Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical dataset.

Use of machine learning (ML) for automated annotation of heart structures from echocardiographic videos is an active research area, but understanding of comparative, generalizable performance among models is lacking. This study aimed to (1) assess the generalizability of five state-of-the-art ML-based echocardiography segmentation models within a large Geisinger clinical dataset, and (2) test the hypothesis that a quality control (QC) method based on segmentation uncertainty can further improve segmentation results. Five models were applied to 47,431 echocardiography studies that were independent from any training samples.

The Initial Gut Microbiota and Response to Antibiotic Perturbation Influence Clostridioides difficile Clearance in Mice.

The gut microbiota has a key role in determining susceptibility to infections (CDIs). However, much of the mechanistic work examining CDIs in mouse models uses animals obtained from a single source. We treated mice from 6 sources (2 University of Michigan colonies and 4 commercial vendors) with clindamycin, followed by a challenge, and then measured colonization levels throughout the infection.

Coding-Complete RNA Virus Genomes Assembled from Murine Cecal Metatranscriptomes.

Efforts to catalog viral diversity in the gut microbiome have largely focused on DNA viruses, while RNA viruses remain understudied. To address this, we screened assemblies of previously published mouse gut metatranscriptomes for the presence of RNA viruses. We identified the coding-complete genomes of an astrovirus and five mitovirus-like viruses.

Metatranscriptomic Analyses of Diel Metabolic Functions During a Bloom in Western Lake Erie (United States).

This study examined diel shifts in metabolic functions of spp. during a 48-h Lagrangian survey of a toxin-producing cyanobacterial bloom in western Lake Erie in the aftermath of the 2014 Toledo Water Crisis. Transcripts mapped to the genomes of recently sequenced lower Great Lakes isolates showed distinct patterns of gene expression between samples collected across day (10:00 h, 16:00 h) and night (22:00 h, 04:00 h).

Corrigendum: Genome and Environmental Activity of a Virus and Its Virophages.

[This corrects the article DOI: 10.3389/fmicb.2019.

Genome and Environmental Activity of a Virus and Its Virophages.

Some giant viruses are ecological agents that are predicted to be involved in the top-down control of single-celled eukaryotic algae populations in aquatic ecosystems. Despite an increased interest in giant viruses since the discovery and characterization of and other viral giants, little is known about their physiology and ecology. In this study, we characterized the genome and functional potential of a giant virus that infects the freshwater haptophyte , originally isolated from Lake Ontario.

Diversity of Active Viral Infections within the Sphagnum Microbiome.

-dominated peatlands play an important role in global carbon storage and represent significant sources of economic and ecological value. While recent efforts to describe microbial diversity and metabolic potential of the microbiome have demonstrated the importance of its microbial community, little is known about the viral constituents. We used metatranscriptomics to describe the diversity and activity of viruses infecting microbes within the peat bog.

Seasonal Gene Expression and the Ecophysiological Implications of Toxic Microcystis aeruginosa Blooms in Lake Taihu.

Harmful cyanobacterial blooms represent an increasing threat to freshwater resources globally. Despite increased research, the physiological basis of how the dominant bloom-forming cyanobacteria, Microcystis spp., proliferate and then maintain high population densities through changing environmental conditions is poorly understood.

Molecular prediction of lytic vs lysogenic states for Microcystis phage: Metatranscriptomic evidence of lysogeny during large bloom events.

Microcystis aeruginosa is a freshwater bloom-forming cyanobacterium capable of producing the potent hepatotoxin, microcystin. Despite increased interest in this organism, little is known about the viruses that infect it and drive nutrient mobilization and transfer of genetic material between organisms. The genomic complement of sequenced phage suggests these viruses are capable of integrating into the host genome, though this activity has not been observed in the laboratory.

Thalamus segmentation using multi-modal feature classification: Validation and pilot study of an age-matched cohort.

Automatic segmentation of the thalamus can be used to measure differences and track changes in thalamic volume that may occur due to disease, injury or normal aging. An automatic thalamus segmentation algorithm incorporating features from diffusion tensor imaging (DTI) and thalamus priors constructed from multiple atlases is proposed. Multiple atlases with corresponding manual thalamus segmentations are registered to the target image and averaged to generate the thalamus prior.

Ecophysiological Examination of the Lake Erie Microcystis Bloom in 2014: Linkages between Biology and the Water Supply Shutdown of Toledo, OH.

Annual cyanobacterial blooms dominated by Microcystis have occurred in western Lake Erie (U.S./Canada) during summer months since 1995.

A Student's Guide to Giant Viruses Infecting Small Eukaryotes: From Acanthamoeba to Zooxanthellae.

The discovery of infectious particles that challenge conventional thoughts concerning "what is a virus" has led to the evolution a new field of study in the past decade. Here, we review knowledge and information concerning "giant viruses", with a focus not only on some of the best studied systems, but also provide an effort to illuminate systems yet to be better resolved. We conclude by demonstrating that there is an abundance of new host-virus systems that fall into this "giant" category, demonstrating that this field of inquiry presents great opportunities for future research.

Functional Characteristics of the Gut Microbiome in C57BL/6 Mice Differentially Susceptible to .

C57BL/6 mice are widely used for studies of immune function and metabolism in mammals. In a previous study, it was observed that when C57BL/6 mice purchased from different vendors were infected with , a causative agent of murine malaria, they exhibited both differential immune responses and significantly different parasite burdens: these patterns were reproducible when gut contents were transplanted into gnotobiotic mice. To gain insight into the mechanism of resistance, we removed whole ceca from mice purchased from two vendors, Taconic Biosciences (low parasitemia) and Charles River Laboratories (high parasitemia), to determine the combined host and microflora metabolome and metatranscriptome.

Thalamus parcellation using multi-modal feature classification and thalamic nuclei priors.

Segmentation of the thalamus and thalamic nuclei is useful to quantify volumetric changes from neurodegenerative diseases. Most thalamus segmentation algorithms only use T1-weighted magnetic resonance images and current thalamic parcellation methods require manual interaction. Smaller nuclei, such as the lateral and medial geniculates, are challenging to locate due to their small size.

Effect of Clostridium perfringens infection and antibiotic administration on microbiota in the small intestine of broiler chickens.

The etiological agent of necrotic enteritis (NE) is Clostridium perfringens (CP), which is an economically significant problem for broiler chicken producers worldwide. Traditional use of in-feed antibiotic growth promoters to control NE disease have resulted in the emergence of antibiotic resistance in CP strains. Identification of probiotic bacteria strains as an alternative to antibiotics for the control of intestinal CP colonization is crucial.

Automatic method for thalamus parcellation using multi-modal feature classification.

Segmentation and parcellation of the thalamus is an important step in providing volumetric assessment of the impact of disease n brain structures. Conventionally, segmentation is carried out on T1-weighted magnetic resonance (MR) images and nuclear parcellation using diffusion weighted MR images. We present the first fully automatic method that incorporates both tissue contrasts and several derived fea-fractional anisotrophy, fiber orientation from the 5D Knutsson representation of the principal eigenvectors, and connectivity between the thalamus and the cortical lobes, as features.

THALAMIC PARCELLATION FROM MULTI-MODAL DATA USING RANDOM FOREST LEARNING.

The thalamus sub-cortical gray matter structure consists of contiguous nuclei, each individually responsible for communication between various cerebral cortex and midbrain regions. These nuclei are differentially affected in neurodegenerative diseases such as multiple sclerosis and Alzheimer's. However thalamic parcellation of the nuclei, manual or automatic, is difficult given the limited contrast in any particular magnetic resonance (MR) modality.

Regional appearance in deformable model segmentation.

Automated medical image segmentation is a challenging task that benefits from the use of effective image appearance models. In this paper, we compare appearance models at three regional scales for statistically characterizing image intensity near object boundaries in the context of segmentation via deformable models. The three models capture appearance in the form of regional intensity quantile functions.

A method and software for segmentation of anatomic object ensembles by deformable m-reps.

Deformable shape models (DSMs) comprise a general approach that shows great promise for automatic image segmentation. Published studies by others and our own research results strongly suggest that segmentation of a normal or near-normal object from 3D medical images will be most successful when the DSM approach uses (1) knowledge of the geometry of not only the target anatomic object but also the ensemble of objects providing context for the target object and (2) knowledge of the image intensities to be expected relative to the geometry of the target and contextual objects. The segmentation will be most efficient when the deformation operates at multiple object-related scales and uses deformations that include not just local translations but the biologically important transformations of bending and twisting, i.

Comparison of human and automatic segmentations of kidneys from CT images.

Purpose: A controlled observer study was conducted to compare a method for automatic image segmentation with conventional user-guided segmentation of right and left kidneys from planning computerized tomographic (CT) images.

Methods And Materials: Deformable shape models called m-reps were used to automatically segment right and left kidneys from 12 target CT images, and the results were compared with careful manual segmentations performed by two human experts. M-rep models were trained based on manual segmentations from a collection of images that did not include the targets.