EPA GLNPO Update: GLRPPR & GLNPO Partnership

Program updates for EPA's Great Lakes National Program Office and the Great Lakes Regional Pollution Prevention Roundtable.Ope

Low energy atomic collision with dipole interactions

We apply quantum defect theory to study low energy ground state atomic collisions including aligned dipole interactions such as those induced by an electric field. Our results show that coupled even ($l$) relative orbital angular momentum partial wave channels exhibit shape resonance structures while odd ($l$) channels do not. We analyze and interpret these resonances within the framework of multichannel quantum defect theory (MQDT).Comment: 27 pages, 17 figures, an inadvertent typo correcte

Expression of Human Frataxin Is Regulated by Transcription Factors SRF and TFAP2

Friedreich ataxia is an autosomal recessive neurodegenerative disease caused by reduced expression levels of the frataxin gene (FXN) due to expansion of triplet nucleotide GAA repeats in the first intron of FXN. Augmentation of frataxin expression levels in affected Friedreich ataxia patient tissues might substantially slow disease progression.We utilized bioinformatic tools in conjunction with chromatin immunoprecipitation and electrophoretic mobility shift assays to identify transcription factors that influence transcription of the FXN gene. We found that the transcription factors SRF and TFAP2 bind directly to FXN promoter sequences. SRF and TFAP2 binding sequences in the FXN promoter enhanced transcription from luciferase constructs, while mutagenesis of the predicted SRF or TFAP2 binding sites significantly decreased FXN promoter activity. Further analysis demonstrated that robust SRF- and TFAP2-mediated transcriptional activity was dependent on a regulatory element, located immediately downstream of the first FXN exon. Finally, over-expression of either SRF or TFAP2 significantly increased frataxin mRNA and protein levels in HEK293 cells, and frataxin mRNA levels were also elevated in SH-SY5Y cells and in Friedreich ataxia patient lymphoblasts transfected with SRF or TFAP2.We identified two transcription factors, SRF and TFAP2, as well as an intronic element encompassing EGR3-like sequence, that work together to regulate expression of the FXN gene. By providing new mechanistic insights into the molecular factors influencing frataxin expression, our results should aid in the discovery of new therapeutic targets for the treatment of Friedreich ataxia

Bound states of the Dirac equation for the PT-symmetric generalized Hulthen potential by the Nikiforov-Uvarov method

The one-dimensional Dirac equation is solved for the PT-symmetric generalized Hulthen potential. The Nikiforov-Uvarov method which is based on solving the second-order linear differential equations by reduction to a generalized equation of hypergeometric type is used to obtain exact energy eigenvalues and corresponding eigenfunctions.Comment: 18 pages including 4 figures,to be published in Phys.Lett.

Defining the Plasticity of Transcription Factor Binding Sites by Deconstructing DNA Consensus Sequences: The PhoP-Binding Sites among Gamma/Enterobacteria

Transcriptional regulators recognize specific DNA sequences. Because these sequences are embedded in the background of genomic DNA, it is hard to identify the key cis-regulatory elements that determine disparate patterns of gene expression. The detection of the intra- and inter-species differences among these sequences is crucial for understanding the molecular basis of both differential gene expression and evolution. Here, we address this problem by investigating the target promoters controlled by the DNA-binding PhoP protein, which governs virulence and Mg2+ homeostasis in several bacterial species. PhoP is particularly interesting; it is highly conserved in different gamma/enterobacteria, regulating not only ancestral genes but also governing the expression of dozens of horizontally acquired genes that differ from species to species. Our approach consists of decomposing the DNA binding site sequences for a given regulator into families of motifs (i.e., termed submotifs) using a machine learning method inspired by the “Divide & Conquer” strategy. By partitioning a motif into sub-patterns, computational advantages for classification were produced, resulting in the discovery of new members of a regulon, and alleviating the problem of distinguishing functional sites in chromatin immunoprecipitation and DNA microarray genome-wide analysis. Moreover, we found that certain partitions were useful in revealing biological properties of binding site sequences, including modular gains and losses of PhoP binding sites through evolutionary turnover events, as well as conservation in distant species. The high conservation of PhoP submotifs within gamma/enterobacteria, as well as the regulatory protein that recognizes them, suggests that the major cause of divergence between related species is not due to the binding sites, as was previously suggested for other regulators. Instead, the divergence may be attributed to the fast evolution of orthologous target genes and/or the promoter architectures resulting from the interaction of those binding sites with the RNA polymerase

Bio-inspired computation: where we stand and what's next

In recent years, the research community has witnessed an explosion of literature dealing with the adaptation of behavioral patterns and social phenomena observed in nature towards efficiently solving complex computational tasks. This trend has been especially dramatic in what relates to optimization problems, mainly due to the unprecedented complexity of problem instances, arising from a diverse spectrum of domains such as transportation, logistics, energy, climate, social networks, health and industry 4.0, among many others. Notwithstanding this upsurge of activity, research in this vibrant topic should be steered towards certain areas that, despite their eventual value and impact on the field of bio-inspired computation, still remain insufficiently explored to date. The main purpose of this paper is to outline the state of the art and to identify open challenges concerning the most relevant areas within bio-inspired optimization. An analysis and discussion are also carried out over the general trajectory followed in recent years by the community working in this field, thereby highlighting the need for reaching a consensus and joining forces towards achieving valuable insights into the understanding of this family of optimization techniques

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist