Dynamic scaling approach to study time series fluctuations

We propose a new approach for properly analyzing stochastic time series by mapping the dynamics of time series fluctuations onto a suitable nonequilibrium surface-growth problem. In this framework, the fluctuation sampling time interval plays the role of time variable, whereas the physical time is treated as the analog of spatial variable. In this way we found that the fluctuations of many real-world time series satisfy the analog of the Family-Viscek dynamic scaling ansatz. This finding permits to use the powerful tools of kinetic roughening theory to classify, model, and forecast the fluctuations of real-world time series.Comment: 25 pages, 7 figures, 1 tabl

Models of RNA Interaction from Experimental Datasets: Framework of Resilience

Resilience is a network property of systems responding under stress, which for biomedicine correlates to chronic or acute insults. Current need exists for models and algorithms to study whole transcriptome differences between tissues and disease states to understand resilience. Goal of this effort is to interpret cellular transcription in a dynamic system biology framework of RNA molecules forming an information structure with regulatory properties acting on individual transcripts. We develop and evaluate a bioinformatics framework based on information theory that utilizes RNA expression data to create a whole transcriptome model of interaction that could lead to the discovery of new biological control mechanisms. This addresses a fundamental question as to why transcription yields such a small fraction of protein products. We focus on a transformative concept that individual transcripts collectively form an “information cloud” of sequence words, which for some genes may have significant regulatory impact. Extending the concept of cis‐ and trans‐regulation, we propose to search for RNAs that are modulated by interactions with the transcriptome cloud and calling such examples nebula regulation. This framework has implications as a paradigm change for RNA regulation and provides a deeper understanding of nucleotide sequence structure and ‐omic language meaning

Anomalous roughness with system size dependent local roughness exponent

We note that in a system far from equilibrium the interface roughening may depend on the system size which plays the role of control parameter. To detect the size effect on the interface roughness, we study the scaling properties of rough interfaces formed in paper combustion experiments. Using paper sheets of different width \lambda L, we found that the turbulent flame fronts display anomalous multi-scaling characterized by non universal global roughness exponent \alpha and the system size dependent spectrum of local roughness exponents,\xi_q, whereas the burning fronts possess conventional multi-affine scaling. The structure factor of turbulent flame fronts also exhibit unconventional scaling dependence on \lambda These results are expected to apply to a broad range of far from equilibrium systems, when the kinetic energy fluctuations exceed a certain critical value.Comment: 33 pages, 16 figure

Correlation between nucleotide composition and folding energy of coding sequences with special attention to wobble bases

Background: The secondary structure and complexity of mRNA influences its accessibility to regulatory molecules (proteins, micro-RNAs), its stability and its level of expression. The mobile elements of the RNA sequence, the wobble bases, are expected to regulate the formation of structures encompassing coding sequences. Results: The sequence/folding energy (FE) relationship was studied by statistical, bioinformatic methods in 90 CDS containing 26,370 codons. I found that the FE (dG) associated with coding sequences is significant and negative (407 kcal/1000 bases, mean +/- S.E.M.) indicating that these sequences are able to form structures. However, the FE has only a small free component, less than 10% of the total. The contribution of the 1st and 3rd codon bases to the FE is larger than the contribution of the 2nd (central) bases. It is possible to achieve a ~ 4-fold change in FE by altering the wobble bases in synonymous codons. The sequence/FE relationship can be described with a simple algorithm, and the total FE can be predicted solely from the sequence composition of the nucleic acid. The contributions of different synonymous codons to the FE are additive and one codon cannot replace another. The accumulated contributions of synonymous codons of an amino acid to the total folding energy of an mRNA is strongly correlated to the relative amount of that amino acid in the translated protein. Conclusion: Synonymous codons are not interchangable with regard to their role in determining the mRNA FE and the relative amounts of amino acids in the translated protein, even if they are indistinguishable in respect of amino acid coding.Comment: 14 pages including 6 figures and 1 tabl

Using a neural network to backtranslate amino acid sequences

A neural network (NN) was trained on amino and nucleic acid sequences to test the NN's ability to predict a nucleic acid sequence given only an amino acid sequence. A multi-layer backpropagation network of one hidden layer with 5 to 9 neurons was used. Different network configurations were used with varying numbers of input neurons to represent amino acids, while a constant representation was used for the output layer representing nucleic acids. In the best-trained network, 93% of the overall bases, 85% of the degenerate bases, and 100% of the fixed bases were correctly predicted from randomly selected test sequences. The training set was composed of 60 human sequences in a window of 10 to 25 codons at the coding sequence start site. Different NN configurations involving the encoding of amino acids under increasing window sizes were evaluated to predict the behavior of the NN with a significantly larger training set. This genetic data analysis effort will assist in understanding human gene structure. Benefits include computational tools that could predict more reliably the backtranslation of amino acid sequences useful for Degenerate PCR cloning, and may assist the identification of human gene coding sequences (CDS) from open reading frames in DNA databases

STAT3 dysregulation in mature T and NK cell lymphomas

T cell lymphomas comprise a distinct class of non-Hodgkin’s lymphomas, which include mature T and natural killer (NK) cell neoplasms. While each malignancy within this group is characterized by unique clinicopathologic features, dysregulation in the Janus tyrosine family of kinases/Signal transducer and activator of transcription (JAK/STAT) signaling pathway, specifically aberrant STAT3 activation, is a common feature among these lymphomas. The mechanisms driving dysregulation vary among T cell lymphoma subtypes and include activating mutations in upstream kinases or STAT3 itself, formation of oncogenic kinases which drive STAT3 activation, loss of negative regulators of STAT3, and the induction of a pro-tumorigenic inflammatory microenvironment. Constitutive STAT3 activation has been associated with the expression of targets able to increase pro-survival signals and provide malignant fitness. Patients with dysregulated STAT3 signaling tend to have inferior clinical outcomes, which underscores the importance of STAT3 signaling in malignant progression. Targeting of STAT3 has shown promising results in pre-clinical studies in T cell lymphoma lines, ex-vivo primary malignant patient cells, and in mouse models of disease. However, targeting this pleotropic pathway in patients has proven difficult. Here we review the recent contributions to our understanding of the role of STAT3 in T cell lymphomagenesis, mechanisms driving STAT3 activation in T cell lymphomas, and current efforts at targeting STAT3 signaling in T cell malignancies

Technetium Waste Form Development - Progress Report

Analytical electron microscopy using SEM and TEM has been used to analyze a ~5 g. ingot with composition 71.3 wt% 316SS-5.3 wt% Zr-13.2 wt% Mo-4.0 wt% Rh-6.2 wt% Re prepared at the Idaho National Laboratory. Four phase fields have been identified two of which are lamellar eutectics, with a fifth possibly present. A Zr rich phase was found distributed as fine precipitate, ~10µm in diameter, often coating large cavities. A Mo-Fe-Re-Cr lamellar eutectic phase field appears as blocky regions ~30µm in diameter, surrounded by a Fe-Mo-Cr lamellar eutectic phase field, and that in turn is surrounded by a Zr-Fe-Rh-Mo-Ni phase field. The eutectic phase separation reactions are different. The Mo-Fe-Re-Cr lamellar eutectic appears a result of austenitic steel forming at lower volume fraction within an Mo-Fe-Re intermetallic phase, whereas the Fe-Mo-Cr lamellar eutectic may be a result of the same intermetallic phase forming within a ferritic steel phase. Cavitation may have arisen either as a result of bubbles, or from loss of equiaxed particles during specimen preparation

Towards Informatics-Driven Design of Nuclear Waste Forms

Informatics-driven approaches, such as machine learning and sequential experimental design, have shown the potential to drastically impact next-generation materials discovery and design. In this perspective, we present a few guiding principles for applying informatics-based methods towards the design of novel nuclear waste forms. We advocate for adopting a system design approach, and describe the effective usage of data-driven methods in every stage of such a design process. We demonstrate how this approach can optimally leverage physics-based simulations, machine learning surrogates, and experimental synthesis and characterization, within a feedback-driven closed-loop sequential learning framework. We discuss the importance of incorporating domain knowledge into the representation of materials, the construction and curation of datasets, the development of predictive property models, and the design and execution of experiments. We illustrate the application of this approach by successfully designing and validating Na- and Nd-containing phosphate-based ceramic waste forms. Finally, we discuss open challenges in such informatics-driven workflows and present an outlook for their widespread application for the cleanup of nuclear wastes.Comment: 35 pages, 9 figures, 2 table