging and re-emerging across Europe, with sev-ere economic implications. We tested if the ecological predictors of BTV outbreak risk wereserotype-specific by examining the most prevalent serotypes recorded in Europe (1, 4, and 8).We used a robust machine learning (ML) pipeline and 23 relevant environmental features to fitpredictive models to 24,245 outbreaks reported in 25 European countries between 2000 and2019. Our ML models demonstrated high predictive performance for all BTV serotypes (accu-racies>0.87) and revealed strong nonlinear relationships between BTV outbreak risk andenvironmental and host features. Serotype-specific analysis suggests, however, that each of themajor serotypes (1, 4, and 8) had a unique outbreak risk profile. For example, temperature andmidge abundance were as the most important characteristics shaping serotype 1, whereas forserotype 4 goat density and temperature were more important. We were also able to identifystrong interactive effects between environmental and host characteristics that were also sero-type specific. Our ML pipeline was able to reveal more in-depth insights into the complex epi-demiology of BTVs and can guide policymakers in intervention strategies to help reduce theeconomic implications and social cost of this important pathogen
Mainstreaming microbes across biomes
Bacteria, fungi, and other microorganisms in the environment (i.e., environmental microbiomes) provide vital ecosystem services and affecthuman health. Despite their importance, public awareness of environmental microbiomes has lagged behind that of human microbiomes. A keyproblem has been a scarcity of research demonstrating the microbial connections across environmental biomes (e.g., marine, soil) and betweenenvironmental and human microbiomes. We show in the present article, through analyses of almost 10,000 microbiome papers and threeglobal data sets, that there are significant taxonomic similarities in microbial communities across biomes, but very little cross-biome researchexists. This disconnect may be hindering advances in microbiome knowledge and translation. In this article, we highlight current and potentialapplications of environmental microbiome research and the benefits of an interdisciplinary, cross-biome approach. Microbiome scientists needto engage with each other, government, industry, and the public to ensure that research and applications proceed ethically, maximizing thepotential benefits to society
Spatial Learning and Action Planning in a Prefrontal Cortical Network Model
The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to
spatial cognition. Complementing hippocampal place coding, prefrontal
representations provide more abstract and hierarchically organized memories
suitable for decision making. We model a prefrontal network mediating
distributed information processing for spatial learning and action planning.
Specific connectivity and synaptic adaptation principles shape the recurrent
dynamics of the network arranged in cortical minicolumns. We show how the PFC
columnar organization is suitable for learning sparse topological-metrical
representations from redundant hippocampal inputs. The recurrent nature of the
network supports multilevel spatial processing, allowing structural features of
the environment to be encoded. An activation diffusion mechanism spreads the
neural activity through the column population leading to trajectory planning.
The model provides a functional framework for interpreting the activity of PFC
neurons recorded during navigation tasks. We illustrate the link from single
unit activity to behavioral responses. The results suggest plausible neural
mechanisms subserving the cognitive “insight” capability originally
attributed to rodents by Tolman & Honzik. Our time course analysis of neural
responses shows how the interaction between hippocampus and PFC can yield the
encoding of manifold information pertinent to spatial planning, including
prospective coding and distance-to-goal correlates