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Institution

Ohio State University

EducationColumbus, Ohio, United States
About: Ohio State University is a education organization based out in Columbus, Ohio, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 102421 authors who have published 222715 publications receiving 8373403 citations. The organization is also known as: Ohio State & The Ohio State University.


Papers
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Journal ArticleDOI
TL;DR: Various network topologies and switching strategies are covered here, including interconnection networks for communication among processors and memory modules.
Abstract: Concurrent processing depends on interconnection networks for communication among processors and memory modules. Various network topologies and switching strategies are covered here.

859 citations

Journal ArticleDOI
TL;DR: The authors explore the potential of the 16S gene for discriminating bacterial taxa and show that full-length sequencing combined with appropriate clustering of intragenomic sequence variation can provide accurate representation of bacterial species in microbiome datasets.
Abstract: The 16S rRNA gene has been a mainstay of sequence-based bacterial analysis for decades. However, high-throughput sequencing of the full gene has only recently become a realistic prospect. Here, we use in silico and sequence-based experiments to critically re-evaluate the potential of the 16S gene to provide taxonomic resolution at species and strain level. We demonstrate that targeting of 16S variable regions with short-read sequencing platforms cannot achieve the taxonomic resolution afforded by sequencing the entire (~1500 bp) gene. We further demonstrate that full-length sequencing platforms are sufficiently accurate to resolve subtle nucleotide substitutions (but not insertions/deletions) that exist between intragenomic copies of the 16S gene. In consequence, we argue that modern analysis approaches must necessarily account for intragenomic variation between 16S gene copies. In particular, we demonstrate that appropriate treatment of full-length 16S intragenomic copy variants has the potential to provide taxonomic resolution of bacterial communities at species and strain level.

859 citations

Journal ArticleDOI
TL;DR: In this article, the miR-106b-25 cluster, upregulated in a subset of human gastric tumors, is activated by E2F1 in parallel with its host gene, Mcm7.

858 citations

Journal ArticleDOI
TL;DR: This exploratory, extended-duration treatment protocol appears to be a promising approach to alter the gut microbiome and virome and improve GI and behavioral symptoms of ASD.
Abstract: Autism spectrum disorders (ASD) are complex neurobiological disorders that impair social interactions and communication and lead to restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. The causes of these disorders remain poorly understood, but gut microbiota, the 1013 bacteria in the human intestines, have been implicated because children with ASD often suffer gastrointestinal (GI) problems that correlate with ASD severity. Several previous studies have reported abnormal gut bacteria in children with ASD. The gut microbiome-ASD connection has been tested in a mouse model of ASD, where the microbiome was mechanistically linked to abnormal metabolites and behavior. Similarly, a study of children with ASD found that oral non-absorbable antibiotic treatment improved GI and ASD symptoms, albeit temporarily. Here, a small open-label clinical trial evaluated the impact of Microbiota Transfer Therapy (MTT) on gut microbiota composition and GI and ASD symptoms of 18 ASD-diagnosed children. MTT involved a 2-week antibiotic treatment, a bowel cleanse, and then an extended fecal microbiota transplant (FMT) using a high initial dose followed by daily and lower maintenance doses for 7–8 weeks. The Gastrointestinal Symptom Rating Scale revealed an approximately 80% reduction of GI symptoms at the end of treatment, including significant improvements in symptoms of constipation, diarrhea, indigestion, and abdominal pain. Improvements persisted 8 weeks after treatment. Similarly, clinical assessments showed that behavioral ASD symptoms improved significantly and remained improved 8 weeks after treatment ended. Bacterial and phagedeep sequencing analyses revealed successful partial engraftment of donor microbiota and beneficial changes in the gut environment. Specifically, overall bacterial diversity and the abundance of Bifidobacterium, Prevotella, and Desulfovibrio among other taxa increased following MTT, and these changes persisted after treatment stopped (followed for 8 weeks). This exploratory, extended-duration treatment protocol thus appears to be a promising approach to alter the gut microbiome and virome and improve GI and behavioral symptoms of ASD. Improvements in GI symptoms, ASD symptoms, and the microbiome all persisted for at least 8 weeks after treatment ended, suggesting a long-term impact. This trial was registered on the ClinicalTrials.gov, with the registration number NCT02504554

858 citations

Journal ArticleDOI
TL;DR: In this paper, the authors study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel and develop efficient algorithms to find the optimal update policy among all causal policies and establish sufficient and necessary conditions for the optimality of the zero-wait policy.
Abstract: In this paper, we study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel. A proper metric for data freshness at the destination is the age-of-information , or simply age , which is defined as how old the freshest received update is, since the moment that this update was generated at the source node (e.g., a sensor). A reasonable update policy is the zero-wait policy, i.e., the source node submits a fresh update once the previous update is delivered, which achieves the maximum throughput and the minimum delay. Surprisingly, this zero-wait policy does not always minimize the age. This counter-intuitive phenomenon motivates us to study how to optimally control information updates to keep the data fresh and to understand when the zero-wait policy is optimal. We introduce a general age penalty function to characterize the level of dissatisfaction on data staleness and formulate the average age penalty minimization problem as a constrained semi-Markov decision problem with an uncountable state space. We develop efficient algorithms to find the optimal update policy among all causal policies and establish sufficient and necessary conditions for the optimality of the zero-wait policy. Our investigation shows that the zero-wait policy is far from the optimum if: 1) the age penalty function grows quickly with respect to the age; 2) the packet transmission times over the channel are positively correlated over time; or 3) the packet transmission times are highly random (e.g., following a heavy-tail distribution).

857 citations


Authors

Showing all 103197 results

NameH-indexPapersCitations
Paul M. Ridker2331242245097
George Davey Smith2242540248373
Carlo M. Croce1981135189007
Eric J. Topol1931373151025
Bernard Rosner1901162147661
David H. Weinberg183700171424
Anil K. Jain1831016192151
Michael I. Jordan1761016216204
Kay-Tee Khaw1741389138782
Richard K. Wilson173463260000
Yang Yang1642704144071
Brian L Winer1621832128850
Jian-Kang Zhu161550105551
Elaine R. Mardis156485226700
R. E. Hughes1541312110970
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023261
20221,234
20219,945
20209,944
20199,052
20188,656