This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/.

Metagenomic biomarker discovery and explanation

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An Introduction To The Event Related Potential Technique

EVOLUTION: Of Mice . . .

The importance of the gut-brain axis in maintaining homeostasis has long been appreciated. However, the past 15 yr have seen the emergence of the microbiota (the trillions of microorganisms within ...

The Microbiota-Gut-Brain Axis

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.

https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2017.0387

Opportunities and obstacles for deep learning in biology and medicine.

Effect of Road Transport on the Equine Cecal Microbiota

Objectives: Obesity is associated with poorer brain health and cognitive function. However, it is not clear whether specific dietary factors may provide neuroprotective effects among individuals wi...

Dietary choline is related to neural efficiency during a selective attention task among middle-aged adults with overweight and obesity.

Background: Physical inactivity and excess adiposity are thought to be detrimental to physical and cognitive health. However, implications of these interrelated health factors are rarely examined together; consequently, little is known regarding the concomitant contribution of physical activity and adiposity to cognition. Methods: Bivariate correlations and hierarchical linear regressions were conducted among a sample of adults between 25 and 45 years (N = 65). Attentional inhibition was assessed using an Eriksen Flanker task. Whole-body percent body fat (%Fat) was assessed using dual-energy X-ray absorptiometry. Daily percent time spent in moderate to vigorous physical activity (%MVPA) was monitored using an accelerometer (7 d). Results: After adjusting for significant covariates, %MVPA was a positive predictor of accuracy in the incongruent task (β = 0.31, P = .03). Individuals who engaged in greater %MVPA exhibited superior attentional inhibition. Additionally, there was an interaction effect of %Fat a...

Relationship Between Physical Activity, Adiposity, and Attentional Inhibition

Oral bacteria and fungi contribute to oral health and establishment of the distal gastrointestinal tract microbiota; however, the impact of diet on the oral microbiota of infants is under-investigated. We aimed to characterize the influence of feeding method (exclusive human milk [HM], formula [FF], HM + FF [mixed], and solid foods) on oral bacterial and fungal communities in vaginally delivered infants during the first 6 mo of life. Infant (N=12) feeding records and tongue and cheek swabs were collected within 24 hr of birth, and at 2, 4, and 6 mo of age. DNA was extracted, sequenced on an Illumina MiSeq, and analyzed with QIIME 1.8 and SAS. Bacterial diversity was lowest in HM and highest in FF and solid food fed infants (p<0.01). Principal coordinates analysis (PCoA) of UniFrac distances between samples based on their 97% OTU composition and abundances indicated that bacterial communities were impacted by feeding method (p<0.005). Infants fed HM or mixed diets had reduced relative abundances of Bactero...

Diet Influences the Oral Microbiota of Infants during the First Six Months of Life

Stress is defined as a state during which the organism reacts to endogenous and exogenous threats and focuses its energies on coping with the situation of danger [28]. Stress can cause a wide variety of physiological and psychological health issues in canines, including increased activity of the sympathetic nervous system, increased release of catecholamine, and increased blood pressure [28]. The physiological effects of stress on the dog are poorly understood and therefore most likely under-reported. It is important to understand the level of stress working dogs can handle before experiencing physiological consequences in order to prevent negative impacts on job performance.

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Hannah D. Holscher

Papers

Effect of Road Transport on the Equine Cecal Microbiota

Dietary choline is related to neural efficiency during a selective attention task among middle-aged adults with overweight and obesity.

Relationship Between Physical Activity, Adiposity, and Attentional Inhibition

Diet Influences the Oral Microbiota of Infants during the First Six Months of Life

Effects of Air Travel Stress on the Canine Microbiome: A Pilot Study