EnsCat: clustering of categorical data via ensembling

Background: Clustering is a widely used collection of unsupervised learning techniques for identifying natural classes within a data set. It is often used in bioinformatics to infer population substructure. Genomic data are often categorical and high dimensional, e.g., long sequences of nucleotides. This makes inference challenging: The distance metric is often not well-defined on categorical data; running time for computations using high dimensional data can be considerable; and the Curse of Dimensionality often impedes the interpretation of the results. Up to the present, however, the literature and software addressing clustering for categorical data has not yet led to a standard approach. Results: We present software for an ensemble method that performs well in comparison with other methods regardless of the dimensionality of the data. In an ensemble method a variety of instantiations of a statistical object are found and then combined into a consensus value. It has been known for decades that ensembling generally outperforms the components that comprise it in many settings. Here, we apply this ensembling principle to clustering. We begin by generating many hierarchical clusterings with different clustering sizes. When the dimension of the data is high, we also randomly select subspaces also of variable size, to generate clusterings. Then, we combine these clusterings into a single membership matrix and use this to obtain a new, ensembled dissimilarity matrix using Hamming distance. Conclusions: Ensemble clustering, as implemented in R and called EnsCat, gives more clearly separated clusters than other clustering techniques for categorical data. The latest version with manual and examples is available at https://github.com/jlp2duke/EnsCat

Modeling Association in Microbial Communities with Clique Loginear Models

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community composition. We propose a statistical technique based on clique loglinear models and Bayes model averaging to identify microbial components in a metagenomic sample at various taxonomic levels that have significant associations. We describe the model class, a stochastic search technique for model selection, and the calculation of estimates of posterior probabilities of interest. We demonstrate our approach using data from the Human Microbiome Project and from a study of the skin microbiome in chronic wound healing. Our technique also identifies significant dependencies among microbial components as evidence of possible microbial syntrophy

Modeling Association in Microbial Communities with Clique Loginear Models

There is a growing awareness of the important roles that microbial communities play in complex biological processes. Modern investigation of these often uses next generation sequencing of metagenomic samples to determine community composition. We propose a statistical technique based on clique loglinear models and Bayes model averaging to identify microbial components in a metagenomic sample at various taxonomic levels that have significant associations. We describe the model class, a stochastic search technique for model selection, and the calculation of estimates of posterior probabilities of interest. We demonstrate our approach using data from the Human Microbiome Project and from a study of the skin microbiome in chronic wound healing. Our technique also identifies significant dependencies among microbial components as evidence of possible microbial syntrophy

Characterization of a Time-Domain Dual Lifetime Referencing pCO2 Optode and Deployment as a High-Resolution Underway Sensor across the High Latitude North Atlantic Ocean

The ocean is a major sink for anthropogenic carbon dioxide (CO2), with the CO2 uptake causing changes to ocean chemistry. To monitor these changes and provide a chemical background for biological and biogeochemical studies, high quality partial pressure of CO2 (pCO2) sensors are required, with suitable accuracy and precision for ocean measurements. Optodes have the potential to measure in situ pCO2 without the need for wet chemicals or bulky gas equilibration chambers that are typically used in pCO2 systems. However, optodes are still in an early developmental stage compared to more established equilibrator-based pCO2 systems. In this study, we performed a laboratory-based characterization of a time-domain dual lifetime referencing pCO2 optode system. The pCO2 optode spot was illuminated with low intensity light (0.2mA, 0.72 mW) to minimize spot photobleaching. The spot was calibrated using an experimental gas calibration rig prior to deployment, with a determined response time (t63) of 50 s at 25◦C. The pCO2 optode was deployed as an autonomous shipboard underway system across the high latitude North Atlantic Ocean with a resolution of ca.10 measurements per hour. The optode data was validated with a secondary shipboard equilibrator-based infrared pCO2 instrument, and pCO2 calculated fromdiscrete samples of dissolved inorganic carbon and total alkalinity. Further verification of the pCO2 optode data was achieved using complimentary variables such as nutrients and dissolved oxygen. The shipboard precision of the pCO2 sensor was 9.5μatmdetermined both from repeat measurements of certified reference materials and from the standard deviation of seawater measurements while on station. Finally, the optode deployment data was used to evaluate the physical and biogeochemical controls on pCO2

Space Station Human Factors: Designing a Human-Robot Interface

The experiments described in this paper are part of a larger joint MIT/NASA research effort and focus on the development of a methodology for designing and evaluating integrated interfaces for highly dexterous and multifunctional telerobot. Specifically, a telerobotic workstation is being designed for an Extravehicular Activity (EVA) anthropomorphic space station telerobot called Robonaut. Previous researchers have designed telerobotic workstations based upon performance of discrete subsets of tasks (for example, peg-in-hole, tracking, etc.) without regard for transitions that operators go through between tasks performed sequentially in the context of larger integrated tasks. The experiments presented here took an integrated approach to describing teleoperator performance and assessed how subjects operating a full-immersion telerobot perform during fine position and gross position tasks. In addition, a Robonaut simulation was also developed as part of this research effort, and experimentally tested against Robonaut itself to determine its utility. Results show that subject performance of teleoperated tasks using both Robonaut and the simulation are virtually identical, with no significant difference between the two. These results indicate that the simulation can be utilized as both a Robonaut training tool, and as a powerful design platform for telepresence displays and aids

Pre - Service Teachers’ Perceptions of Disability as Represented in Children’s Television Programs--RESEARCH

As colleges and universities prepare pre-service teachers to teach in inclusive classrooms, it is important to understand college students’ schema of diversity. Part of creating an inclusive classroom culture is to understand how children view similarities and differences in others, and how to create a culture of acceptance. One way to create a culture of understanding is to use media representations and popular children’s television shows as a springboard for conversation and acceptance, but before pre-service teachers can use media, they have to first understand the characteristics and qualification criteria for students with disabilities, and also how the community at large perceives children with disabilities. This research investigated pre-service teachers’ understanding of proportionality and equality in children’s television programming. University undergraduate students applying to or already admitted into teacher education programs watched several hours of children’s television programs and answered questions about the number of characters they observed with disabilities, as well as the way these characters and their disabilities were presented in the show. The research showed that pre-service teachers disproportionately identified more television characters as having disabilities. Implications for practice include increasing early knowledge of IDEA categories and focusing on positive inclusive models in children’s programming and media

The heterogeneous nature of Fe delivery from melting icebergs

The micronutrient iron (Fe) can be transported from marine terminating glaciers to the ocean by icebergs. There are however few observations of iceberg Fe content, and the flux of Fe from icebergs to the offshore surface ocean is poorly constrained. Here we report the dissolved Fe (DFe), total dissolvable Fe (TdFe) and ascorbic acid extractable Fe (FeAsc) sediment content of icebergs from Kongsfjorden, Svalbard. The concentrations of DFe (range 0.63 nM – 536 nM, mean 37 nM, median 6.5 nM) and TdFe (range 46 nM – 57 µM, mean 3.6 µM, median 144 nM) both demonstrated highly heterogeneous distributions and there was no significant correlation between these two fractions. FeAsc (range 0.0042 to 0.12 wt. %) was low compared to both previous measurements in Kongsfjorden and to current estimates of the global mean. FeAsc content per volume ice did however, as expected, show a significant relationship with sediment loading (which ranged from < 0.1 – 234 g L-1 of meltwater). In the Arctic, icebergs lose their sediment load faster than ice volume due to the rapid loss of basal ice after calving. We therefore suggest that the loss of basal ice is a potent mechanism for the reduction of mean TdFe and FeAsc per volume of iceberg. Delivery of TdFe and FeAsc to the ocean is thereby biased towards coastal waters where, in Kongsfjorden, DFe (18 ± 17 nM) and TdFe (mean 8.1 µM, median 3.7 µM) concentrations were already elevated

Developments in marine pCO2 measurement technology; towards sustained in situ observations

The oceanic uptake of anthropogenic CO2 causes pronounced changes to the marine carbonate system. High quality pCO2 measurements with good temporal and spatial coverage are required to monitor the oceanic uptake, identify regions with pronounced carbonate system changes, and observe the effectiveness of CO2 emission mitigation strategies. There are currently several instruments available, but many are unsuitable for autonomous deployments on in situ platforms such as gliders, moorings and Argo floats. We assess currently available technology on its suitability for in situ deployment, with a focus on optode technology developments. Optodes for pCO2 measurements provide a promising new technological approach, and were successfully calibrated over the range of 280–480 μatm applying modified time-domain dual lifetime referencing. A laboratory precision of 0.8 μatm (n = 10) and a response time (τ90) of 165 s were achieved, and with further development pCO2 optodes may become as widely used as their oxygen counterparts

Intracranial Injection of Dengue Virus Induces Interferon Stimulated Genes and CD8+ T Cell Infiltration by Sphingosine Kinase 1 Independent Pathways

Copyright: © 2017 Al-Shujairi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.We have previously reported that the absence of sphingosine kinase 1 (SK1) affects both dengue virus (DENV) infection and innate immune responses in vitro. Here we aimed to define SK1-dependancy of DENV-induced disease and the associated innate responses in vivo. The lack of a reliable mouse model with a fully competent interferon response for DENV infection is a challenge, and here we use an experimental model of DENV infection in the brain of immunocompetent mice. Intracranial injection of DENV-2 into C57BL/6 mice induced body weight loss and neurological symptoms which was associated with a high level of DENV RNA in the brain. Body weight loss and DENV RNA level tended to be greater in SK1-/- compared with wildtype (WT) mice. Brain infection with DENV-2 is associated with the induction of interferon-β (IFN-β) and IFN-stimulated gene (ISG) expression including viperin, Ifi27l2a, IRF7, and CXCL10 without any significant differences between WT and SK1-/- mice. The SK2 and sphingosine-1-phosphate (S1P) levels in the brain were unchanged by DENV infection or the lack of SK1. Histological analysis demonstrated the presence of a cellular infiltrate in DENV-infected brain with a significant increase in mRNA for CD8 but not CD4 suggesting this infiltrate is likely CD8+ but not CD4+ T-lymphocytes. This increase in T-cell infiltration was not affected by the lack of SK1. Overall, DENV-infection in the brain induces IFN and T-cell responses but does not influence the SK/S1P axis. In contrast to our observations in vitro, SK1 has no major influence on these responses following DENV-infection in the mouse brain

Association between baseline abundance of Peptoniphilus, a Gram-positive anaerobic coccus, and wound healing outcomes of DFUs

Diabetic foot ulcers (DFUs) lead to nearly 100,000 lower limb amputations annually in the United States. DFUs are colonized by complex microbial communities, and infection is one of the most common reasons for diabetes-related hospitalizations and amputations. In this study, we examined how DFU microbiomes respond to initial sharp debridement and off- loading and how the initial composition associates with 4 week healing outcomes. We employed 16S rRNA next generation sequencing to perform microbial profiling on 50 sam- ples collected from 10 patients with vascularized neuropathic DFUs. Debrided wound sam- ples were obtained at initial visit and after one week from two DFU locations, wound bed and wound edge. Samples of the foot skin outside of the wounds were also collected for compar- ison. We showed that DFU wound beds are colonized by a greater number of distinct bacte- rial phylotypes compared to the wound edge or skin outside the wound. However, no significant microbiome diversity changes occurred at the wound sites after one week of stan- dard care. Finally, increased initial abundance of Gram-positive anaerobic cocci (GPAC), especially Peptoniphilus (p \u3c 0.05; n = 5 subjects), was associated with impaired healing; thus, GPAC’s abundance could be a predictor of the wound-healing outcome