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The Soudan Underground Mine State Park, found in the Vermilion Iron Range in northern Minnesota, provides access to a ~ 2.7 billion-year-old banded iron formation. Exploratory boreholes drilled between 1958 and 1962 on the 27th level (713 m underground) of the mine intersect calcium and iron-rich brines that have recently been subject to metagenomic analysis and microbial enrichments. Using concentrated brine samples pumped from a borehole depth of up to 55 m, a novel Gram-positive bacterium was enriched under anaerobic, acetate-oxidizing, and Fe(III) citrate-reducing conditions. The isolated bacterium, designated strain MK1, is non-motile, rod-shaped, spore-forming, anaerobic, and mesophilic, with a growth range between 24°C and 30°C. The complete circular MK1 genome was found to be 3,720,236 bp and encodes 25 putative multiheme cytochromes, including homologs to inner membrane cytochromes in the Gram-negative bacteriumGeobacter sulfurreducensand cytoplasmic membrane and periplasmic cytochromes in the Gram-positive bacteriumThermincola potens. However, MK1 does not encode homologs of the peptidoglycan (CwcA) and cell surface-associated (OcwA) multiheme cytochromes proposed to be required byT. potensto perform extracellular electron transfer. The 16S rRNA gene sequence of MK1 indicates that its closest related isolate isDesulfitibacter alkalitoleransstrain sk.kt5 (91% sequence identity), which places MK1 in a novel genus within theDesulfitibacteraceaefamily andMoorellalesorder. Within theMoorellalesorder, onlyCalderihabitans maritimusstrain KKC1 has been reported to reduce Fe(III), and onlyD. alkalitoleranscan also grow in temperatures below 40°C. Thus, MK1 represents a novel species within a novel genus, for which we propose the name “Metallumcola ferriviriculae”strain MK1, and provides a unique opportunity to study a cytochrome-rich, mesophilic, Gram-positive, spore-forming Fe(III)-reducing bacterium.

The Soudan Underground Mine State Park gives access to understudied regions of the deep terrestrial subsurface that potentially predate the Great Oxidation Event. Studying organisms that have been relatively unperturbed by surface conditions for as long as 2.7 billion years may give us a window into ancient life before oxygen dominated the planet. Additionally, studying microbes from anoxic and iron-rich environments can help us better understand the requirements of life in analogous environments, such as on Mars. The isolation and characterization of “Metallumcola ferriviriculae”strain MK1 give us insights into a novel genus and species that is distinct both from its closest related isolates and from iron reducers characterized to date. “M. ferriviriculae”strain MK1 may also act as a model organism to study how the processes of sporulation and germination are affected by insoluble extracellular acceptors, as well as the impact of spores in the deep terrestrial biosphere.

 

Scalp Electroencephalography (EEG) is one of the most popular noninvasive modalities for studying real-time neural phenomena. While traditional EEG studies have focused on identifying group-level statistical effects, the rise of machine learning has prompted a shift in computational neuroscience towards spatio-temporal predictive analyses. We introduce a novel open-source viewer, the EEG Prediction Visualizer (EPViz), to aid researchers in developing, validating, and reporting their predictive modeling outputs. EPViz is a lightweight and standalone software package developed in Python. Beyond viewing and manipulating the EEG data, EPViz allows researchers to load a PyTorch deep learning model, apply it to EEG features, and overlay the output channel-wise or subject-level temporal predictions on top of the original time series. These results can be saved as high-resolution images for use in manuscripts and presentations. EPViz also provides valuable tools for clinician-scientists, including spectrum visualization, computation of basic data statistics, and annotation editing. Finally, we have included a built-in EDF anonymization module to facilitate sharing of clinical data. Taken together, EPViz fills a much needed gap in EEG visualization. Our user-friendly interface and rich collection of features may also help to promote collaboration between engineers and clinicians.

 

We propose a novel neural network architecture, SZTrack, to detect and track the spatio-temporal propagation of seizure activity in multichannel EEG. SZTrack combines a convolutional neural network encoder operating on individual EEG channels with recurrent neural networks to capture the evolution of seizure activity. Our unique training strategy aggregates individual electrode level predictions for patient-level seizure detection and localization. We evaluate SZTrack on a clinical EEG dataset of 201 seizure recordings from 34 epilepsy patients acquired at the Johns Hopkins Hospital. Our network achieves similar seizure detection performance to state-of-the-art methods and provides valuable localization information that has not previously been demonstrated in the literature. We also show the cross-site generalization capabilities of SZTrack on a dataset of 53 seizure recordings from 14 epilepsy patients acquired at the University of Wisconsin Madison. SZTrack is able to determine the lobe and hemisphere of origin in nearly all of these new patients without retraining the network . To our knowledge, SZTrack is the first end-to-end seizure tracking network using scalp EEG. 

Deep subsurface environments are decoupled from Earth’s surface processes yet diverse, active, and abundant microbial communities thrive in these isolated environments. Microbes inhabiting the deep biosphere face unique challenges such as electron donor/acceptor limitations, pore space/fracture network limitations, and isolation from other microbes within the formation. Of the few systems that have been characterized, it is apparent that nutrient limitations likely facilitate diverse microbe-microbe interactions (i.e., syntrophic, symbiotic, or parasitic) and that these interactions drive biogeochemical cycling of major elements. Here we describe microbial communities living in low temperature, chemically reduced brines at the Soudan Underground Mine State Park, United States. The Soudan Iron mine intersects a massive hematite formation at the southern extent of the Canadian Shield. Fractured rock aquifer brines continuously flow from exploratory boreholes drilled circa 1960 and are enriched in deuterium compared to the global meteoric values, indicating brines have had little contact with surface derived waters, and continually degas low molecular weight hydrocarbons C 1 -C 4 . Microbial enrichments suggest that once brines exit the boreholes, oxidation of the hydrocarbons occur. Amplicon sequencing show these borehole communities are low in diversity and dominated by Firmicute and Proteobacteria phyla. From the metagenome assemblies, we recovered approximately thirty genomes with estimated completion over 50%. Analysis of genome taxonomy generally followed the amplicon data, and highlights that several of the genomes represent novel families and genera. Metabolic reconstruction shows two carbon-fixation pathways were dominant, the Wood-Ljungdahl (acetogenesis) and Calvin-Benson-Bassham (via RuBisCo), indicating that inorganic carbon likely enters into the microbial foodweb with differing carbon fractionation potentials. Interestingly, methanogenesis is likely driven by Methanolobus and suggests cycling of methylated compounds and not H 2 /CO 2 or acetate. Furthermore, the abundance of sulfate in brines suggests cryptic sulfur cycling may occur, as we detect possible sulfate reducing and thiosulfate oxidizing microorganisms. Finally, a majority of the microorganisms identified contain genes that would allow them to participate in several element cycles, highlighting that in these deep isolated systems metabolic flexibility may be an important life history trait.