Dielectronic recombination of ground-state and metastable Li+ ions

Dielectronic recombination has been investigated for Delta n = 1 resonances of ground-state Li+(1s(2)) and for Delta n = 0 resonances of metastable Li (+) (1s2s S-3). The ground-state spectrum shows three prominent transitions between 53 and 64 eV, while the metastable spectrum exhibits many transitions with energies

Prognostic significance of combined MN1, ERG, BAALC, and EVI1 (MEBE) expression in patients with myelodysplastic syndromes

Overexpression of MN1, ERG, BAALC, and EVI1 (MEBE) genes in cytogenetically normal acute myeloid leukemia (AML) patients is associated with poor prognosis, but their prognostic effect in patients with myelodysplastic syndromes (MDS) has not been studied systematically. Expression data of the four genes from 140 MDS patients were combined in an additive score, which was validated in an independent patient cohort of 110 MDS patients. A high MEBE score, defined as high expression of at least two of the four genes, predicted a significantly shorter overall survival (OS) (HR 2.29, 95 % CI 1.3-4.09, P?=?.005) and time to AML progression (HR 4.83, 95 % CI 2.01-11.57, P?

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

Altered cofactor binding affects stability and activity of human UDP-galactose 4′-epimerase: Implications for type III galactosemia

Deficiency of UDP-galactose 4'-epimerase is implicated in type III galactosemia. Two variants, p.K161N-hGALE and p.D175N-hGALE, have been previously found in combination with other alleles in patients with a mild form of the disease. Both variants were studied in vivo and in vitro and showed different levels of impairment. p.K161N-hGALE was severely impaired with substantially reduced enzymatic activity, increased thermal stability, reduced cofactor binding and no ability to rescue the galactose-sensitivity of gal10-null yeast. Interestingly p.K161N-hGALE showed less impairment of activity with UDP-N-acetylgalactosamine in comparison to UDP-galactose. Differential scanning fluorimetry revealed that p.K161N-hGALE was more stable than the wild-type protein and only changed stability in the presence of UDP-N-acetylglucosamine and NAD(+). p.D175N-hGALE essentially rescued the galactose-sensitivity of gal10-null yeast, was less stable than the wild-type protein but showed increased stability in the presence of substrates and cofactor. We postulate that p.K161N-hGALE causes its effects by abolishing an important interaction between the protein and the cofactor, whereas p.D175N-hGALE is predicted to remove a stabilizing salt bridge between the ends of two a-helices that contain residues that interact with NAD(+). These results suggest that the cofactor binding is dynamic and that its loss results in significant structural changes that may be important in disease causation.

Mapping stone surface temperature fluctuations: Implications for lichen distribution and biomodification on historic stone surfaces

The exposure of historic stone to processes of lichen-induced surface biomodification is determined, first and foremost, by the bioreceptivity of those surfaces to lichen colonization. As an important component of surface bioreceptivity, spatiotemporal variation in stone surface temperature plays a critical role in the spatial distribution of saxicolous lichen on historic stone structures, especially within seasonally hot environments. The ornate limestone and tufa stairwell of the Monastery of Cartuja (1516), Granada, Spain, exhibits significant aspect-related differences in lichen distribution. Lichen coverage and
diurnal fluctuations in stone surface temperature on the stairwell were monitored and mapped, under anticyclonic conditions in summer and winter, using an infrared thermometer and Geographical Information Systems approach. This research suggests that it is not extreme high surface temperatures that
determine the presence or absence of lichen coverage on stonework. Instead, average stone surface temperatures
over the course of the year seem to play a critical role in determining whether or not surfaces are receptive to lichen colonization and subsequent biomodification. It is inferred that lichen, capable of surviving extreme surface temperatures during the Mediterranean summer in an ametabolic state, require a respite period of lower temperatures within which they can metabolize, grow and reproduce.
The higher the average annual temperature a surface experiences, the shorter the respite period for any lichen potentially inhabiting that surface. A critical average temperature threshold of approximately 21 ?C has been identified on the stairwell, with average stone surface temperatures greater than this
generally inhibiting lichen colonization. A brief visual condition assessment between lichen-covered and lichen-free surfaces on the limestone sections of the stairwell suggests relative bioprotection induced by lichen coverage, with stonework quality and sharpness remaining more defined beneath lichen-covered surfaces. The methodology employed in this paper may have further applications in the monitoring and mapping of thermal stress fatigue on historic building materials.

Mass-loss rates for hot luminous stars:The influence of line branching

The effect of photon frequency redistribution by line branching on mass-loss rates for hot luminous stars is investigated. Monte Carlo simulations are carried out for a range of OB star models which show that previous mass-loss calculations which neglect non-resonance line scattering overestimate mass-loss rates for luminous O stars by ~20 per cent. For luminous B stars the effect is somewhat larger, typically ~50 per cent. A Wolf-Rayet star model is used to investigate line branching in the strong wind limit. In this case the effect of line branching is much greater, giving mass-loss rates that are smaller by a factor ~3 from computations which neglect branching.

Use of MIR Spectroscopy for Optimisation of Biogas Plants

MIR spectroscopy is an established technique which has process monitoring applications in the chemical and pharmaceutical industries. Previous attempts to utilise the technology for monitoring of AD plants were of limited success, with operation hindered by severe clogging of the probe.

Novel fittings, which allow a probe to be withdrawn from the process fluid, cleaned and recalibrated in situ have now been developed to combat this clogging problem. This has allowed a spectroscopic probe to be used successfully in lab scale digesters for real time measurement of VFA concentration, a key parameter to the stability of AD plants.

This project will demonstrate the technology at a farm scale AD plant for the first time. Both real-time measurements of VFA concentrations and parameters currently measured by plant operators will be available, leading to state-of-the-art monitoring and control of the AD plant. With the improved monitoring that this probe will deliver, it is hoped to realise a 10% increase in biogas production without compromising the stability of the process. This will deliver both economic and environmental benefits.

The Interlaboratory Robustness Of Next-Generation Sequencing (IRON) Study Phase II: Deep-Sequencing Analyses Of Hematological Malignancies Performed In 8,867 Cases By An International Network Involving 27 Laboratories

Introduction: Amplicon deep-sequencing using second-generation sequencing technology is an innovative molecular diagnostic technique and enables a highly-sensitive detection of mutations. As an international consortium we had investigated previously the robustness, precision, and reproducibility of 454 amplicon next-generation sequencing (NGS) across 10 laboratories from 8 countries (Leukemia, 2011;25:1840-8).

Aims: In Phase II of the study, we established distinct working groups for various hematological malignancies, i.e. acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), chronic myelogenous leukemia (CML), myelodysplastic syndromes (MDS), myeloproliferative neoplasms (MPN), and multiple myeloma. Currently, 27 laboratories from 13 countries are part of this research consortium. In total, 74 gene targets were selected by the working groups and amplicons were developed for a NGS deep-sequencing assay (454 Life Sciences, Branford, CT). A data analysis pipeline was developed to standardize mutation interpretation both for accessing raw data (Roche Amplicon Variant Analyzer, 454 Life Sciences) and variant interpretation (Sequence Pilot, JSI Medical Systems, Kippenheim, Germany).

Results: We will report on the design, standardization, quality control aspects, landscape of mutations, as well as the prognostic and predictive utility of this assay in a cohort of 8,867 cases. Overall, 1,146 primer sequences were designed and tested. In detail, for example in AML, 924 cases had been screened for CEBPA mutations. RUNX1 mutations were analyzed in 1,888 cases applying the deep-sequencing read counts to study the stability of such mutations at relapse and their utility as a biomarker to detect residual disease. Analyses of DNMT3A (n=1,041) were focused to perform landscape investigations and to address the prognostic relevance. Additionally, this working group is focusing on TET2, ASXL1, and TP53 analyses. A novel prognostic model is being developed allowing stratification of AML into prognostic subgroups based on molecular markers only. In ALL, 1,124 pediatric and adult cases have been screened, including 763 assays for TP53 mutations both at diagnosis and relapse of ALL. Pediatric and adult leukemia expert labs developed additional content to study the mutation incidence of other B and T lineage markers such as IKZF1, JAK2, IL7R, PAX5, EP300, LEF1, CRLF2, PHF6, WT1, JAK1, PTEN, AKT1, IL7R, NOTCH1, CREBBP, or FBXW7. Further, the molecular landscape of CLL is changing rapidly. As such, a separate working group focused on analyses including NOTCH1, SF3B1, MYD88, XPO1, FBXW7 and BIRC3. Currently, 922 cases were screened to investigate the range of mutational burden of NOTCH1 mutations for their prognostic relevance. In MDS, RUNX1 mutation analyses were performed in 977 cases. The prognostic relevance of TP53 mutations in MDS was assessed in additional 327 cases, including isolated deletions of chromosome 5q. Next, content was developed targeting genes of the cellular splicing component, e.g. SF3B1, SRSF2, U2AF1, and ZRSR2. In BCR-ABL1-negative MPN, nine genes of interest (JAK2, MPL, TET2, CBL, KRAS, EZH2, IDH1, IDH2, ASXL1) have been analyzed in a cohort of 155 primary myelofibrosis cases searching for novel somatic mutations and addressing their relevance for disease progression and leukemia transformation. Moreover, an assay was developed and applied to CMML cases allowing the simultaneous analysis of 25 leukemia-associated target genes in a single sequencing run using just 20 ng of starting DNA. Finally, nine laboratories are studying CML, applying ultra-deep sequencing of the BCR-ABL1 tyrosine kinase domain. Analyses were performed on 615 cases investigating the dynamics of expansion of mutated clones under various tyrosine kinase inhibitor therapies.

Conclusion: Molecular characterization of hematological malignancies today requires high diagnostic sensitivity and specificity. As part of the IRON-II study, a network of laboratories analyzed a variety of disease entities applying amplicon-based NGS assays. Importantly, the consortium not only standardized assay design for disease-specific panels, but also achieved consensus on a common data analysis pipeline for mutation interpretation. Distinct working groups have been forged to address scientific tasks and in total 8,867 cases had been analyzed thus far.

Classification of fundus autofluorescence patterns in early age-related macular disease

PURPOSE. To describe and classify patterns of abnormal fundus autofluorescence (FAF) in eyes with early nonexudative age-related macular disease (AMD). METHODS. FAF images were recorded in eyes with early AMD by confocal scanning laser ophthalmoscopy (cSLO) with excitation at 488 nm (argon or OPSL laser) and emission above 500 or 521 nm (barrier filter). A standardized protocol for image acquisition and generation of mean images after automated alignment was applied, and routine fundus photographs were obtained. FAF images were classified by two independent observers. The ? statistic was applied to assess intra- and interobserver variability. RESULTS. Alterations in FAF were classified into eight phenotypic patterns including normal, minimal change, focal increased, patchy, linear, lacelike, reticular, and speckled. Areas with abnormal increased or decreased FAF signals may or may not have corresponded to funduscopically visible alterations. For intraobserver variability, ? of observer I was 0.80 (95% confidence interval [CI]0.71-0.89) and of observer II, 0.74. (95% CI, 0.64-0.84). For interobserver variability, ? was 0.77 (95% CI, 0.67-0.87). CONCLUSIONS. Various phenotypic patterns of abnormal FAF can be identified with cSLO imaging. Distinct patterns may reflect heterogeneity at a cellular and molecular level in contrast to a nonspecific aging process. The results indicate that the classification system yields a relatively high degree of intra- and interobserver agreement. It may be applicable for determination of novel prognostic determinants in longitudinal natural history studies, for identification of genetic risk factors, and for monitoring of future therapeutic interventions to slow the progression of early AMD. Copyright © Association for Research in Vision and Ophthalmology.

Nonlinear scattering by anisotropic dielectric periodic structures

The combinatorial frequency generation by the periodic stacks of binary layers of anisotropic nonlinear dielectrics is examined. The products of nonlinear scattering are characterised in terms of the three-wave mixing processes. It is shown that the intensity of the scattered waves of combinatorial frequencies is strongly influenced by the constitutive and geometrical parameters of the anisotropic layers, and the frequency ratio and angles of incidence of pump waves. The enhanced efficiency of the frequency conversion at Wolf-Bragg resonances has been demonstrated for the lossless and lossy-layered structures. © 2012 O. V. Shramkova and A. G. Schuchinsky.

State Estimation for Anaerobic Digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.