Constraint-based Mining of Frequent Arrangements of Temporal Intervals

The problem of discovering frequent arrangements of temporal intervals is studied. It is assumed that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine temporal arrangements of event intervals that appear frequently in the database. The motivation of this work is the observation that in practice most events are not instantaneous but occur over a period of time and different events may occur concurrently. Thus, there are many practical applications that require mining such temporal correlations between intervals including the linguistic analysis of annotated data from American Sign Language as well as network and biological data. Two efficient methods to find frequent arrangements of temporal intervals are described; the first one is tree-based and uses depth first search to mine the set of frequent arrangements, whereas the second one is prefix-based. The above methods apply efficient pruning techniques that include a set of constraints consisting of regular expressions and gap constraints that add user-controlled focus into the mining process. Moreover, based on the extracted patterns a standard method for mining association rules is employed that applies different interestingness measures to evaluate the significance of the discovered patterns and rules. The performance of the proposed algorithms is evaluated and compared with other approaches on real (American Sign Language annotations and network data) and large synthetic datasets.

Shifting ranges and conservation challenges for lemurs in the face of climate change.

Geospatial modeling is one of the most powerful tools available to conservation biologists for estimating current species ranges of Earth's biodiversity. Now, with the advantage of predictive climate models, these methods can be deployed for understanding future impacts on threatened biota. Here, we employ predictive modeling under a conservative estimate of future climate change to examine impacts on the future abundance and geographic distributions of Malagasy lemurs. Using distribution data from the primary literature, we employed ensemble species distribution models and geospatial analyses to predict future changes in species distributions. Current species distribution models (SDMs) were created within the BIOMOD2 framework that capitalizes on ten widely used modeling techniques. Future and current SDMs were then subtracted from each other, and areas of contraction, expansion, and stability were calculated. Model overprediction is a common issue associated Malagasy taxa. Accordingly, we introduce novel methods for incorporating biological data on dispersal potential to better inform the selection of pseudo-absence points. This study predicts that 60% of the 57 species examined will experience a considerable range of reductions in the next seventy years entirely due to future climate change. Of these species, range sizes are predicted to decrease by an average of 59.6%. Nine lemur species (16%) are predicted to expand their ranges, and 13 species (22.8%) distribution sizes were predicted to be stable through time. Species ranges will experience severe shifts, typically contractions, and for the majority of lemur species, geographic distributions will be considerably altered. We identify three areas in dire need of protection, concluding that strategically managed forest corridors must be a key component of lemur and other biodiversity conservation strategies. This recommendation is all the more urgent given that the results presented here do not take into account patterns of ongoing habitat destruction relating to human activities.

Spatial, seasonal and long-term fluctuations of plankton in relation to hydroclimatic features in the English Channel, Celtic Sea and Bay of Biscay

Plankton collected by the Continuous Plankton Recorder (CPR) survey were investigated for the English Channel, Celtic Sea and Bay of Biscay from 1979 to 1995. The main goal was to study the relationship between climate and plankton and to understand the factors influencing it. In order to take into account the spatial and temporal structure of biological data, a three-mode principal component analysis (PCA) was developed. It not only identified 5 zones characterised by their similar biological composition and by the seasonal and inter-annual evolution of the plankton, it also made species associations based on their location and year-to-year change. The studied species have stronger year-to-year fluctuations in abundance over the English Channel and Celtic Sea than the species offshore in the Bay of Biscay. The changes in abundance of plankton in the English Channel are negatively related to inter-annual changes of climatic conditions from December to March (North Atlantic Oscillation [NAO] index and air temperature). Thus, the negative relationship shown by Fromentin and Planque (1996; Mar Ecol Prog Ser 134:111-118) between year-to-year changes of Calanus finmarchicus abundance in the northern North Atlantic and North Sea and NAO was also found for the most abundant copepods in the Channel. However, the hypothesis proposed to explain the plankton/NAO relationship is different for this region and a new hypothesis is proposed. In the Celtic Sea, a relationship between the planktonic assemblage and the air temperature was detected, but it is weaker than for the English Channel. No relationship was found for the Bay of Biscay. Thus, the local physical environment and the biological composition of these zones appear to modify the relationship between winter climatic conditions and the year-to-year fluctuations of the studied planktonic species. This shows, therefore, that the relationship between climate and plankton is difficult to generalise.

An overview of plankton ecology in the North Sea

The purpose of this report is to give an overview of plankton ecology in the North Sea, and the processes that effect it, as derived from current research. The Sir Alister Hardy Foundation has extensive data for the North Sea area, and other sources have also been used to provide information for this report. Shortfalls in current research have also been highlighted. The information contained herein is to be contributed towards an information base for the Strategic Environmental Assessment. The North Sea is an extension of the North Atlantic that has an area of 574,980 km2. The deepest area is off the coast of Norway (660m), with a number of shallow areas, such as the Dogger Bank (15m). The North Sea represents a large source of hydrocarbons that have been exploited since the early 1970s. The aim of this study is to provide the Department of Trade and Industry with biological data on the planktonic community of the North Sea, as a contribution towards the Strategic Environmental Assessment (SEA 2). An overview of phyto- and zoo- plankton community composition, plankton blooms, Calanus, mero-, pico- and megaplankton, sensitivity to disturbance / contamination, phytodetritus and vertical fluxes and the resting stages of phytoplankton is made using the results of the survey database. Additional published literature has also been used, and gaps in available data have been highlighted. 1.3 The Continuous Plankton Recorder (CPR) survey provides a unique long-term dataset of plankton abundance in the North Atlantic and North Sea (Warner and Hays 1994). The survey has been running for almost 70 years, using ‘ships of opportunity’ to tow CPRs on regular, and incidental routes, sampling at a depth of 10 m. Each sample represents 18 km of tow and approximately 3 m3 of filtered seawater. Over 400 taxa of plankton are routinely identified by a team of taxonomists. The samples are also compared to colour charts to give an indication of ‘greenness’, which provides a visual index of chlorophyll value. CPRs have been towed for over 4 million nautical miles, accumulating almost 200,000 samples. The design of the CPR has remained virtually unchanged since sampling started, thus providing a consistency of sampling that provides good historical comparisons. By systematically monitoring the plankton over a period, changes in abundance and long term trends can be distinguished. From this baseline data, inferences can be made, particularly concerning climate change and potentialanthropogenic impacts.

Macroecology of Calanus finmarchicus and C. helgolandicus in the North Atlantic Ocean and adjacent seas

Global climate change is expected to modify the spatial distribution of marine organisms. However, projections of future changes should be based on robust information on the ecological niche of species. This paper presents a macroecological study of the environmental tolerance and ecological niche (sensu Hutchinson 1957, i.e. the field of tolerance of a species to the principal factors of its environment) of Calanus finmarchicus and C. helgolandicus in the North Atlantic Ocean and adjacent seas. Biological data were collected by the Continuous Plankton Recorder (CPR) Survey, which samples plankton in the North Atlantic and adjacent seas at a standard depth of 7 m. Eleven parameters were chosen including bathymetry, temperature, salinity, nutrients, mixed-layer depth and an index of turbulence compiled from wind data and chlorophyll a concentrations (used herein as an index of available food). The environmental window and the optimum level were determined for both species and for each abiotic factor and chlorophyll concentration. The most important parameters that influenced abundance and spatial distribution were temperature and its correlates such as oxygen and nutrients. Bathymetry and other water-column-related parameters also played an important role. The ecological niche of C. finmarchicus was larger than that of C. helgolandicus and both niches were significantly separated. Our results have important implications in the context of global climate change. As temperature (and to some extent stratification) is predicted to continue to rise in the North Atlantic sector, changes in the spatial distribution of these 2 Calanus species can be expected. Application of this approach to the 1980s North Sea regime shift provides evidence that changes in sea temperature alone could have triggered the substantial and rapid changes identified in the dynamic regimes of these ecosystems. C. finmarchicus appears to be a good indicator of the Atlantic Polar Biome (mainly the Atlantic Subarctic and Arctic provinces) while C. helgolandicus is an indicator of more temperate waters (Atlantic Westerly Winds Biome) in regions characterised by more pronounced spatial changes in bathymetry.

Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets

Motivation: Recently, many univariate and several multivariate approaches have been suggested for testing differential expression of gene sets between different phenotypes. However, despite a wealth of literature studying their performance on simulated and real biological data, still there is a need to quantify their relative performance when they are testing different null hypotheses.

Results: In this article, we compare the performance of univariate and multivariate tests on both simulated and biological data. In the simulation study we demonstrate that high correlations equally affect the power of both, univariate as well as multivariate tests. In addition, for most of them the power is similarly affected by the dimensionality of the gene set and by the percentage of genes in the set, for which expression is changing between two phenotypes. The application of different test statistics to biological data reveals that three statistics (sum of squared t-tests, Hotelling's T2, N-statistic), testing different null hypotheses, find some common but also some complementing differentially expressed gene sets under specific settings. This demonstrates that due to complementing null hypotheses each test projects on different aspects of the data and for the analysis of biological data it is beneficial to use all three tests simultaneously instead of focusing exclusively on just one.

Biogeography, macroecology and species’ traits mediate competitive interactions in the order Lagomorpha

1. In addition to abiotic determinants, biotic factors, including competitive, interspecific interactions, limit species’ distributions. Environmental changes in human disturbance, land use and climate are predicted to have widespread impacts on interactions between species, especially in the order Lagomorpha due to the higher latitudes and more extreme environmental conditions they occupy.
2. We reviewed the published literature on interspecific interactions in the order Lagomorpha, and compared the biogeography, macroecology, phylogeny and traits of species known to interact with those of species with no reported interactions, to investigate how projected future environmental change may affect interactions and potentially alter species’ distributions.
3. Thirty-three lagomorph species have competitive interactions reported in the literature; the majority involve hares (Lepus sp.) or the eastern cottontail rabbit (Sylvilagus floridanus). Key regions for interactions are located between 30-50°N of the Equator, and include eastern Asia (southern Russia on the border of Mongolia) and North America (north western USA).
4. Closely related, large-bodied, similarly sized species occurring in regions of human-modified, typically agricultural landscapes, or at high elevations are significantly more likely to have reported competitive interactions than other lagomorph species.
5. We identify species’ traits associated with competitive interactions, and highlight some potential impacts that future environmental change may have on interspecific interactions. Our approach using bibliometric and biological data is widely applicable, and with relatively straightforward methodologies, can provide insights into interactions between species.
6. Our results have implications for predicting species’ responses to global change, and we advise that capturing, parameterizing and incorporating interspecific interactions into analyses (for example, species distribution modelling) may be more important than suggested by the literature.

EpsinR an AP1/clathrin interacting protein involved in vesicle trafficking

EpsinR is a clathrin-coated vesicle (CCV) enriched 70-kD protein that binds to phosphatidylinositol-4-phosphate, clathrin, and the gamma appendage domain of the adaptor protein complex 1 (AP1). In cells, its distribution overlaps with the perinuclear pool of clathrin and AP1 adaptors. Overexpression disrupts the CCV-dependent trafficking of cathepsin D from the trans-Golgi network to lysosomes and the incorporation of mannose-6-phosphate receptors into CCVs. These biochemical and cell biological data point to a role for epsinR in AP1/clathrin budding events in the cell, just as epsin1 is involved in the budding of AP2 CCVs. Furthermore, we show that two gamma appendage domains can simultaneously bind to epsinR with affinities of 0.7 and 45 microM, respectively. Thus, potentially, two AP1 complexes can bind to one epsinR. This high affinity binding allowed us to identify a consensus binding motif of the form DFxDF, which we also find in gamma-synergin and use to predict that an uncharacterized EF-hand-containing protein will be a new gamma binding partner.

Environmental exposure to toxicants mixtures from a multi-purpose estuary: perspectives for a biomonitoring study in Portugal

This work was focused on a multi-purpose estuarine environment (river Sado estuary, SW Portugal) around which a number of activities (e.g., fishing, farming, heavy industry, tourism and recreational activities) coexist with urban centres with a total of about 200 000 inhabitants. Based on previous knowledge of the hazardous chemicals within the ecosystem and their potential toxicity to benthic species, this project intended to evaluate the impact of estuarine contaminants on the human and ecosystem health. An integrative methodology based on epidemiological, analytical and biological data and comprising several lines of evidence, namely, human contamination pathways, human health effects, consumption of local produce, estuarine sediments, wells and soils contamination, effects on commercial benthic organisms, and genotoxic potential of sediments, was used. The epidemiological survey confirmed the occurrence of direct and indirect (through food chain) exposure of the local population to estuarine contaminants. Furthermore, the complex mixture of contaminants (e.g., metals, pesticides, polycyclic aromatic hydrocarbons) trapped in the estuary sediments was toxic to human liver cells exposed in vitro, causing cell death, oxidative stress and genotoxic effects that might constitute a risk factor for the development of chronic-degenerative diseases, on the long term. Finally, the integration of data from several endpoints indicated that the estuary is moderately impacted by toxicants that affect also the aquatic biota. Nevertheless, the human health risk can only be correctly assessed through a biomonitoring study including the quantification of contaminants (or metabolites) in biological fluids as well as biomarkers of early biological effects (e.g., biochemical, genetic and omics-based endpoints) and genetic susceptibility in the target population. Data should be supported by a detailed survey to assess the impact of the contaminated seafood and local farm products consumption on human health and, particularly, on metabolic diseases or cancer development.

New insights into functional regulation in MS-based drug profiling

We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.

Estimating the risk of developing type 2 diabetes: a comparison of several risk scores: the Cohorte Lausannoise study.

To compare in the Swiss population the results of several scores estimating the risk of developing type 2 diabetes. This was a single-center, cross-sectional study conducted between 2003 and 2006 in Lausanne, Switzerland. Overall, 3,251 women and 2,937 men, aged 35-75 years, were assessed, of which 5,760 (93%) were free from diabetes and included in the current study. The risk of developing type 2 diabetes was assessed using seven different risk scores, including clinical data with or without biological data. Participants were considered to be eligible for primary prevention according to the thresholds provided for each score. The results were then extrapolated to the Swiss population of the same sex and age. The risk of developing type 2 diabetes increased with age in all scores. The prevalence of participants at high risk ranged between 1.6 and 24.9% in men and between 1.1 and 15.7% in women. Extrapolated to the Swiss population of similar age, the overall number of participants at risk, and thus susceptible to intervention, ranged between 46,708 and 636,841. In addition, scores that included the same clinical variables led to a significantly different prevalence of participants at risk (4.2% [95% CI 3.4-5.0] vs. 12.8% [11.5-14.1] in men and 2.9% [2.4-3.6] vs. 6.0% [5.2-6.9] in women). CONCLUSIONS; The prevalence of participants at risk for developing type 2 diabetes varies considerably according to the scoring system used. To adequately prevent type 2 diabetes, risk-scoring systems must be validated for each population considered.

Diatoms as indicators of lake trophic status

Relationships between surface sediment diatom assemblages and lake trophic status were studied in 50 Canadian Precambrian Shield lakes in the Muskoka-Haliburton and southern Ontario regions. The purpose of this study was to develop mathematical regression models to infer lake trophic status from diatom assemblage data. To achieve this goal, however, additional investigations dealing with the evaluation of lake trophic status and the autecological features of key diatom species were carried out. Because a unifying index and classification for lake trophic status was not available, a new multiple index was developed in this study, by the computation of the physical, chemical and biological data from 85 south Ontario lakes. By using the new trophic parameter, the lake trophic level (TL) was determined: TL = 1.37 In[1 +(TP x Chl-a / SD)], where, TP=total phosphorus, Chl-a=chlorophyll-a and SD=Secchi depth. The boundaries between 7 lake trophic categories (Ultra-oligotrophic lakes: 0-0.24; Oligotrophic lakes: 0.241-1.8; Oligomesotrophic lakes: 1.813.0; Mesotrophic lakes: 3.01-4.20; Mesoeutrophic lakes: 4.21-5.4; Eutrophic lakes: 5.41-10 and Hyper-eutrophic lakes: above 10) were established. The new trophic parameter was more convenient for management of water quality, communication to the public and comparison with other lake trophic status indices than many of the previously published indices because the TL index attempts to Increase understanding of the characteristics of lakes and their comprehensive trophic states. It is more reasonable and clear for a unifying determination of true trophic states of lakes. Diatom specIes autecology analysis was central to this thesis. However, the autecological relationship of diatom species and lake trophic status had not previously been well documented. Based on the investigation of the diatom composition and variety of species abundance in 30 study lakes, the distribution optima of diatom species were determined. These determinations were based on a quantitative method called "weighted average" (Charles 1985). On this basis, the diatom species were classified into five trophic categories (oligotrophic, oligomesotrophic, mesotrophic, mesoeutrophic and eutrophic species groups). The resulting diatom trophic status autecological features were used in the regressIon analysis between diatom assemblages and lake trophic status. When the TL trophic level values of the 30 lakes were regressed against their fi ve corresponding diatom trophic groups, the two mathematical equations for expressing the assumed linear relationship between the diatom assemblages composition were determined by (1) uSIng a single regression technique: Trophic level of lake (TL) = 2.643 - 7.575 log (Index D) (r = 0.88 r2 = 0.77 P = 0.0001; n = 30) Where, Index D = (0% + OM% + M%)/(E% + ME% + M%); 4 (2) uSIng a' multiple regressIon technique: TL=4.285-0.076 0%- 0.055 OM% - 0.026 M% + 0.033 ME% + 0.065 E% (r=0.89, r2=0.792, P=O.OOOl, n=30) There was a significant correlation between measured and diatom inferred trophic levels both by single and multiple regressIon methods (P < 0.0001, n=20), when both models were applied to another 20 test lakes. Their correlation coefficients (r2 ) were also statistically significant (r2 >0.68, n=20). As such, the two transfer function models between diatoms and lake trophic status were validated. The two models obtained as noted above were developed using one group of lakes and then tested using an entirely different group of lakes. This study indicated that diatom assemblages are sensitive to lake trophic status. As indicators of lake trophic status, diatoms are especially useful in situations where no local trophic information is available and in studies of the paleotrophic history of lakes. Diatom autecological information was used to develop a theory assessing water quality and lake trophic status.

The nesting biology of Ceratina (Hymenoptera: Apidae) in the Niagara Region : new species, nest site selection and parasitism

One of the most common bee genera in the Niagara Region, the genus Ceratina (Hymenoptera: Apidae) is composed of four species, C. dupla, C. calcarata, the very rare C. strenua, and a previously unknown species provisionally named C. near dupla. The primary goal of this thesis was to investigate how these closely related species coexist with one another in the Niagara ~ee community. The first necessary step was to describe and compare the nesting biologies and life histories of the three most common species, C. dupla, C. calcarata and the new C. near dupla, which was conducted in 2008 via nest collections and pan trapping. Ceratina dupla and C. calcarata were common, each comprising 49% of the population, while C. near dupla was rare, comprising only 2% of the population. Ceratina dupla and C. near dupla both nested more commonly in teasel (Dipsacus sp.) in the sun, occasionally in raspberry (Rubus sp.) in the shade, and never in shady sumac (Rhus sp.), while C. calcarata nested most commonly in raspberry and sumac (shaded) and occasionally in teasel (sunny). Ceratina near dupla differed from both C. dupla and C. calcarata in that it appeared to be partially bivoltine, with some females founding nests very early and then again very late in the season. To examine the interactions and possible competition for nests that may be taking place between C. dupla and C. calcarata, a nest choice experiment was conducted in 2009. This experiment allowed both species to choose among twigs from all three substrates in the sun and in the shade. I then compared the results from 2008 (where bees chose from what was available), to where they nested when given all options (2009 experiment). Both C. dupla and C. calcarata had the same preferences for microhabitat and nest substrate in 2009, that being raspberry and sumac twigs in the sun. As that microhabitat and nest substrate combination is extremely rare in nature, both species must make a choice. In nature Ceratina dupla nests more often in the preferred microhabitat (sun), while C. calcarata nests in the preferred substrate (raspberry). Nesting in the shade also leads to smaller clutch sizes, higher parasitism and lower numbers of live brood in C. calcarata, suggesting that C. dupla may be outcompeting C. calcarata for the sunny nesting sites. The development and host preferences of Ceratina parasitoids were also examined. Ceratina species in Niagara were parasitized by no less than eight species of arthropod. Six of these were wasps from the superfamily Chalcidoidea (Hymenoptera), one was a wasp from the family Ichneumonidae (Hymenoptera) and one was a physogastric mite from the family Pyemotidae (Acari). Parasites shared a wide range of developmental strategies, from ichneumonid larvae that needed to consume multiple Ceratina immatures to complete development, to the species from the Eulophidae (Baryscapus) and Encyrtidae (Coelopencyrtus), in which multiple individuals completed development inside a single Ceratina host. Biological data on parasitoids is scarce in the scientific literature, and this Chapter documents these interactions for future research.

The Synthesis of Imidazole Fatty Acid Conjugates as Inhibitors of Apoptosis

Ionizing radiation is known to initiate apoptosis in mammalian cells by causing the transformation of cytochrome c into a peroxidase, which results in the specific peroxidation of the mitochondrial phospholipid cardiolipin. Here we report the design and synthesis of 8 imidazole fatty acid derivatives that bind to the cyt c:CL complex and inhibit the peroxidase activity required for the initiation of apoptosis. We postulate that imidazole acts as a sixth ligand to the haem iron and stops the interaction with H2O2. Two mitochondrially directed analogues (3-hydroxypropyl)triphenylphosphonium esters) of 12-imidazole-stearic acid and 12-imidazole-oleic acid not only were demonstrated to be peroxidase inhibitors in vitro, but were also extraordinarily effective in protecting mice from lethal doses (9 Gy) of ionization radiation. We studied the structure activity relationship to a group of triphenyl phosphonium derivatives containing imidazole at different positions on the fatty acid chain, and observed that the C8-imidazole stearate analogue had marginally better activity than the others. But overall, the structure activity result were remarkable “flat” with all compounds prepared having rather similar inhibitory strength. We also synthesized carnitine mono and di-esters of 12-imidazole fatty acids but full biological data is not yet available for these compounds.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.