scispace - formally typeset
Search or ask a question
Institution

Michigan State University

EducationEast Lansing, Michigan, United States
About: Michigan State University is a education organization based out in East Lansing, Michigan, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 60109 authors who have published 137074 publications receiving 5633022 citations. The organization is also known as: MSU & Michigan State.


Papers
More filters
Journal ArticleDOI
TL;DR: The genomic structure of NIPBL is characterized and it is found that it is widely expressed in fetal and adult tissues and facilitates enhancer-promoter communication and regulates Notch signaling and other developmental pathways in Drosophila melanogaster.
Abstract: Cornelia de Lange syndrome (CdLS; OMIM 122470) is a dominantly inherited multisystem developmental disorder characterized by growth and cognitive retardation; abnormalities of the upper limbs; gastroesophageal dysfunction; cardiac, ophthalmologic and genitourinary anomalies; hirsutism; and characteristic facial features. Genital anomalies, pyloric stenosis, congenital diaphragmatic hernias, cardiac septal defects, hearing loss and autistic and self-injurious tendencies also frequently occur. Prevalence is estimated to be as high as 1 in 10,000 (ref. 4). We carried out genome-wide linkage exclusion analysis in 12 families with CdLS and identified four candidate regions, of which chromosome 5p13.1 gave the highest multipoint lod score of 2.7. This information, together with the previous identification of a child with CdLS with a de novo t(5;13)(p13.1;q12.1) translocation, allowed delineation of a 1.1-Mb critical region on chromosome 5 for the gene mutated in CdLS. We identified mutations in one gene in this region, which we named NIPBL, in four sporadic and two familial cases of CdLS. We characterized the genomic structure of NIPBL and found that it is widely expressed in fetal and adult tissues. The fly homolog of NIPBL, Nipped-B, facilitates enhancer-promoter communication and regulates Notch signaling and other developmental pathways in Drosophila melanogaster.

658 citations

Journal ArticleDOI
TL;DR: Differences in the composition and stability of the microbial community between pregnant and non-pregnant women were observed and can serve as the basis to study the relationship between the vaginal microbiome and adverse pregnancy outcomes.
Abstract: Background: This study was undertaken to characterize the vaginal microbiota throughout normal human pregnancy using sequence-based techniques. We compared the vaginal microbial composition of non-pregnant patients with a group of pregnant women who delivered at term. Results: A retrospective case–control longitudinal study was designed and included non-pregnant women (n = 32) and pregnant women who delivered at term (38 to 42 weeks) without complications (n = 22). Serial samples of vaginal fluid were collected from both non-pregnant and pregnant patients. A 16S rRNA gene sequence-based survey was conducted using pyrosequencing to characterize the structure and stability of the vaginal microbiota. Linear mixed effects models and generalized estimating equations were used to identify the phylotypes whose relative abundance was different between the two study groups. The vaginal microbiota of normal pregnant women was different from that of non-pregnant women (higher abundance of Lactobacillus vaginalis, L. crispatus, L. gasseri and L. jensenii and lower abundance of 22 other phylotypes in pregnant women). Bacterial community state type (CST) IV-B or CST IV-A characterized by high relative abundance of species of genus Atopobium as well as the presence of Prevotella, Sneathia, Gardnerella, Ruminococcaceae, Parvimonas, Mobiluncus and other taxa previously shown to be associated with bacterial vaginosis were less frequent in normal pregnancy. The stability of the vaginal microbiota of pregnant women was higher than that of non-pregnant women; however, during normal pregnancy, bacterial communities shift almost exclusively from one CST dominated by Lactobacillus spp. to another CST dominated by Lactobacillus spp. Conclusion: We report the first longitudinal study of the vaginal microbiota in normal pregnancy. Differences in the composition and stability of the microbial community between pregnant and non-pregnant women were observed. Lactobacillus spp. were the predominant members of the microbial community in normal pregnancy. These results can serve as the basis to study the relationship between the vaginal microbiome and adverse pregnancy outcomes.

657 citations

Journal ArticleDOI
TL;DR: The authors give an overview of available techniques for PS estimation and PS application and provide a way to help compare PS techniques, using the resulting measured covariate balance as the criterion for selecting between techniques.
Abstract: There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available techniques for PS estimation and PS application. They also provide a way to help compare PS techniques, using the resulting measured covariate balance as the criterion for selecting between techniques. The empirical example for this study involves the potential causal relationship linking early-onset cannabis problems and subsequent negative mental health outcomes and uses data from a prospective cohort study. PS techniques are described and evaluated on the basis of their ability to balance the distributions of measured potentially confounding covariates for individuals with and without early-onset cannabis problems. This article identifies the PS techniques that yield good statistical balance of the chosen measured covariates within the context of this particular research question and cohort.

655 citations

Journal ArticleDOI
TL;DR: This paper proposes the concept of feature saliency and introduces an expectation-maximization algorithm to estimate it, in the context of mixture-based clustering, and extends the criterion and algorithm to simultaneously estimate the feature saliencies and the number of clusters.
Abstract: Clustering is a common unsupervised learning technique used to discover group structure in a set of data. While there exist many algorithms for clustering, the important issue of feature selection, that is, what attributes of the data should be used by the clustering algorithms, is rarely touched upon. Feature selection for clustering is difficult because, unlike in supervised learning, there are no class labels for the data and, thus, no obvious criteria to guide the search. Another important problem in clustering is the determination of the number of clusters, which clearly impacts and is influenced by the feature selection issue. In this paper, we propose the concept of feature saliency and introduce an expectation-maximization (EM) algorithm to estimate it, in the context of mixture-based clustering. Due to the introduction of a minimum message length model selection criterion, the saliency of irrelevant features is driven toward zero, which corresponds to performing feature selection. The criterion and algorithm are then extended to simultaneously estimate the feature saliencies and the number of clusters.

655 citations

Journal ArticleDOI
TL;DR: It is shown that the performance of a globally bounded partial state feedback control of an input-output linearizable system can be recovered by a sufficiently fast high-gain observer.
Abstract: It is shown that the performance of a globally bounded partial state feedback control of a certain class of nonlinear systems can be recovered by a sufficiently fast high-gain observer. The performance recovery includes recovery of asymptotic stability of the origin, the region of attraction, and trajectories.

655 citations


Authors

Showing all 60636 results

NameH-indexPapersCitations
David Miller2032573204840
Anil K. Jain1831016192151
D. M. Strom1763167194314
Feng Zhang1721278181865
Derek R. Lovley16858295315
Donald G. Truhlar1651518157965
Donald E. Ingber164610100682
J. E. Brau1621949157675
Murray F. Brennan16192597087
Peter B. Reich159790110377
Wei Li1581855124748
Timothy C. Beers156934102581
Claude Bouchard1531076115307
Mercouri G. Kanatzidis1521854113022
James J. Collins15166989476
Network Information
Related Institutions (5)
University of California, Davis
180K papers, 8M citations

97% related

University of Illinois at Urbana–Champaign
225.1K papers, 10.1M citations

97% related

University of Minnesota
257.9K papers, 11.9M citations

97% related

University of Wisconsin-Madison
237.5K papers, 11.8M citations

97% related

Cornell University
235.5K papers, 12.2M citations

97% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023250
2022752
20217,041
20206,870
20196,548
20185,779