Algae Living in Salamanders, Friend or Foe?

Roughly speaking, our bodies use energy from the sun, but we can\u27t use sunlight directly. Instead, plants and algae collect sunlight and store it as chemical energy through the process of photosynthesis. We can access that fuel directly when we eat plants, or indirectly when we eat other animals that eat plants. However, in some invertebrate animals (those without a backbone) the relationships to algae are more intimate. Tiny single-celled algal symbionts can actually live inside the cells of living corals and small animals like hydra that live in water. The algae live in a safe environment inside animal cells and are provided with building block materials to function. They use sunlight to convert the building block materials into larger molecules to store energy and build cellular structures. At the same time some of that stored solar energy is directly transferred to the host animal, allowing it to live in otherwise nutrient poor environments. Thus the algae and their hosts depend on one another to live and thrive. These mutually beneficial relationships are called photosymbioses. [excerpt

Feedback Control of Low Dimensional Models of Transition to Turbulence

The problem of controlling or delaying transition to turbulence in shear flows has been the subject of numerous papers over the past twenty years. This period has seen the development of several low dimensional models for parallel shear flows in an attempt to explain the failure of classical linear hydrodynamic stability theory to correctly predict transition. In recent years, ideas from robust control theory have been employed to attack this problem. In this paper we use these models to develop a scenario for transition that employs both classical bifurcation theory and robust control theory. In addition, we present numerical results to illustrate the ideas and to show how feedback can be used to delay transition. We close with a specific conjecture and discuss some previous results along this line

Transciptome Analysis Illuminates the Nature of the Intracellular Interaction in a Vertebrate-Algal Symbiosis

During embryonic development, cells of the green alga Oophila amblystomatis enter cells of the salamander Ambystoma maculatum forming an endosymbiosis. Here, using de novo dual-RNA seq, we compared the host salamander cells that harbored intracellular algae to those without algae and the algae inside the animal cells to those in the egg capsule. This two-by-two-way analysis revealed that intracellular algae exhibit hallmarks of cellular stress and undergo a striking metabolic shift from oxidative metabolism to fermentation. Culturing experiments with the alga showed that host glutamine may be utilized by the algal endosymbiont as a primary nitrogen source. Transcriptional changes in salamander cells suggest an innate immune response to the alga, with potential attenuation of NF-κB, and metabolic alterations indicative of modulation of insulin sensitivity. In stark contrast to its algal endosymbiont, the salamander cells did not exhibit major stress responses, suggesting that the host cell experience is neutral or beneficial

Co-Cultures of Oophila Amblystomatis Between Ambystoma Maculatum and Ambystoma Gracile Hosts Show Host-Symbiont Fidelity

A unique symbiosis occurs between embryos of the spotted salamander (Ambystoma maculatum) and a green alga (Oophila amblystomatis). Unlike most vertebrate host-symbiont relationships, which are ectosymbiotic, A. maculatum exhibits both an ecto- and an endo-symbiosis, where some of the green algal cells living inside egg capsules enter embryonic tissues as well as individual salamander cells. Past research has consistently categorized this symbiosis as a mutualism, making this the first example of a “beneficial” microbe entering vertebrate cells. Another closely related species of salamander, Ambystoma gracile, also harbors beneficial Oophila algae in its egg capsules. However, our sampling within the A. gracile range consistently shows this to be a strict ectosymbiotic interaction—with no sign of tissue or presumably cellular entry. In this study we swapped cultured algae derived from intracapsular fluid of different salamander hosts to test the fidelity of tissue entry in these symbioses. Both A. maculatum and A. gracile embryos were raised in cultures with their own algae or algae cultured from the other host. Under these in vitro culture conditions A. maculatum algae will enter embryonic A. maculatum tissues. Additionally, although at a much lower frequency, A. gracile derived algae will also enter A. maculatum host tissues. However, neither Oophila strain enters A. gracile hosts in these co-culture conditions. These data reveal a potential host-symbiont fidelity that allows the unique endosymbiosis to occur in A. maculatum, but not in A. gracile. However, preliminary trials in our study found that persistent endogenous A. maculatum algae, as opposed to the cultured algae used in subsequent trials, enters host tissues at a higher frequency. An analysis of previously published Oophila transcriptomes revealed dramatic differences in gene expression between cultured and intracapsular Oophila. These include a suite of genes in protein and cell wall synthesis, photosynthesis, central carbon metabolism suggesting the intracapsular algae are assimilating ammonia for nitrogen metabolism and may be undergoing a life-cycle transition. Further refinements of these co-culture conditions could help determine physiological differences between cultured and endogenous algae, as well as rate-limiting cues provided for the alga by the salamander

Extended BEG Model of Monhalogenated Methanes Physisorbed on Ionic Crystals

The 2D dielectric phases and phase transitions of adsorbed dipolar molecules are modeled using a dilute spin-one Ising model. This model is studied in the Blume–Emery–Griffiths formalism, using a mean-field approximation, where the interaction parameters are uniquely determined from the system interaction energies using an averaging procedure. The model is applied to four monhalogenated methane species physisorbed on MgO(1 0 0) and NaCl(1 0 0) surfaces using previous experimental and theoretical studies to estimate the interaction energy parameters. We find that temperature- and coverage-dependent antiferroelectric to ferroelectric, coverage-dependent ferroelectric up to ferroelectric down, reentrant ferroelectric to ferrielectric, and order-disorder dipole phase transitions can occur. Phase diagrams based on this model are presented

Substructure in clusters containing wide-angle tailed radio galaxies. I. New redshifts

We present new redshifts and positions for 635 galaxies in nine rich clusters containing Wide-Angle Tailed (WAT) radio galaxies. Combined with existing data, we now have a sample of 18 WAT-containing clusters with more than 10 redshifts. This sample contains a substantial portion of the WAT clusters in the VLA 20 cm survey of Abell clusters, including 75% of WAT clusters in the complete survey (z0.09. It is a representative sample which should not contain biases other than selection by radio morphology. We graphically present the new data using histograms and sky maps. A semi-automated procedure is used to search for emission lines in the spectra in order to add and verify galaxy redshifts. We find that the average apparent fraction of emission line galaxies is about 9% in both the clusters and the field. We investigate the magnitude completeness of our redshift surveys with CCD data for a test case, Abell 690. This case indicates that our galaxy target lists are deeper than the detection limit of a typical MX exposure, and they are 82% complete down to R=19.0. The importance of the uniformity of the placement of fibers on targets is posited, and we evaluate this in our datasets. We find some cases of non-uniformities which may influence dynamical analyses. A second paper will use this database to look for correlations between the WAT radio morphology and the cluster's dynamical state.Comment: 15 pages, 5 figures, 7 tables. To appear in the Astronomical Journa

Synchrotron X-ray Diffraction of Layering Transitions of Multilayer Nitrogen Physisorbed on Graphite

We use synchrotron x-ray diffraction for structural analysis of the behavior of multilayer nitrogen films physisorbed on graphite foam. We provide structural information and concentrations of 2D and 3D solid phases at a coverage of Θ = 8 ML (Θ / 1 ML for a %3 x %3 structure) for temperatures from below the bulk α-ß transition temperature [Tα-ß = 34 0.5 K] to above the bulk triple point [Ttp = 63 K]. Our data indicate layering begins near Tα-ß, with subsequent layering occurring as the temperature is raised; all bulk nitrogen forms disordered film layers by 48 K at Θ = 8 ML. Our results are consistent with ellipsometry studies of nitrogen on HOPG which found multilayer nitrogen on single crystal graphite to undergo a series of layering transitions above the bulk nitrogen α-ß structural transition.[U.G. Volkmann, and K. Knorr, Phys. Rev. Lett. 1991, 66, 473.] The effect of adsorption on a graphite foam substrate, which results in capillary condensation and finite size effects, is limited to a broadening and overlap of the discrete transition temperatures observed on a single crystal substrate. A phase diagram for coverages above 2 ML is proposed, summarizing this and previous work

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey\u27s 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score \u3c 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret

The Effect Of Image Resolution On Fluid Flow Simulations In Porous Media

Realistic simulations of flow in porous media are dependent upon having a three-dimensional, high resolution image of pore structure which is difficult to obtain. So, we ask the question, "How fine a resolution is necessary to adequately model flow in porous media?" To find the answer, we take a 7.5 p,m resolution image and coarsen it to five different resolutions. Lattice gas simulations are performed on each image. From the simulation results, we observe changes in permeability and velocity fields as the resolution is altered. The results show permeability varies by a factor of 5 over the resolution range. Flow paths change as the resolution is changed. We also find that the image processing has a large impact on the outcome of the simulations.Massachusetts Institute of Technology. Borehole Acoustics and Logging ConsortiumMassachusetts Institute of Technology. Earth Resources Laboratory. Reservoir Delineation Consortiu