Estimating species trees using multiple-allele DNA sequence data

Several techniques, such as concatenation and consensus methods, are available for combining data from multiple loci to produce a single statement of phylogenetic relationships. However, when multiple alleles are sampled from individual species, it becomes more challenging to estimate relationships at the level of species, either because concatenation becomes inappropriate due to conflicts among individual gene trees, or because the species from which multiple alleles have been sampled may not form monophyletic groups in the estimated tree. We propose a Bayesian hierarchical model to reconstruct species trees from multiple-allele, multilocus sequence data, building on a recently proposed method for estimating species trees from single allele multilocus data. A two-step Markov Chain Monte Carlo (MCMC) algorithm is adopted to estimate the posterior distribution of the species tree. The model is applied to estimate the posterior distribution of species trees for two multiple-allele datasets - yeast (Saccharomyces) and birds (Manacus - manakins). The estimates of the species trees using our method are consistent with those inferred from other methods and genetic markers, but in contrast to other species tree methods, it provides credible regions for the species tree. The Bayesian approach described here provides a powerful framework for statistical testing and integration of population genetics and phylogenetics. © 2008 The Author(s)

Mentoring Undergraduate Research in Statistics: Reaping the Benefits and Overcoming the Barriers

Undergraduate research experiences (UREs), whether within the context of a mentor-mentee experience or a classroom framework, represent an excellent opportunity to expose students to the independent scholarship model. The high impact of undergraduate research has received recent attention in the context of STEM disciplines. Reflecting a 2017 survey of statistics faculty, this article examines the perceived benefits of UREs, as well as barriers to the incorporation of UREs, specifically within the field of statistics. Viewpoints of students, faculty mentors, and institutions are investigated. Further, the article offers several strategies for leveraging characteristics unique to the field of statistics to overcome barriers and thereby provide greater opportunity for undergraduate statistics students to gain research experience

The Major Histocompatibility Complex–related Fc Receptor for IgG (FcRn) Binds Albumin and Prolongs Its Lifespan

The inverse relationship between serum albumin concentration and its half-life suggested to early workers that albumin would be protected from a catabolic fate by a receptor-mediated mechanism much like that proposed for IgG. We show here that albumin binds FcRn in a pH dependent fashion, that the lifespan of albumin is shortened in FcRn-deficient mice, and that the plasma albumin concentration of FcRn-deficient mice is less than half that of wild-type mice. These results affirm the hypothesis that the major histocompatibility complex–related Fc receptor protects albumin from degradation just as it does IgG, prolonging the half-lives of both

Isolation of lactic acid bacteria from kantong, a condiment produced from the fermentation of kapok (Ceiba pentandra) seeds and cassava (Manihot esculentum) flour

Abstract: Kantong, a traditional food condiment of the people of Northern Ghana, is produced by fermentation of Ceiba pentandra seeds and cassava flour. Knowledge of the microbiology of the fermentation process will be useful in its technological improvement and starter culture development. There was a drop in the initial pH from 6.9 before fermentation to 4.9 after fermentation with change in color of the product from grayish to dark brown as well as the development of a more desirable flavor. Lactic acid bacteria (LAB) with counts between 10 6 and 10 9 cfu/g were isolated on MRS agar and subjected to Gram, catalase and oxidase tests. The LAB were further identified by biochemical and genotypic methods using rep-PCR, (GTG) 5 primer, 16S rRNA gene sequencing and carbohydrate assimilation profiling. A total of 331 Lactic acid bacteria were isolated of which 47% were Lactobacillus plantarum , 18% Lactobacillus fermentum, 8% Leuconostoc mesenteroides, 12% Pediococcus acidilactici and 15% a

Crisis Standard of Care: Management of Infantile Spasms during COVID‐19

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156180/2/ana25792_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156180/1/ana25792.pd

Corresponding Functional Dynamics across the Hsp90 Chaperone Family: Insights from a Multiscale Analysis of MD Simulations

Understanding how local protein modifications, such as binding small-molecule ligands, can trigger and regulate large-scale motions of large protein domains is a major open issue in molecular biology. We address various aspects of this problem by analyzing and comparing atomistic simulations of Hsp90 family representatives for which crystal structures of the full length protein are available: mammalian Grp94, yeast Hsp90 and E.coli HtpG. These chaperones are studied in complex with the natural ligands ATP, ADP and in the Apo state. Common key aspects of their functional dynamics are elucidated with a novel multi-scale comparison of their internal dynamics. Starting from the atomic resolution investigation of internal fluctuations and geometric strain patterns, a novel analysis of domain dynamics is developed. The results reveal that the ligand-dependent structural modulations mostly consist of relative rigid-like movements of a limited number of quasi-rigid domains, shared by the three proteins. Two common primary hinges for such movements are identified. The first hinge, whose functional role has been demonstrated by several experimental approaches, is located at the boundary between the N-terminal and Middle-domains. The second hinge is located at the end of a three-helix bundle in the Middle-domain and unfolds/unpacks going from the ATP- to the ADP-state. This latter site could represent a promising novel druggable allosteric site common to all chaperones

Development and implementation of clinical guidelines : an artificial intelligence perspective

Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.This work is funded by national funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project PEst-OE/EEI/UI0752/2011"