Prospects and challenges of numerical modeling of the Sun at millimeter wavelengths

The Atacama Large Millimeter/submillimeter Array (ALMA) offers new diagnostic possibilities that complement other commonly used diagnostics for the study of the Sun. In particular, ALMA’s ability to serve as an essentially linear thermometer of the chromospheric gas at unprecedented spatial resolution at millimeter wavelengths and future polarization measurements has great diagnostic potential. Solar ALMA observations are therefore expected to contribute significantly to answering long-standing questions about the structure, dynamics, and energy balance of the outer layers of the solar atmosphere. In this regard, current and future ALMA data are also important for constraining and further developing numerical models of the solar atmosphere, which in turn are often vital for the interpretation of observations. The latter is particularly important given the Sun’s highly intermittent and dynamic nature that involves a plethora of processes occurring over extended ranges in spatial and temporal scales. Realistic forward modeling of the Sun therefore requires time-dependent three-dimensional radiation magnetohydrodynamics that account for non-equilibrium effects and, typically as a separate step, detailed radiative transfer calculations, resulting in synthetic observables that can be compared to observations. Such artificial observations sometimes also account for instrumental and seeing effects, which, in addition to aiding the interpretation of observations, provide instructive tools for designing and optimizing ALMA’s solar observing modes. In the other direction, ALMA data in combination with other simultaneous observations enable the reconstruction of the solar atmospheric structure via data inversion techniques. This article highlights central aspects of the impact of ALMA for numerical modeling of the Sun and their potential and challenges, together with selected examples

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes

<p>Abstract</p> <p>Background</p> <p>In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases.</p> <p>Results</p> <p>This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis.</p> <p>Conclusion</p> <p>The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.</p

Psychometric performance of the CAMPHOR and SF-36 in pulmonary hypertension

BACKGROUND: The Cambridge Pulmonary Hypertension Outcome Review (CAMPHOR) and the Medical Outcomes Study Short Form 36 (SF-36) are widely used to assess patient-reported outcome in individuals with pulmonary hypertension (PH). The aim of the study was to compare the psychometric properties of the two measures. METHODS: Participants were recruited from specialist PH centres in Australia and New Zealand. Participants completed the CAMPHOR and SF-36 at two time points two weeks apart. The SF-36 is a generic health status questionnaire consisting of 36 items split into 8 sections. The CAMPHOR is a PH-specific measure consisting of 3 scales; symptoms, activity limitations and needs-based QoL. The questionnaires were assessed for distributional properties (floor and ceiling effects), internal consistency (Cronbach's alpha), test-retest reliability and construct validity (scores by World Health Organisation functional classification). RESULTS: The sample comprised 65 participants (mean (SD) age = 57.2 (14.5) years; n(%) male = 14 (21.5%)). Most of the patients were in WHO class 2 (27.7%) and 3 (61.5%). High ceiling effects were observed for the SF-36 bodily pain, social functioning and role emotional domains. Test-retest reliability was poor for six of the eight SF-36 domains, indicating high levels of random measurement error. Three of the SF-36 domains did not distinguish between WHO classes. In contrast, all CAMPHOR scales exhibited good distributional properties, test retest reliability and distinguished between WHO functional classes. CONCLUSIONS: The CAMPHOR exhibited superior psychometric properties, compared with the SF-36, in the assessment of PH patient-reported outcome

Resolving forward-reverse logistics multi-period model using evolutionary algorithms

© 2016 Elsevier Ltd In the changing competitive landscape and with growing environmental awareness, reverse logistics issues have become prominent in manufacturing organizations. As a result there is an increasing focus on green aspects of the supply chain to reduce environmental impacts and ensure environmental efficiency. This is largely driven by changes made in government rules and regulations with which organizations must comply in order to successfully operate in different regions of the world. Therefore, manufacturing organizations are striving hard to implement environmentally efficient supply chains while simultaneously maximizing their profit to compete in the market. To address the issue, this research studies a forward-reverse logistics model. This paper puts forward a model of a multi-period, multi-echelon, vehicle routing, forward-reverse logistics system. The network considered in the model assumes a fixed number of suppliers, facilities, distributors, customer zones, disassembly locations, re-distributors and second customer zones. The demand levels at customer zones are assumed to be deterministic. The objective of the paper is to maximize the total expected profit and also to obtain an efficient route for the vehicle corresponding to an optimal/near optimal solution. The proposed model is resolved using Artificial Immune System (AIS) and Particle Swarm Optimization (PSO) algorithms. The findings show that for the considered model, AIS works better than the PSO. This information is important for a manufacturing organization engaged in reverse logistics programs and in running units efficiently. This paper also contributes to the limited literature on reverse logistics that considers costs and profit as well as vehicle route management

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

High Chromosome Number in hematological cancer cell lines is a Negative Predictor of Response to the inhibition of Aurora B and C by GSK1070916

<p>Abstract</p> <p>Background</p> <p>Aurora kinases play critical roles in mitosis and are being evaluated as therapeutic targets in cancer. GSK1070916 is a potent, selective, ATP competitive inhibitor of Aurora kinase B and C. Translation of predictive biomarkers to the clinic can benefit patients by identifying the tumors that are more likely to respond to therapies, especially novel inhibitors such as GSK1070916.</p> <p>Methods</p> <p>59 Hematological cancer-derived cell lines were used as models for response where <it>in vitro </it>sensitivity to GSK1070916 was based on both time and degree of cell death. The response data was analyzed along with karyotype, transcriptomics and somatic mutation profiles to determine predictors of response.</p> <p>Results</p> <p>20 cell lines were sensitive and 39 were resistant to treatment with GSK1070916. High chromosome number was more prevalent in resistant cell lines (p-value = 0.0098, Fisher Exact Test). Greater resistance was also found in cell lines harboring polyploid subpopulations (p-value = 0.00014, Unpaired t-test). A review of NOTCH1 mutations in T-ALL cell lines showed an association between NOTCH1 mutation status and chromosome number (p-value = 0.0066, Fisher Exact Test).</p> <p>Conclusions</p> <p>High chromosome number associated with resistance to the inhibition of Aurora B and C suggests cells with a mechanism to bypass the high ploidy checkpoint are resistant to GSK1070916. High chromosome number, a hallmark trait of many late stage hematological malignancies, varies in prevalence among hematological malignancy subtypes. The high frequency and relative ease of measurement make high chromosome number a viable negative predictive marker for GSK1070916.</p

H2r: Identification of evolutionary important residues by means of an entropy based analysis of multiple sequence alignments

BACKGROUND: A multiple sequence alignment (MSA) generated for a protein can be used to characterise residues by means of a statistical analysis of single columns. In addition to the examination of individual positions, the investigation of co-variation of amino acid frequencies offers insights into function and evolution of the protein and residues. RESULTS: We introduce conn(k), a novel parameter for the characterisation of individual residues. For each residue k, conn(k) is the number of most extreme signals of co-evolution. These signals were deduced from a normalised mutual information (MI) value U(k, l) computed for all pairs of residues k, l. We demonstrate that conn(k) is a more robust indicator than an individual MI-value for the prediction of residues most plausibly important for the evolution of a protein. This proposition was inferred by means of statistical methods. It was further confirmed by the analysis of several proteins. A server, which computes conn(k)-values is available at http://www-bioinf.uni-regensburg.de. CONCLUSION: The algorithms H2r, which analyses MSAs and computes conn(k)-values, characterises a specific class of residues. In contrast to strictly conserved ones, these residues possess some flexibility in the composition of side chains. However, their allocation is sensibly balanced with several other positions, as indicated by conn(k)

Cooperative Transition between Open and Closed Conformations in Potassium Channels

Potassium (K+) ion channels switch between open and closed conformations. The nature of this important transition was revealed by comparing the X-ray crystal structures of the MthK channel from Methanobacterium thermoautotrophicum, obtained in its open conformation, and the KcsA channel from Streptomyces lividans, obtained in its closed conformation. We analyzed the dynamic characteristics and energetics of these homotetrameric structures in order to study the role of the intersubunit cooperativity in this transition. For this, elastic models and in silico alanine-scanning mutagenesis were used, respectively. Reassuringly, the calculations manifested motion from the open (closed) towards the closed (open) conformation. The calculations also revealed a network of dynamically and energetically coupled residues. Interestingly, the network suggests coupling between the selectivity filter and the gate, which are located at the two ends of the channel pore. Coupling between these two regions was not observed in calculations that were conducted with the monomer, which emphasizes the importance of the intersubunit interactions within the tetrameric structure for the cooperative gating behavior of the channel

N-Terminal Gly224–Gly411 Domain in Listeria Adhesion Protein Interacts with Host Receptor Hsp60

Listeria adhesion protein (LAP) is a housekeeping bifunctional enzyme consisting of N-terminal acetaldehyde dehydrogenase (ALDH) and C-terminal alcohol dehydrogenase (ADH). It aids Listeria monocytogenes in crossing the epithelial barrier through a paracellular route by interacting with its host receptor, heat shock protein 60 (Hsp60). To gain insight into the binding interaction between LAP and Hsp60, LAP subdomain(s) participating in the Hsp60 interaction were investigated.Using a ModBase structural model, LAP was divided into 4 putative subdomains: the ALDH region contains N1 (Met(1)-Pro(223)) and N2 (Gly(224)-Gly(411)), and the ADH region contains C1 (Gly(412)-Val(648)) and C2 (Pro(649)-Val(866)). Each subdomain was cloned and overexpressed in Escherichia coli and purified. Purified subdomains were used in ligand overlay, immunofluorescence, and bead-based epithelial cell adhesion assays to analyze each domain's affinity toward Hsp60 protein or human ileocecal epithelial HCT-8 cells.The N2 subdomain exhibited the greatest affinity for Hsp60 with a K(D) of 9.50±2.6 nM. The K(D) of full-length LAP (7.2±0.5 nM) to Hsp60 was comparable to the N2 value. Microspheres (1 µm diameter) coated with N2 subdomain showed significantly (P<0.05) higher binding to HCT-8 cells than beads coated with other subdomains and this binding was inhibited when HCT-8 cells were pretreated with anti-Hsp60 antibody to specifically block epithelial Hsp60. Furthermore, HCT-8 cells pretreated with purified N2 subdomain also reduced L. monocytogenes adhesion by about 4 log confirming its involvement in interaction with epithelial cells.These data indicate that the N2 subdomain in the LAP ALDH domain is critical in initiating interaction with mammalian cell receptor Hsp60 providing insight into the molecular mechanism of pathogenesis for the development of potential anti-listerial control strategies