Fresh Mudd: Transforming a Subject Branch

Re-think it: Libraries for a New Age is a national conference that brings together academic, public and K-12 librarians, administrators, technologists, architects, designers, furniture manufacturers, and educators. Participants gathered to collectively re-think the increasingly important role libraries play in the communities they serve. The conference was held January 8-10, 2018 at the University of Texas and other locations in Austin. In its second edition, Re-think it 2018 is co-hosted by The UT Libraries, the Austin Public Library, the Austin Community College Library Services, and seven additional local library partners.UT Librarie

Diversity of woody-host infecting Phytophthora species in public parks and botanic gardens as revealed by metabarcoding, and opportunities for mitigation through best practice

The diversity of Phytophthora species in soils collected from 14 highly disturbed sites in northern Britain, including botanic gardens, arboreta, public parks and other amenity woodland sites, was analysed using a molecular technique known as DNA metabarcoding. This technique enables the identification of multiple species present in a single environmental sample based on a DNA ‘barcode’ unique to each species. The genus Phytophthora was targeted in this study due to its increasing impact on Britain’s forests and woodlands over thelast 20 years. The introduction and spread of new Phytophthora species into Britain has been strongly associated with the movement of traded containerised plants, with a number of Phytophthora outbreaks reported on host trees located in public gardens and parks that had recently undergone planting or landscape regeneration schemes. This study was undertaken to assess the extent to which these highly disturbed sites with extensive planting regimes act as harbours for woody-host infecting Phytophthora species. A total of 23 Phytophthora species, the majority of which are known to be pathogens of woody hosts, were detected across the 14 sites sampled. These included four quarantine-regulated pathogens and four species notpreviously recorded in Britain. Also detected were three as-yet undescribed Phytophthora species and nine oomycete sequences with no clear match to any known genus. There was no effect of geographical location, elevation, underlying soil type, host family or host health status on the Phytophthora assemblages at each site, suggesting that the Phytophthora communities detected are likely to comprise introduced species associated with planting programmes. P. austrocedri and P. pseudosyringae were two of the most abundant Phytophthoraspecies detected, both of which cause serious damage to trees and are regarded as fairly recent introductions to Britain. The practical implications of the findings in terms of mitigating Phytophthora introduction, spread and impact at botanic gardens, arboreta and urban parks are discussed

Population genomics of domestic and wild yeasts

The natural genetics of an organism is determined by the distribution of sequences of its genome. Here we present one- to four-fold, with some deeper, coverage of the genome sequences of over seventy isolates of the domesticated baker's yeast, _Saccharomyces cerevisiae_, and its closest relative, the wild _S. paradoxus_, which has never been associated with human activity. These were collected from numerous geographic locations and sources (including wild, clinical, baking, wine, laboratory and food spoilage). These sequences provide an unprecedented view of the population structure, natural (and artificial) selection and genome evolution in these species. Variation in gene content, SNPs, indels, copy numbers and transposable elements provide insights into the evolution of different lineages. Phenotypic variation broadly correlates with global genome-wide phylogenetic relationships however there is no correlation with source. _S. paradoxus_ populations are well delineated along geographic boundaries while the variation among worldwide _S. cerevisiae_ isolates show less differentiation and is comparable to a single _S. paradoxus_ population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of _S. cerevisiae_ shows a few well defined geographically isolated lineages and many different mosaics of these lineages, supporting the notion that human influence provided the opportunity for outbreeding and production of new combinations of pre-existing variation

ObStruct: A method to objectively analyse factors driving population structure using Bayesian ancestry profiles

Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin) correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present ObStruct, a novel tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods. ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct's ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses. © 2014 Gayevskiy et al

Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

Metabarcoding reveals a high diversity of woody host-associated Phytophthora spp. in soils at public gardens and amenity woodlands in Britain

This work was supported by Forestry Commission Scotland (grant number SLA-14/15-034), the Living With Environmental Change Phase 3 project ‘Phyto-Threats’ as part of the Tree Health and Plant Biosecurity Initiative (grant number BB/N023463/1) and the European Union’s Horizon 2020 research and innovation programme POnTE (Pest Organisms Threatening Europe) (grant number 635646). David E.L. Cooke, Pete E. Hedley, Leighton Pritchard, Peter Thorpe also received funding from the Scottish GovernmentForests and woodlands worldwide are being severely impacted by invasive Phytophthora species, with initial outbreaks in some cases occurring on host trees located in public parks and gardens. These highly disturbed sites with diverse planting practices may indeed act as harbours for invasive Phytophthora pathogens which are particularly well adapted to surviving in soil. High throughput Illumina sequencing was used to analyse Phytophthora species diversity in soil samples collected from 14 public garden/amenity woodland sites in northern Britain. Bioinformatic analyses revealed some limitations to using internal transcribed spacer as the barcode region; namely reporting of false positives and ambiguous species matches. Taking this into account, 35 distinct sequences were amplified across the sites, corresponding to 23 known Phytophthora species as well as twelve oomycete sequences with no match to any known Phytophthora species. Phytophthora pseudosyringae and P. austrocedri, both of which cause serious damage to trees and are regarded as fairly recent introductions to Britain, were the two most abundant Phytophthora species detected. There was no evidence that any of the detected Phytophthora species were more associated with any one type of host, healthy or otherwise. This study has demonstrated the ubiquity and diversity of Phytophthora species endemic in highly managed, extensively planted soil environments in Britain. Suggested improvements to the methodology and the practical implications of the findings in terms of mitigating Phytophthora spread and impact are discussed.Publisher PDFPeer reviewe

Different applications of concept maps in Higher Education

Purpose: The aim of this work is to show different applications of concept maps in higher education, concretely in qualifications of the Polytechnic University of Valencia. Design/methodology/approach: Different methodologies have been used depending on the application of concept maps: as evaluation tool, as knowledge organizing tool, and as meaningful learning tool. Findings: Students consider the concept maps useful principally to select key ideas, to achieve a comprehensive view of the lesson, and to bring up the subject. Moreover, concept maps promote the meaningful and active learning, help students to understand, follow-up, and learn subjects with a high load of contents. Research limitations/implications: The most important limitation is the use of the concept maps in subjects with a high number of students. Practical implications: The realization of concept maps allows the student to develop generic competences. Originality/value: The originality of this work is to show how a same tool can be used in different subjects of different qualifications. © Journal of Industrial Engineering and Management, 2011.Bes Piá, A.; Blasco-Tamarit, E.; Muñoz Portero, MJ. (2011). Different applications of concept maps in Higher Education. Journal of Industrial Engineering and Management. 4(1):81-102. doi:10.3926/jiem.2011.v4n1.p81-102Senia811024

Implementing major system change in specialist cancer surgery: The role of provider networks

Objective: Major system change (MSC) has multiple, sometimes conflicting, goals and involves implementing change across a number of organizations. This study sought to develop new understanding of how the role that networks can play in implementing MSC, using the case of centralization of specialist cancer surgery in London, UK. Methods: The study was based on a framework drawn from literature on networks and MSC. We analysed 100 documents, conducted 134 h of observations during relevant meetings and 81 interviews with stakeholders involved in the centralization. We analysed the data using thematic analysis. Results: MSC in specialist cancer services was a contested process, which required constancy in network leadership over several years, and its horizontal and vertical distribution across the network. A core central team composed of network leaders, managers and clinical/manager hybrid roles was tasked with implementing the changes. This team developed different forms of engagement with provider organizations and other stakeholders. Some actors across the network, including clinicians and patients, questioned the rationale for the changes, the clinical evidence used to support the case for change, and the ways in which the changes were implemented. Conclusions: Our study provides new understanding of MSC by discussing the strategies used by a provider network to facilitate complex changes in a health care context in the absence of a system-wide authority

A framework for parameter estimation and model selection from experimental data in systems biology using approximate Bayesian computation.

As modeling becomes a more widespread practice in the life sciences and biomedical sciences, researchers need reliable tools to calibrate models against ever more complex and detailed data. Here we present an approximate Bayesian computation (ABC) framework and software environment, ABC-SysBio, which is a Python package that runs on Linux and Mac OS X systems and that enables parameter estimation and model selection in the Bayesian formalism by using sequential Monte Carlo (SMC) approaches. We outline the underlying rationale, discuss the computational and practical issues and provide detailed guidance as to how the important tasks of parameter inference and model selection can be performed in practice. Unlike other available packages, ABC-SysBio is highly suited for investigating, in particular, the challenging problem of fitting stochastic models to data. In order to demonstrate the use of ABC-SysBio, in this protocol we postulate the existence of an imaginary reaction network composed of seven interrelated biological reactions (involving a specific mRNA, the protein it encodes and a post-translationally modified version of the protein), a network that is defined by two files containing 'observed' data that we provide as supplementary information. In the first part of the PROCEDURE, ABC-SysBio is used to infer the parameters of this system, whereas in the second part we use ABC-SysBio's relevant functionality to discriminate between two different reaction network models, one of them being the 'true' one. Although computationally expensive, the additional insights gained in the Bayesian formalism more than make up for this cost, especially in complex problems