Uniform electron gases

We show that the traditional concept of the uniform electron gas (UEG) --- a homogeneous system of finite density, consisting of an infinite number of electrons in an infinite volume --- is inadequate to model the UEGs that arise in finite systems. We argue that, in general, a UEG is characterized by at least two parameters, \textit{viz.} the usual one-electron density parameter $\rho$ and a new two-electron parameter $\eta$. We outline a systematic strategy to determine a new density functional $E(\rho,\eta)$ across the spectrum of possible $\rho$ and $\eta$ values.Comment: 8 pages, 2 figures, 5 table

Random-phase approximation and its applications in computational chemistry and materials science

The random-phase approximation (RPA) as an approach for computing the electronic correlation energy is reviewed. After a brief account of its basic concept and historical development, the paper is devoted to the theoretical formulations of RPA, and its applications to realistic systems. With several illustrating applications, we discuss the implications of RPA for computational chemistry and materials science. The computational cost of RPA is also addressed which is critical for its widespread use in future applications. In addition, current correction schemes going beyond RPA and directions of further development will be discussed.Comment: 25 pages, 11 figures, published online in J. Mater. Sci. (2012

Statistical Analysis of Molecular Signal Recording

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.United States. Defense Advanced Research Projects Agency. Living Foundries ProgramGoogle (Firm)New York Stem Cell Foundation. Robertson Neuroscience Investigator AwardNational Institutes of Health (U.S.) (EUREKA Award 1R01NS075421)National Institutes of Health (U.S.) (Transformative R01 1R01GM104948)National Institutes of Health (U.S.) (Single Cell Grant 1 R01 EY023173)National Institutes of Health (U.S.) (Grant 1R01DA029639)National Institutes of Health (U.S.) (Grant 1R01NS067199)National Science Foundation (U.S.) (CAREER Award CBET 1053233)National Science Foundation (U.S.) (Grant EFRI0835878)National Science Foundation (U.S.) (Grant DMS1042134)Paul G. Allen Family Foundation (Distinguished Investigator in Neuroscience Award

Deep sequencing reveals as-yet-undiscovered small RNAs in Escherichia coli

<p>Abstract</p> <p>Background</p> <p>In <it>Escherichia coli</it>, approximately 100 regulatory small RNAs (sRNAs) have been identified experimentally and many more have been predicted by various methods. To provide a comprehensive overview of sRNAs, we analysed the low-molecular-weight RNAs (< 200 nt) of <it>E. coli </it>with deep sequencing, because the regulatory RNAs in bacteria are usually 50-200 nt in length.</p> <p>Results</p> <p>We discovered 229 novel candidate sRNAs (≥ 50 nt) with computational or experimental evidence of transcription initiation. Among them, the expression of seven intergenic sRNAs and three <it>cis</it>-antisense sRNAs was detected by northern blot analysis. Interestingly, five novel sRNAs are expressed from prophage regions and we note that these sRNAs have several specific characteristics. Furthermore, we conducted an evolutionary conservation analysis of the candidate sRNAs and summarised the data among closely related bacterial strains.</p> <p>Conclusions</p> <p>This comprehensive screen for <it>E. coli </it>sRNAs using a deep sequencing approach has shown that many as-yet-undiscovered sRNAs are potentially encoded in the <it>E. coli </it>genome. We constructed the <it>Escherichia coli </it>Small RNA Browser (ECSBrowser; <url>http://rna.iab.keio.ac.jp/</url>), which integrates the data for previously identified sRNAs and the novel sRNAs found in this study.</p

Salicornia ramosissima population dynamics and tolerance of salinity

Abstract Field and greenhouse studies have been conducted to clarify aspects of population dynamics and NaCl tolerance of Salicornia ramosissima J. Woods. Two populations, Varela and Verdemilho, were monitored in the field during two consecutive life cycles and aspects of their morphology and density were recorded monthly. In the laboratory seedlings were exposed to different salinity for 10 weeks and growth and mortality rate were recorded weekly. The growth of the populations differed significantly, possibly because of the different salinities of the two sampling sites and/or genetic adaptations of the two populations to the environmental conditions. The absence of a significant correlation between sediment salinity and stem elongation suggested, however, that salinity, alone was not responsible for the differences observed and was possibly associated with other factors, because of nutritional, edaphic, and microclimatic conditions. S. ramosissima did not develop well in conditions of elevated or moderate salinity; its growth was optimum at low salinity. Optimum development of S. ramosissima may, nevertheless, depend on the total number of large seeds in a population seed bank, because of their greater success in germination and germinability under stress conditions than small seeds

Inferring decoding strategies from choice probabilities in the presence of correlated variability

The activity of cortical neurons in sensory areas covaries with perceptual decisions, a relationship that is often quantified by choice probabilities. Although choice probabilities have been measured extensively, their interpretation has remained fraught with difficulty. We derive the mathematical relationship between choice probabilities, read-out weights and correlated variability in the standard neural decision-making model. Our solution allowed us to prove and generalize earlier observations on the basis of numerical simulations and to derive new predictions. Notably, our results indicate how the read-out weight profile, or decoding strategy, can be inferred from experimentally measurable quantities. Furthermore, we developed a test to decide whether the decoding weights of individual neurons are optimal for the task, even without knowing the underlying correlations. We confirmed the practicality of our approach using simulated data from a realistic population model. Thus, our findings provide a theoretical foundation for a growing body of experimental results on choice probabilities and correlations