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Author

Hannah D. Holscher

Bio: Hannah D. Holscher is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Medicine & Overweight. The author has an hindex of 24, co-authored 79 publications receiving 2585 citations.
Topics: Medicine, Overweight, Gut flora, Microbiome, Obesity

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: This Consensus Statement outlines the definition and scope of the term ‘synbiotics’ as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in May 2019 and explores the levels of evidence, safety, effects upon targets and implications for stakeholders of the synbiotic concept.
Abstract: In May 2019, the International Scientific Association for Probiotics and Prebiotics (ISAPP) convened a panel of nutritionists, physiologists and microbiologists to review the definition and scope of synbiotics. The panel updated the definition of a synbiotic to “a mixture comprising live microorganisms and substrate(s) selectively utilized by host microorganisms that confers a health benefit on the host”. The panel concluded that defining synbiotics as simply a mixture of probiotics and prebiotics could suppress the innovation of synbiotics that are designed to function cooperatively. Requiring that each component must meet the evidence and dose requirements for probiotics and prebiotics individually could also present an obstacle. Rather, the panel clarified that a complementary synbiotic, which has not been designed so that its component parts function cooperatively, must be composed of a probiotic plus a prebiotic, whereas a synergistic synbiotic does not need to be so. A synergistic synbiotic is a synbiotic for which the substrate is designed to be selectively utilized by the co-administered microorganisms. This Consensus Statement further explores the levels of evidence (existing and required), safety, effects upon targets and implications for stakeholders of the synbiotic concept. Gut microbiota can be manipulated to benefit host health, including the use of probiotics, prebiotics and synbiotics. This Consensus Statement outlines the definition and scope of the term ‘synbiotics’ as determined by an expert panel convened by the International Scientific Association for Probiotics and Prebiotics in May 2019.

953 citations

Journal ArticleDOI
TL;DR: The current knowledge of the impact of fiber and prebiotic consumption on the composition and metabolic function of the human gastrointestinal microbiota is reviewed, including the effects of physiochemical properties of complex carbohydrates, adequate intake and treatment dosages, and the phenotypic responses related to the composition of thehuman microbiota.
Abstract: The gastrointestinal microbiota has an important role in human health, and there is increasing interest in utilizing dietary approaches to modulate the composition and metabolic function of the mic...

903 citations

Journal ArticleDOI
TL;DR: It is suggested that exercise training induces compositional and functional changes in the human gut microbiota that are dependent on obesity status, independent of diet and contingent on the sustainment of exercise.
Abstract: PurposeExercise is associated with altered gut microbial composition, but studies have not investigated whether the gut microbiota and associated metabolites are modulated by exercise training in humans. We explored the impact of 6 wk of endurance exercise on the composition, functional capa

430 citations

Journal ArticleDOI
TL;DR: A review of recent, emerging, and anticipated trends in probiotic and prebiotic science, and a vision for broad areas of developing influence in the field can be found in this article.

191 citations

Journal ArticleDOI
TL;DR: Novel information is conveys novel information about the impact of dietary fiber supplementation on the phylogenetic structure and functional capacity of the fecal microbiome of healthy adults.

125 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article, a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation is described and validated, which addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities.
Abstract: 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/.

3,060 citations

01 Jan 2016
TL;DR: This is an introduction to the event related potential technique, which can help people facing with some malicious bugs inside their laptop to read a good book with a cup of tea in the afternoon.
Abstract: Thank you for downloading an introduction to the event related potential technique. Maybe you have knowledge that, people have look hundreds times for their favorite readings like this an introduction to the event related potential technique, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious bugs inside their laptop.

2,445 citations

Journal ArticleDOI
24 Dec 2004-Science

1,949 citations

Journal ArticleDOI
TL;DR: Future studies will focus on understanding the mechanisms underlying the microbiota-gut-brain axis and attempt to elucidate microbial-based intervention and therapeutic strategies for neuropsychiatric disorders.
Abstract: 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 ...

1,775 citations

Journal ArticleDOI
TL;DR: It is found 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.
Abstract: 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.

1,491 citations