Comparative Dissimilation of Xylose and Glucose by Escherichia coli and Citrobacter anindolicum

The dissimilative action of Escherichia coli, Citrobacter anindolicum and various organisms of the intermediate groups on xylose and on dextrose was studied under comparable conditions with the aim of postulating a mechanism of the breakdown of the xylose molecule. It was found in many cases that there were significant differences in the ratios of the end products obtained from the two sugars. The products found were H2, CO2, formic, acetic, lactic, and succinic acids, and ethyl alcohol. Acetaldehyde could be isolated by means of sodium bisulphite during the fermentative process

Lorenz gauge gravitational self-force calculations of eccentric binaries using a frequency domain procedure

We present an algorithm for calculating the metric perturbations and gravitational self-force for extreme-mass-ratio inspirals (EMRIs) with eccentric orbits. The massive black hole is taken to be Schwarzschild and metric perturbations are computed in Lorenz gauge. The perturbation equations are solved as coupled systems of ordinary differential equations in the frequency domain. Accurate local behavior of the metric is attained through use of the method of extended homogeneous solutions and mode-sum regularization is used to find the self-force. We focus on calculating the self-force with sufficient accuracy to ensure its error contributions to the phase in a long term orbital evolution will be $\delta\Phi \lesssim 10^{-2}$ radians. This requires the orbit-averaged force to have fractional errors $\lesssim 10^{-8}$ and the oscillatory part of the self-force to have errors $\lesssim 10^{-3}$ (a level frequently easily exceeded). Our code meets this error requirement in the oscillatory part, extending the reach to EMRIs with eccentricities of $e \lesssim 0.8$, if augmented by use of fluxes for the orbit-averaged force, or to eccentricities of $e \lesssim 0.5$ when used as a stand-alone code. Further, we demonstrate accurate calculations up to orbital separations of $a \simeq 100 M$, beyond that required for EMRI models and useful for comparison with post-Newtonian theory. Our principal developments include (1) use of fully constrained field equations, (2) discovery of analytic solutions for even-parity static modes, (3) finding a pre-conditioning technique for outer homogeneous solutions, (4) adaptive use of quad-precision and (5) jump conditions to handle near-static modes, and (6) a hybrid scheme for high eccentricities

Bryozoa from Chesapeake Bay

Author Institution: Ohio State University, Columbus, Ohi

Some Common Misconceptions of Evolution

Author Institution: Department of Zoology and Entomology, Ohio State Universit

Evaluating the role of bacterial diversity in supporting soil ecosystem functions under anthropogenic stress

Ecosystem functions and services are under threat from anthropogenic global change at a planetary scale. Microorganisms are the dominant drivers of nearly all ecosystem functions and therefore ecosystem-scale responses are dependent on responses of resident microbial communities. However, the specific characteristics of microbial communities that contribute to ecosystem stability under anthropogenic stress are unknown. We evaluated bacterial drivers of ecosystem stability by generating wide experimental gradients of bacterial diversity in soils, applying stress to the soils, and measuring responses of several microbial-mediated ecosystem processes, including C and N cycling rates and soil enzyme activities. Some processes (e.g., C mineralization) exhibited positive correlations with bacterial diversity and losses of diversity resulted in reduced stability of nearly all processes. However, comprehensive evaluation of all potential bacterial drivers of the processes revealed that bacterial α diversity per se was never among the most important predictors of ecosystem functions. Instead, key predictors included total microbial biomass, 16S gene abundance, bacterial ASV membership, and abundances of specific prokaryotic taxa and functional groups (e.g., nitrifying taxa). These results suggest that bacterial α diversity may be a useful indicator of soil ecosystem function and stability, but that other characteristics of bacterial communities are stronger statistical predictors of ecosystem function and better reflect the biological mechanisms by which microbial communities influence ecosystems. Overall, our results provide insight into the role of microorganisms in supporting ecosystem function and stability by identifying specific characteristics of bacterial communities that are critical for understanding and predicting ecosystem responses to global change