Transcriptome and Functional Analysis of Carotid Body Glomus Cells

The carotid body (CB) is a major arterial chemoreceptor containing glomus cells that are activated by changes in arterial blood contents including oxygen. Despite significant advancement in the characterization of their physiological properties, our understanding on the underlying molecular machinery and signaling pathway in CB glomus cells is still limited.

To overcome these limitations, in chapter 1, I demonstrated the first transcriptome profile of CB glomus cells using single cell sequencing technology, which allowed us to uncover a set of abundantly expressed genes, including novel glomus cell-specific transcripts. These results revealed involvement of G protein-coupled receptor (GPCR) signaling pathway, various types of ion channels, as well as atypical mitochondrial subunits in CB function. I also identified ligands for the mostly highly expressed GPCR (Olfr78) in CB glomus cells and examined this receptor’s role in CB mediated hypoxic ventilatory response.

Current knowledge of CB suggest glomus cells rely on unusual mitochondria for their sensitivity to hypoxia. I previously identified the atypical mitochondrial subunit Ndufa4l2 as a highly over-represented gene in CB glomus cells. In chapter 2, to investigate the functional significance of Ndufa4l2 in CB function, I phenotyped both Ndufa4l2 knockout mice and mice with conditional Ndufa4l2 deletion in CB glomus cells. I found that Ndufa4l2 is essential to the establishment of regular breathing after birth. Ablating Ndufa4l2 in postnatal CB glomus cells resulted in defective CB sensitivity to hypoxia as well as CB mediated hypoxic ventilatory response. Together, our data showed that Ndufa4l2 is critical to respiratory control and the oxygen sensitivity of CB glomus cells.

The effects of centrally acting ACE inhibitors on the rate of cognitive and functional decline in dementia: a KDD approach

Alzheimer’s Disease and other dementias are one of the most challenging illnesses confronting countries with ageing populations. Treatment options for dementia are limited, and the costs are significant. There is a growing need to develop new treatments for dementia, especially for the elderly. There is also growing evidence that centrally acting angiotensin converting enzyme (ACE) inhibitors, which cross the blood-brain barrier, are associated with a reduced rate of cognitive and functional decline in dementia, especially in Alzheimer’s disease (AD). The aim of this research is to investigate the effects of centrally acting ACE inhibitors (CACE-Is) on the rate of cognitive and functional decline in dementia, using a three phased KDD process. KDD, as a scientific way to process and analysis clinical data, is used to find useful insights from a variety of clinical databases. The data used are from three clinic databases: Geriatric Assessment Tool (GAT), the Doxycycline and Rifampin for Alzheimer’s Disease (DARAD), and the Qmci validation databases, which were derived from several different geriatric clinics in Canada. This research involves patients diagnosed with AD, vascular or mixed dementia only. Patients were included if baseline and end-point (at least six months apart) Standardised Mini-Mental State Examination (SMMSE), Quick Mild Cognitive Impairment (Qmci) or Activities Daily Living (ADL) scores were available. Basically, the rates of change are compared between patients taking CACE-Is, and those not currently treated with CACE-Is. The results suggest that there is a statistically significant difference in the rate of decline in cognitive and functional scores between CACE-I and NoCACE-I patients. This research also validates that the Qmci, a new short assessment test, has potential to replace the current popular screening tests for cognition in the clinic and clinical trials.

Assessment of the Spatial and Temporal Distribution of Functional Connectivity in Resting-State BOLD fMRI

Recent research into resting-state functional magnetic resonance imaging (fMRI) has shown that the brain is very active during rest. This thesis work utilizes blood oxygenation level dependent (BOLD) signals to investigate the spatial and temporal functional network information found within resting-state data, and aims to investigate the feasibility of extracting functional connectivity networks using different methods as well as the dynamic variability within some of the methods. Furthermore, this work looks into producing valid networks using a sparsely-sampled sub-set of the original data.

In this work we utilize four main methods: independent component analysis (ICA), principal component analysis (PCA), correlation, and a point-processing technique. Each method comes with unique assumptions, as well as strengths and limitations into exploring how the resting state components interact in space and time.

Correlation is perhaps the simplest technique. Using this technique, resting-state patterns can be identified based on how similar the time profile is to a seed region’s time profile. However, this method requires a seed region and can only identify one resting state network at a time. This simple correlation technique is able to reproduce the resting state network using subject data from one subject’s scan session as well as with 16 subjects.

Independent component analysis, the second technique, has established software programs that can be used to implement this technique. ICA can extract multiple components from a data set in a single analysis. The disadvantage is that the resting state networks it produces are all independent of each other, making the assumption that the spatial pattern of functional connectivity is the same across all the time points. ICA is successfully able to reproduce resting state connectivity patterns for both one subject and a 16 subject concatenated data set.

Using principal component analysis, the dimensionality of the data is compressed to find the directions in which the variance of the data is most significant. This method utilizes the same basic matrix math as ICA with a few important differences that will be outlined later in this text. Using this method, sometimes different functional connectivity patterns are identifiable but with a large amount of noise and variability.

To begin to investigate the dynamics of the functional connectivity, the correlation technique is used to compare the first and second halves of a scan session. Minor differences are discernable between the correlation results of the scan session halves. Further, a sliding window technique is implemented to study the correlation coefficients through different sizes of correlation windows throughout time. From this technique it is apparent that the correlation level with the seed region is not static throughout the scan length.

The last method introduced, a point processing method, is one of the more novel techniques because it does not require analysis of the continuous time points. Here, network information is extracted based on brief occurrences of high or low amplitude signals within a seed region. Because point processing utilizes less time points from the data, the statistical power of the results is lower. There are also larger variations in DMN patterns between subjects. In addition to boosted computational efficiency, the benefit of using a point-process method is that the patterns produced for different seed regions do not have to be independent of one another.

This work compares four unique methods of identifying functional connectivity patterns. ICA is a technique that is currently used by many scientists studying functional connectivity patterns. The PCA technique is not optimal for the level of noise and the distribution of the data sets. The correlation technique is simple and obtains good results, however a seed region is needed and the method assumes that the DMN regions is correlated throughout the entire scan. Looking at the more dynamic aspects of correlation changing patterns of correlation were evident. The last point-processing method produces a promising results of identifying functional connectivity networks using only low and high amplitude BOLD signals.

Cocrystallisation involving the thioamide, amide and imide functional groups

The work presented in this dissertation focused on the development and characterisation of novel cocrystals that incorporated the thioamide, amide and imide functional groups. A particular emphasis was placed on the characterisation of these cocrystals by single crystal X-ray diffraction methods. In Chapter One a summary of the intermolecular interactions utilised in this work and a short review of the solid state and multicomponent systems is provided. A brief introduction to the ways in which different multicomponent systems can be distinguished, crystal engineering strategies and a number of cocrystal applications highlights the importance the understanding of intermolecular interactions can have on the physical and chemical properties of crystalline materials. Chapter Two is the first Results and Discussion chapter and includes an introduction that is specific to the chapter. The main body of this work focuses on the primary aromatic thioamide functional group and its propensity to cocrystallise with a number of sulfoxides. Unlike the amide functional group, thioamides are not commonly employed in cocrystallisation studies. This chapter presents the first direct comparison between the cocrystallisation abilities of these two functional groups and the intermolecular hydrogen bonding interactions present in the cocrystal structures are examined. Chapter Three describes the crystal landscape of a short series of secondary aromatic amides and their analogous thioamides. Building on the results obtained in Chapter Two, a cocrystal screen of the secondary thioamides with the sulfoxide functional group was carried out in order to determine the effect removing a hydrogen bond had on the supramolecular synthons observed in the cocrystals. These secondary thioamides are also utilised in Chapter Four, which examines their halogen bonding capabilities with two organoiodine coformers: 1,2- and 1,4-diiodotetrafluorobenzene. Chapter Five explores the cocrystallisation abilities of three related cyclic imides as coformers for cocrystallisation with a range of commonly used coformers. Chapter Six is an overall conclusions chapter that highlights the findings of the results presented in Chapters Two to Five. Chapter Seven details the instrument and experimental data for the compounds and cocrystals discussed in the Results and Discussion Chapters. The accompanying CD contains all of the crystallographic data in .cif format for the novel single crystal structures characterised in this work.

Content-aware compression for big textual data analysis

A substantial amount of information on the Internet is present in the form of text. The value of this semi-structured and unstructured data has been widely acknowledged, with consequent scientific and commercial exploitation. The ever-increasing data production, however, pushes data analytic platforms to their limit. This thesis proposes techniques for more efficient textual big data analysis suitable for the Hadoop analytic platform. This research explores the direct processing of compressed textual data. The focus is on developing novel compression methods with a number of desirable properties to support text-based big data analysis in distributed environments. The novel contributions of this work include the following. Firstly, a Content-aware Partial Compression (CaPC) scheme is developed. CaPC makes a distinction between informational and functional content in which only the informational content is compressed. Thus, the compressed data is made transparent to existing software libraries which often rely on functional content to work. Secondly, a context-free bit-oriented compression scheme (Approximated Huffman Compression) based on the Huffman algorithm is developed. This uses a hybrid data structure that allows pattern searching in compressed data in linear time. Thirdly, several modern compression schemes have been extended so that the compressed data can be safely split with respect to logical data records in distributed file systems. Furthermore, an innovative two layer compression architecture is used, in which each compression layer is appropriate for the corresponding stage of data processing. Peripheral libraries are developed that seamlessly link the proposed compression schemes to existing analytic platforms and computational frameworks, and also make the use of the compressed data transparent to developers. The compression schemes have been evaluated for a number of standard MapReduce analysis tasks using a collection of real-world datasets. In comparison with existing solutions, they have shown substantial improvement in performance and significant reduction in system resource requirements.

An investigation of the functional role of GRAB in the context of Rab3, Rab8 and Rab11

Rab GTPases are the largest family of the Ras superfamily and are key regulators of membrane trafficking within the cell. There are over 60 members of the Rab family which localise to specific membrane compartments and interact with effector proteins to regulate membrane trafficking processes, such as vesicle formation, vesicle trafficking within the cell and fusion with an acceptor compartment. Multiple effector proteins have been identified for many Rabs, some of which can interact with more than one Rab to link their function at a specific membrane location or to link them together in a Rab activation cascade. Rabin8 is one such protein which is an effector for Rab11a and a Guanine nucleotide Exchange Factor (GEF) for Rab8a. Rabin8 participates in a conserved Rab activation cascade which is critical in the formation of primary cilia. Data presented in this thesis has shown that GRAB interacts with Rab3a, Rab8a, Rab11a and Rab11b in a nucleotide dependent manner. Furthermore, the minimal interacting regionbetween these proteins has been investigated. The functional outcome of GRAB knockdown has also been examined and data in this thesis highlights the phenotypic outcome.

Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs Gamma-A nifH genes abundance, computed from a collection of source data sets.

Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.

Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in netCDF format

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

Biogeochemical data from terrestrial and aquatic ecosystems in a periglacial catchment, West Greenland

Global warming is expected to be most pronounced in the Arctic where permafrost thaw and release of old carbon may provide an important feedback mechanism to the climate system. To better understand and predict climate effects and feedbacks on the cycling of elements within and between ecosystems in northern latitude landscapes, a thorough understanding of the processes related to transport and cycling of elements is required. A fundamental requirement to reach a better process understanding is to have access to high-quality empirical data on chemical concentrations and biotic properties for a wide range of ecosystem domains and functional units (abiotic and biotic pools). The aim of this study is therefore to make one of the most extensive field data sets from a periglacial catchment readily available that can be used both to describe present-day periglacial processes and to improve predictions of the future. Here we present the sampling and analytical methods, field and laboratory equipment and the resulting biogeochemical data from a state-of-the-art whole-ecosystem investigation of the terrestrial and aquatic parts of a lake catchment in the Kangerlussuaq region, West Greenland. This data set allows for the calculation of whole-ecosystem mass balance budgets for a long list of elements, including carbon, nutrients and major and trace metals.

Structural and functional vulnerability to elevated pCO2 in marine benthic communities

The effect of elevated pCO2/low pH on marine invertebrate benthic biodiversity, community structure and selected functional responses which underpin ecosystem services (such as community production and calcification) was tested in a medium-term (30 days) mesocosm experiment in June 2010. Standardised intertidal macrobenthic communities, collected (50.3567°N, 4.1277°W) using artificial substrate units (ASUs), were exposed to one of seven pH treatments (8.05, 7.8. 7.6, 7.4, 7.2, 6.8 and 6.0). Community net calcification/dissolution rates, as well as changes in biomass, community structure and diversity, were measured at the end of the experimental period. Communities showed significant changes in structure and reduced diversity in response to reduced pH: shifting from a community dominated by calcareous organisms to one dominated by non-calcareous organisms around either pH 7.2 (number of individuals and species) or pH 7.8 (biomass). These results were supported by a reduced total weight of CaCO3 structures in all major taxa at lowered pH and a switch from net calcification to net dissolution around pH 7.4 (Omega calc = 0.78, Omega ara = 0.5). Overall community soft tissue biomass did not change with pH and high mortality was observed only at pH 6.0, although molluscs and arthropods showed significant decreases in soft tissue. This study supports and refines previous findings on how elevated pCO2 can induce changes in marine biodiversity, underlined by differential vulnerability of different phyla. In addition, it shows significant elevated pCO2-/low pH-dependent changes in fundamental community functional responses underpinning changes in ecosystem services.

Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs nitrogen fixation rates, computed from a collection of source data sets.

Collection of data on aboveground invertebrates in the Jena Experiment (time series since 2002)

This collection contains measurements of abundance and diversity of different groups of aboveground invertebrates sampled on the plots of the different sub-experiments at the field site of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. The following series of datasets are contained in this collection: 1. Measurements of ant abundance (number of individuals attracted to baits) and ant occurrence (binary data) in the Main Experiment in 2006 and 2013. Ants where sampled using two types of baited traps receiving ~10g of Tuna or ~10g of honey/Sucrose. After 30min the occurrence (presence = 1 / absence = 0) and abundance (number) of ants at the two types of baits was recorded and pooled per plot.