Untangling the Genetic Basis of Fibrolytic Specialization by Lachnospiraceae and Ruminococcaceae in Diverse Gut Communities

The Lachnospiraceae and Ruminococcaceae are two of the most abundant families from the order Clostridiales found in the mammalian gut environment, and have been associated with the maintenance of gut health. While they are both diverse groups, they share a common role as active plant degraders. By comparing the genomes of the Lachnospiraceae and Ruminococcaceae with the Clostridiaceae, a more commonly free-living group, we identify key carbohydrate-active enzymes, sugar transport mechanisms, and metabolic pathways that distinguish these two commensal groups as specialists for the degradation of complex plant material

Energetic Limitations Of Thermophilic Methanogens And Thiosulfate Reducers In The Subsurface Biosphere At Deep-Sea Hydrothermal Vents

This dissertation examined the substrate and energetic limitations of hydrogenotrophic thermophiles from deep-sea hydrothermal vents. Thermophilic and hyperthermophilic organisms in diffuse hydrothermal venting are thought to represent a hot subsurface biosphere associated with deep-sea hydrothermal vents, where primary production is dominated by hydrogenotrophy rather than sulfide oxidation as at the vent/seawater interface of hydrothermal sulfide chimneys. Methanogens and sulfur-reducers are known to compete for hydrogen in mesophilic, freshwater systems, and likely do so in deep-sea hydrothermal vent environments as well. However, the exact size and biomass of the subsurface biosphere is difficult to determine through direct sampling. Firstly, the distribution of thermophilic and hyperthermophilic methanogens, sulfur-reducers, and heterotrophs in diffuse venting fluids at our field site, Axial Volcano (on the Juan de Fuca Ridge), was examined using culture-dependent (Most-Probable-Number) and independent (omics) techniques. It was confirmed that methane production in diffuse venting fluids could be stimulated by the sole addition of hydrogen and incubation at thermophilic and/or hyperthermophilic temperatures, indicating that methanogens in this system are not limited significantly by nutrient or trace element requirements. To determine why one novel hyperthermophilic methanogen from our field site (Methanocaldococcus bathoardescens) appeared to prefer high levels of nitrogen when grown in the lab, its genome was examined for nitrogen assimilation-related genes. In the laboratory, the growth energies of Methanocaldococcus and Methanothermococcus spp. over their full temperature ranges were measured in order to determine Arrhenius constants for their production of methane. They were also grown in continuous flow chemostat culture to determine their hydrogen limitations at both optimal and sub-optimal temperatures for growth, and the Monod kineticsfor their hydrogen use and methane production were measured. Additionally, the minimum hydrogen and thiosulfate requirements, as well as Monod kinetics, were measured in batch bioreactor culture for a thiosulfate-reducing, hydrogenotrophic, thermophilic Desulfurobacterium sp. isolated from another site on the Juan de Fuca Ridge, the Endeavour Segment, to determine where it might compete with methanogens for hydrogen. Finally, the geochemical and distribution data from Axial Volcano and laboratory-derived kinetic data for thermophilic and hyperthermophilic methanogens were used to create a one-dimensional reactive transport model (RTM) of hydrogenotrophic methanogenesis in the subsurface at Axial Volcano. In this way, the relative dimensions and biomass of methanogens in the subsurface can be predicted without direct sampling. In future, this type of model could be used make predictions about the thermophilic subsurface at other vent locations, as well as expanded to include competition between different types of hydrogenotrophs (rather than just hydrogenotrophic methanogens with different optimum temperatures) and interactions with other organisms, such as hydrogen-producing hyperthermophilic heterotrophs

Representing temporal dependencies in human activity recognition.

Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared over time. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs and consider the temporal dependencies that exist in binary ambient sensor data in order to produce case-based representations. These LSTM approaches are compared to the performance of a selection of baseline classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier

Representing temporal dependencies in smart home activity recognition for health monitoring.

Long term health conditions, such as fall risk, are traditionally diagnosed through testing performed in hospital environments. Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared overtime. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs which consider the temporal dependencies present in the sensor data in order to produce richer representations and improved classification accuracy. The LSTM approaches are compared to the performance of a selection of base line classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier

Monitoring health in smart homes using simple sensors.

We consider use of an ambient sensor network, installed in Smart Homes, to identify low level events taking place which can then be analysed to generate a resident's profile of activities of daily living (ADLs). These ADL profiles are compared to both the resident's typical profile and to known 'risky' profiles to support evidence-based interventions. Human activity recognition to identify ADLs from sensor data is a key challenge, a windowbased representation is compared on four existing datasets. We find that windowing works well, giving consistent performance. We also introduce FITsense, which is building a Smart Home environment to specifically identify increased risk of falls to allow interventions before falls occurs

Spitzer IRS Spectra of Basaltic Asteroids: Preliminary Results

We present preliminary results of a Spitzer program to observe the 5.2--38 micron spectra of small basaltic asteroids using the Spitzer IRS (Infrared Spectrograph). Our targets include members of the dynamical family of the unique large differentiated asteroid 4 Vesta ("Vestoids"), four outer-main-belt basaltic asteroids whose orbits exclude them from originating on 4 Vesta, and the basaltic near-Earth asteroid (NEA) 4055 Magellan. We will compare the compositions and thermophysical properties of the non-Vestoid objects with those of the dynamical vestoids to provide insight on the extent of metal-silicate differentiation on planetsimals during the epoch of planet formation in the early Solar System. As of this writing, spectra of asteroids 10537 (1991 RY16) and 2763 Jeans have been returned. Analysis of these data are ongolng. Observations of 956 Elisa, 2653 Principia, 4215 Kamo, 7472 Kumakiri, and 1459 Magnya have been scheduled and are expected to be available by the time of the DPS meeting. NIR spectra and lightcurves o f the target asteroids are also being observed in support of this program

Effects of maternal caffeine consumption on the breastfed child : a systematic review

Background: Nutrition in the first 1000 days between pregnancy and 24 months of life is critical for child health, and exclusive breastfeeding is promoted as the infant’s best source of nutrition in the first 6 months. Caffeine is a central nervous system stimulant occurring naturally in some foods and used to treat primary apnoea in premature babies. However high caffeine intake can be harmful, and caffeine is transmitted into breastmilk. Aim: To systematically review the evidence on the effects of maternal caffeine consumption during breastfeeding on the breastfed child. Method: A systematic search was conducted to October 2017 in MEDLINE, EMBASE, Web of Science, CINAHL, and Cochrane Library. The British Library catalogue, which covers doctoral theses, was searched and PRISMA guidelines followed. Two reviewers screened for experimental, cohort, or case-control studies and performed independent quality assessment using the Newcastle-Ottawa scale. The main reviewer performed data extraction, checked by the second reviewer. Results: Two cohort, two crossover studies, and one N-of-1 trial were included for narrative synthesis. One crossover and two cohort studies of small sample sizes directly investigated maternal caffeine consumption. No significant effects on 24-hour heart rate, 24-hour sleep time, or frequent night waking of the breastfed child were found. One study found a decreased rate of full breastfeeding at 6 months postpartum. Two studies indirectly investigated caffeine exposure. Maternal chocolate and coffee consumption was associated with increased infant colic, and severe to moderate exacerbation of infant atopic dermatitis. However, whether caffeine was the causal ingredient is questionable. The insufficient and inconsistent evidence available had quality issues impeding conclusions on the effects of maternal caffeine consumption on the breastfed child. Conclusion: Evidence for recommendations on caffeine intake for breastfeeding women is scant, of limited quality and inconclusive. Birth cohort studies investigating the potential positive and negative effects of various levels of maternal caffeine consumption on the breastfed child and breastfeeding mother could improve the knowledge base and allow evidence-based advice for breastfeeding mothers

A primary fish gill cell culture model to assess pharmaceutical uptake and efflux:evidence for passive and facilitated transport

AbstractThe gill is the principle site of xenobiotic transfer to and from the aqueous environment. To replace, refine or reduce (3Rs) the large numbers of fish used in in vivo uptake studies an effective in vitro screen is required that mimics the function of the teleost gill. This study uses a rainbow trout (Oncorhynchus mykiss) primary gill cell culture system grown on permeable inserts, which tolerates apical freshwater thus mimicking the intact organ, to assess the uptake and efflux of pharmaceuticals across the gill. Bidirectional transport studies in media of seven pharmaceuticals (propranolol, metoprolol, atenolol, formoterol, terbutaline, ranitidine and imipramine) showed they were transported transcellularly across the epithelium. However, studies conducted in water showed enhanced uptake of propranolol, ranitidine and imipramine. Concentration-equilibrated conditions without a concentration gradient suggested that a proportion of the uptake of propranolol and imipramine is via a carrier-mediated process. Further study using propranolol showed that its transport is pH-dependent and at very low environmentally relevant concentrations (ngL−1), transport deviated from linearity. At higher concentrations, passive uptake dominated. Known inhibitors of drug transport proteins; cimetidine, MK571, cyclosporine A and quinidine inhibited propranolol uptake, whilst amantadine and verapamil were without effect. Together this suggests the involvement of specific members of SLC and ABC drug transporter families in pharmaceutical transport