Deep Markov Random Field for Image Modeling

Markov Random Fields (MRFs), a formulation widely used in generative image modeling, have long been plagued by the lack of expressive power. This issue is primarily due to the fact that conventional MRFs formulations tend to use simplistic factors to capture local patterns. In this paper, we move beyond such limitations, and propose a novel MRF model that uses fully-connected neurons to express the complex interactions among pixels. Through theoretical analysis, we reveal an inherent connection between this model and recurrent neural networks, and thereon derive an approximated feed-forward network that couples multiple RNNs along opposite directions. This formulation combines the expressive power of deep neural networks and the cyclic dependency structure of MRF in a unified model, bringing the modeling capability to a new level. The feed-forward approximation also allows it to be efficiently learned from data. Experimental results on a variety of low-level vision tasks show notable improvement over state-of-the-arts.Comment: Accepted at ECCV 201

Evolution and comparative analysis of the MHC Class III inflammatory region

BACKGROUND: The Major Histocompatibility Complex (MHC) is essential for immune function. Historically, it has been subdivided into three regions (Class I, II, and III), but a cluster of functionally related genes within the Class III region has also been referred to as the Class IV region or "inflammatory region". This group of genes is involved in the inflammatory response, and includes members of the tumour necrosis family. Here we report the sequencing, annotation and comparative analysis of a tammar wallaby BAC containing the inflammatory region. We also discuss the extent of sequence conservation across the entire region and identify elements conserved in evolution. RESULTS: Fourteen Class III genes from the tammar wallaby inflammatory region were characterised and compared to their orthologues in other vertebrates. The organisation and sequence of genes in the inflammatory region of both the wallaby and South American opossum are highly conserved compared to known genes from eutherian ("placental") mammals. Some minor differences separate the two marsupial species. Eight genes within the inflammatory region have remained tightly clustered for at least 360 million years, predating the divergence of the amphibian lineage. Analysis of sequence conservation identified 354 elements that are conserved. These range in size from 7 to 431 bases and cover 15.6% of the inflammatory region, representing approximately a 4-fold increase compared to the average for vertebrate genomes. About 5.5% of this conserved sequence is marsupial-specific, including three cases of marsupial-specific repeats. Highly Conserved Elements were also characterised. CONCLUSION: Using comparative analysis, we show that a cluster of MHC genes involved in inflammation, including TNF, LTA (or its putative teleost homolog TNF-N), APOM, and BAT3 have remained together for over 450 million years, predating the divergence of mammals from fish. The observed enrichment in conserved sequences within the inflammatory region suggests conservation at the transcriptional regulatory level, in addition to the functional level

Changes in the functional diversity of modern bird species over the last million years

Despite evidence of declining biosphere integrity, we currently lack understanding of how the functional diversity associated with changes in abundance among ecological communities has varied over time and before widespread human disturbances. We combine morphological, ecological, and life-history trait data for >260 extant bird species with genomic-based estimates of changing effective population size (Ne) to quantify demographic-based shifts in avian functional diversity over the past million years and under pre-anthropogenic climate warming. We show that functional diversity was relatively stable over this period, but underwent significant changes in some key areas of trait space due to changing species abundances. Our results suggest that patterns of population decline over the Pleistocene have been concentrated in particular regions of trait space associated with extreme reproductive strategies and low dispersal ability, consistent with an overall erosion of functional diversity. Further, species most sensitive to climate warming occupied a relatively narrow region of functional space, indicating that the largest potential population increases and decreases under climate change will occur among species with relatively similar trait sets. Overall, our results identify fluctuations in functional space of extant species over evolutionary timescales and represent the demographic-based vulnerability of different regions of functional space among these taxa. The integration of paleodemographic dynamics with functional trait data enhances our ability to quantify losses of biosphere integrity before anthropogenic disturbances and attribute contemporary biodiversity loss to different drivers over time

High levels of genetic variability and differentiation in hilsa shad, Tenualosa ilisha (Clupeidae, Clupeiformes) populations revealed by PCR-RFLP analysis of the mitochondrial DNA D-loop region

The hilsa shad, Tenualosa ilisha (Clupeidae, Clupeiformes) is an important anadromous clupeid species from the Western division of the Indo-Pacific region. It constitutes the largest single fishable species in Bangladesh. Information on genetic variability and population structure is very important for both management and conservation purposes. Past reports on the population structure of T. ilisha involving morphometric, allozyme and RAPD analyses are contradictory. We examined genetic variability and divergence in two riverine (the Jamuna and the Meghna), two estuarine (Kuakata and Sundarbans) and one marine (Cox's Bazar) populations of T. ilisha by applying PCR-RFLP analysis of the mtDNA D-loop region. The amplified PCR products were restricted with four restriction enzymes namely, XbaI, EcoRI, EcoRV, and HaeIII. High levels of haplotype and gene diversity within and significant differentiations among, populations of T. ilisha were observed in this study. Significant FST values indicated differentiation among the river, estuary and marine populations. The UPGMA dendrogram based on genetic distance resulted in two major clusters, although, these were subsequently divided into three, corresponding to the riverine, estuarine and marine populations. The study underlines the usefulness of RFLP of mtDNA D-loop region as molecular markers, and detected at least two differentiated populations of T. ilisha in Bangladesh waters

FAM5C Contributes to Aggressive Periodontitis

Aggressive periodontitis is characterized by a rapid and severe periodontal destruction in young systemically healthy subjects. A greater prevalence is reported in Africans and African descendent groups than in Caucasians and Hispanics. We first fine mapped the interval 1q24.2 to 1q31.3 suggested as containing an aggressive periodontitis locus. Three hundred and eighty-nine subjects from 55 pedigrees were studied. Saliva samples were collected from all subjects, and DNA was extracted. Twenty-one single nucleotide polymorphisms were selected and analyzed by standard polymerase chain reaction using TaqMan chemistry. Non-parametric linkage and transmission distortion analyses were performed. Although linkage results were negative, statistically significant association between two markers, rs1935881 and rs1342913, in the FAM5C gene and aggressive periodontitis (p = 0.03) was found. Haplotype analysis showed an association between aggressive periodontitis and the haplotype A-G (rs1935881-rs1342913; p = 0.009). Sequence analysis of FAM5C coding regions did not disclose any mutations, but two variants in conserved intronic regions of FAM5C, rs57694932 and rs10494634, were found. However, these two variants are not associated with aggressive periodontitis. Secondly, we investigated the pattern of FAM5C expression in aggressive periodontitis lesions and its possible correlations with inflammatory/immunological factors and pathogens commonly associated with periodontal diseases. FAM5C mRNA expression was significantly higher in diseased versus healthy sites, and was found to be correlated to the IL-1β, IL-17A, IL-4 and RANKL mRNA levels. No correlations were found between FAM5C levels and the presence and load of red complex periodontopathogens or Aggregatibacter actinomycetemcomitans. This study provides evidence that FAM5C contributes to aggressive periodontitis

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Phylogenetic Analysis Suggests That Habitat Filtering Is Structuring Marine Bacterial Communities Across the Globe

The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes

Multilocus Bayesian Estimates of Intra-Oceanic Genetic Differentiation, Connectivity, and Admixture in Atlantic Swordfish (Xiphias gladius L.)

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Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

<p>Abstract</p> <p>Background</p> <p>Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.</p> <p>Methods</p> <p>Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.</p> <p>Results</p> <p>The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.</p> <p>Conclusion</p> <p>The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.</p