Fundamental Studies of Oxygen Electrocatalysis in Alkaline Electrochemical Cells

Until recently the world’s main source of energy has been fossil fuels, such as coal and petroleum. However, these energy sources are polluting our planet, becoming scarce and increasingly inaccessible, and are costly to extract. Therefore, much attention has been directed to harvesting clean, abundant, and renewable energy, such as solar rays and wind. However, the intermittency of solar and wind power generation requires an effective energy buffering solution (aka energy storage) to become efficient and reliable. With high efficiency and energy density, rechargeable batteries and reversible fuel cells are two of the best methods for this purpose. Unfortunately, a broader and deeper implementation of these two technologies is currently hindered by their poor performance, specifically the sluggish electrode kinetics. The overarching objective of this Ph.D. work is to fill this technical and scientific gap by investigating the fundamentals of oxygen electrolysis (oxygen reduction reaction and oxygen evolution reaction) mechanisms of non-noble metal-based oxygen electrode materials operating in alkaline electrochemical cells, such as metal-air batteries. The overall approach employed is two-fold: experimentation and theoretical modeling. The oxygen electrode material studied is a mixture of model perovskite structured complex oxide, La0.6Sr0.4CoO3-δ (LSCO) and Vulcan carbon (XC-72) in different ratios. Standard linear sweep voltammetry (LSV) under rotating disk electrode (RDE) and rotating ring disk electrode (RRDE) is the primary tool used to collect electrochemical data, from which the multiphysics models are validated. A 1-D RDE multiphysics model is first established from multi-step, multi-electron (4 or 2 electron transfer), sequential and parallel elementary electrode reactions in conjunction with a peroxide-involving chemical reaction. The governing equations are derived from basic charge transfer and mass transport theories with appropriate boundary conditions. The model is then validated by the RDE LSV data collected from the LSCO/XC-72 oxygen electrode. The validated model is able to project partial current densities for each elementary electrode reaction considered along with the peroxide production rate of the chemical reaction, which cannot be done by “classical” approaches. The 1-D RDE model is further expanded into a 2-D RRDE model to quantify the peroxide intermediates vs applied potential. The new 2-D model is validated with a glassy carbon electrode and it is found that the addition of a parallel, series 1e- reduction of oxygen, incorporating a superoxide intermediate, is necessary

Statistical properties of thermodynamically predicted RNA secondary structures in viral genomes

By performing a comprehensive study on 1832 segments of 1212 complete genomes of viruses, we show that in viral genomes the hairpin structures of thermodynamically predicted RNA secondary structures are more abundant than expected under a simple random null hypothesis. The detected hairpin structures of RNA secondary structures are present both in coding and in noncoding regions for the four groups of viruses categorized as dsDNA, dsRNA, ssDNA and ssRNA. For all groups hairpin structures of RNA secondary structures are detected more frequently than expected for a random null hypothesis in noncoding rather than in coding regions. However, potential RNA secondary structures are also present in coding regions of dsDNA group. In fact we detect evolutionary conserved RNA secondary structures in conserved coding and noncoding regions of a large set of complete genomes of dsDNA herpesviruses.Comment: 9 pages, 2 figure

Long noncoding RNAs in neuronal-glial fate specification and oligodendrocyte lineage maturation

Background: Long non-protein-coding RNAs (ncRNAs) are emerging as important regulators of cellular differentiation and are widely expressed in the brain.Results: Here we show that many long ncRNAs exhibit dynamic expression patterns during neuronal and oligodendrocyte (OL) lineage specification, neuronal-glial fate transitions, and progressive stages of OL lineage elaboration including myelination. Consideration of the genomic context of these dynamically regulated ncRNAs showed they were part of complex transcriptional loci that encompass key neural developmental protein-coding genes, with which they exhibit concordant expression profiles as indicated by both microarray and in situ hybridization analyses. These included ncRNAs associated with differentiation-specific nuclear subdomains such as Gomafu and Neat1, and ncRNAs associated with developmental enhancers and genes encoding important transcription factors and homeotic proteins. We also observed changes in ncRNA expression profiles in response to treatment with trichostatin A, a histone deacetylase inhibitor that prevents the progression of OL progenitors into post-mitotic OLs by altering lineage-specific gene expression programs.Conclusion: This is the first report of long ncRNA expression in neuronal and glial cell differentiation and of the modulation of ncRNA expression by modification of chromatin architecture. These observations explicitly link ncRNA dynamics to neural stem cell fate decisions, specification and epigenetic reprogramming and may have important implications for understanding and treating neuropsychiatric diseases

Combating escalating harms associated with pharmaceutical opioid use in Australia: The POPPY II study protocol

© Author(s) (or their employer(s)) 2018. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. Introduction Opioid prescribing has increased 15-fold in Australia in the past two decades, alongside increases in a range of opioid-related harms such as opioid dependence and overdose. However, despite concerns about increasing opioid use, extramedical use and harms, there is a lack of population-level evidence about the drivers of long-term prescribed opioid use, dependence, overdose and other harms. Methods and analysis We will form a cohort of all adult residents in New South Wales (NSW), Australia, who initiated prescribed opioids from 2002 using Pharmaceutical Benefits Scheme dispensing records. This cohort will be linked to a wide range of other datasets containing information on sociodemographic and clinical characteristics, health service use and adverse outcomes (eg, opioid dependence and non-fatal and fatal overdose). Analyses will initially examine patterns and predictors of prescribed opioid use and then apply regression and survival analysis to quantify the risks and risk factors of adverse outcomes associated with prescribed opioid use. Ethics and dissemination This study has received full ethical approval from the Australian Institute of Health and Welfare Ethics Committee, the NSW Population and Health Services Research Committee and the ACT Health Human Research Ethics Committee. This will be the largest postmarketing surveillance study of prescribed opioids undertaken in Australia, linking exposure and outcomes and examining risk factors for adverse outcomes of prescribed opioids. As such, this work has important translational promise, with direct relevance to regulatory authorities and agencies worldwide. Project findings will be disseminated at scientific conferences and in peer-reviewed journals. We will also conduct targeted dissemination with policy makers, professional bodies and peak bodies in the pain, medicine and addiction fields through stakeholder workshops and advisory groups. Results will be reported in accordance with the REporting of studies Conducted using Observational Routinely collected Data (RECORD) Statement

Receptor Quaternary Organization Explains G Protein-Coupled Receptor Family Structure.

The organization of Rhodopsin-family G protein-coupled receptors (GPCRs) at the cell surface is controversial. Support both for and against the existence of dimers has been obtained in studies of mostly individual receptors. Here, we use a large-scale comparative study to examine the stoichiometric signatures of 60 receptors expressed by a single human cell line. Using bioluminescence resonance energy transfer- and single-molecule microscopy-based assays, we found that a relatively small fraction of Rhodopsin-family GPCRs behaved as dimers and that these receptors otherwise appear to be monomeric. Overall, the analysis predicted that fewer than 20% of ∼700 Rhodopsin-family receptors form dimers. The clustered distribution of the dimers in our sample and a striking correlation between receptor organization and GPCR family size that we also uncover each suggest that receptor stoichiometry might have profoundly influenced GPCR expansion and diversification

The Accelerating Growth of Online Tagging Systems

Research on the growth of online tagging systems not only is interesting in its own right, but also yields insights for website management and semantic web analysis. Traditional models that describing the growth of online systems can be divided between linear and nonlinear versions. Linear models, including the BA model (Brabasi and Albert, 1999), assume that the average activity of users is a constant independent of population. Hence the total activity is a linear function of population. On the contrary, nonlinear models suggest that the average activity is affected by the size of the population and the total activity is a nonlinear function of population. In the current study, supporting evidences for the nonlinear growth assumption are obtained from data on Internet users' tagging behavior. A power law relationship between the number of new tags (F) and the population (P), which can be expressed as F ~ P ^ gamma (gamma > 1), is found. I call this pattern accelerating growth and find it relates the to time-invariant heterogeneity in individual activities. I also show how a greater heterogeneity leads to a faster growth.Comment: 8 pages, 3 figure

Exploiting Oxytricha trifallax nanochromosomes to screen for non-coding RNA genes

We took advantage of the unusual genomic organization of the ciliate Oxytricha trifallax to screen for eukaryotic non-coding RNA (ncRNA) genes. Ciliates have two types of nuclei: a germ line micronucleus that is usually transcriptionally inactive, and a somatic macronucleus that contains a reduced, fragmented and rearranged genome that expresses all genes required for growth and asexual reproduction. In some ciliates including Oxytricha, the macronuclear genome is particularly extreme, consisting of thousands of tiny ‘nanochromosomes’, each of which usually contains only a single gene. Because the organism itself identifies and isolates most of its genes on single-gene nanochromosomes, nanochromosome structure could facilitate the discovery of unusual genes or gene classes, such as ncRNA genes. Using a draft Oxytricha genome assembly and a custom-written protein-coding genefinding program, we identified a subset of nanochromosomes that lack any detectable protein-coding gene, thereby strongly enriching for nanochromosomes that carry ncRNA genes. We found only a small proportion of non-coding nanochromosomes, suggesting that Oxytricha has few independent ncRNA genes besides homologs of already known RNAs. Other than new members of known ncRNA classes including C/D and H/ACA snoRNAs, our screen identified one new family of small RNA genes, named the Arisong RNAs, which share some of the features of small nuclear RNAs

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments