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Live cell flattening
(2010)
Eukaryotic cell flattening is valuable for improving microscopic observations, ranging from bright field (BF) to total internal reflection fluorescence (TIRF) microscopy. Fundamental processes, such as mitosis and in vivo actin polymerization, have been investigated using these techniques. Here, we review the well known agar overlayer protocol and the oil overlay method. In addition, we present more elaborate microfluidics-based techniques that provide us with a greater level of control. We demonstrate these techniques on the social amoebae Dictyostelium discoideum, comparing the advantages and disadvantages of each method.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
(2010)
Background
In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space.
Results
The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability.
Conclusions
While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Background: Cysteine is a component in organic compounds including glutathione that have been implicated in the adaptation of plants to stresses. O-acetylserine (thiol) lyase (OAS-TL) catalyses the final step of cysteine biosynthesis. OAS-TL enzyme isoforms are localised in the cytoplasm, the plastids and mitochondria but the contribution of individual OAS-TL isoforms to plant sulphur metabolism has not yet been fully clarified.
Results: The seedling lethal phenotype of the Arabidopsis onset of leaf death3-1 (old3-1) mutant is due to a point mutation in the OAS-A1 gene, encoding the cytosolic OAS-TL. The mutation causes a single amino acid substitution from Gly(162) to Glu(162), abolishing old3-1 OAS-TL activity in vitro. The old3-1 mutation segregates as a monogenic semidominant trait when backcrossed to its wild type accession Landsberg erecta (Ler-0) and the Di-2 accession. Consistent with its semi-dominant behaviour, wild type Ler-0 plants transformed with the mutated old3-1 gene, displayed the early leaf death phenotype. However, the old3-1 mutation segregates in an 11: 4: 1 (wild type: semi-dominant: mutant) ratio when backcrossed to the Colombia-0 and Wassilewskija accessions. Thus, the early leaf death phenotype depends on two semi-dominant loci. The second locus that determines the old3-1 early leaf death phenotype is referred to as odd-ler (for old3 determinant in the Ler accession) and is located on chromosome 3. The early leaf death phenotype is temperature dependent and is associated with increased expression of defence-response and oxidative-stress marker genes. Independent of the presence of the odd-ler gene, OAS-A1 is involved in maintaining sulphur and thiol levels and is required for resistance against cadmium stress.
Conclusions: The cytosolic OAS-TL is involved in maintaining organic sulphur levels. The old3-1 mutation causes genome-dependent and independent phenotypes and uncovers a novel function for the mutated OAS-TL in cell death regulation.
Background: Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites.
Results: From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented.
These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected.
Conclusions: We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
We show that the residue density of the logarithm of a generalized Laplacian on a closed manifold definesan invariant polynomial-valued differential form. We express it in terms of a finite sum of residues ofclassical pseudodifferential symbols. In the case of the square of a Dirac operator, these formulas providea pedestrian proof of the Atiyah–Singer formula for a pure Dirac operator in four dimensions and for atwisted Dirac operator on a flat space of any dimension. These correspond to special cases of a moregeneral formula by Scott and Zagier. In our approach, which is of perturbative nature, we use either aCampbell–Hausdorff formula derived by Okikiolu or a noncommutative Taylor-type formula.
We present an approach that provides automatic or semi-automatic support for evolution and change management in heterogeneous legacy landscapes where (1) legacy heterogeneous, possibly distributed platforms are integrated in a service oriented fashion, (2) the coordination of functionality is provided at the service level, through orchestration, (3) compliance and correctness are provided through policies and business rules, (4) evolution and correctness-by-design are supported by the eXtreme Model Driven Development paradigm (XMDD) offered by the jABC (Margaria and Steffen in Annu. Rev. Commun. 57, 2004)—the model-driven service oriented development platform we use here for integration, design, evolution, and governance. The artifacts are here semantically enriched, so that automatic synthesis plugins can field the vision of Enterprise Physics: knowledge driven business process development for the end user.
We demonstrate this vision along a concrete case study that became over the past three years a benchmark for Semantic Web Service discovery and mediation. We enhance the Mediation Scenario of the Semantic Web Service Challenge along the 2 central evolution paradigms that occur in practice: (a) Platform migration: platform substitution of a legacy system by an ERP system and (b) Backend extension: extension of the legacy Customer Relationship Management (CRM) and Order Management System (OMS) backends via an additional ERP layer.
Two recent magnetic field models, GRIMM and xCHAOS, describe core field accelerations with similar behavior up to Spherical Harmonic (SH) degree 5, but which differ significantly for higher degrees. These discrepancies, due to different approaches in smoothing rapid time variations of the core field, have strong implications for the interpretation of the secular variation. Furthermore, the amount of smoothing applied to the highest SH degrees is essentially the modeler’s choice. We therefore investigate new ways of regularizing core magnetic field models. Here we propose to constrain field models to be consistent with the frozen flux induction equation by co-estimating a core magnetic field model and a flow model at the top of the outer core. The flow model is required to have smooth spatial and temporal behavior. The implementation of such constraints and their effects on a magnetic field model built from one year of CHAMP satellite and observatory data, are presented. In particular, it is shown that the chosen constraints are efficient and can be used to build reliable core magnetic field secular variation and acceleration model components.
It has been suggested that coronal mass ejections (CMEs) remove the magnetic he-licity of their coronal source region from the Sun. Such removal is often regarded to be necessary due to the hemispheric sign preference of the helicity, which inhibits a simple annihilation by reconnection between volumes of opposite chirality. Here we monitor the relative magnetic he-licity contained in the coronal volume of a simulated flux rope CME, as well as the upward flux of relative helicity through horizontal planes in the simulation box. The unstable and erupting flux rope carries away only a minor part of the initial relative helicity; the major part remains in the volume. This is a consequence of the requirement that the current through an expanding loop must decrease if the magnetic energy of the configuration is to decrease as the loop rises, to provide the kinetic energy of the CME.
The Takab complex is composed of a variety of metamorphic rocks including amphibolites, metapelites, mafic granulites, migmatites and meta-ultramafics, which are intruded by the granitoid. The granitoid magmatic activity occurred in relation to the subduction of the Neo-Tethys oceanic crust beneath the Iranian crust during Tertiary times. The granitoids are mainly granodiorite, quartz monzodiorite, monzonite and quartz diorite. Chemically, the magmatic rocks are characterized by ASI < 1.04, AI < 0.87 and high contents of CaO (up to ∼ 14.5 wt %), which are consistent with the I-type magmatic series. Low FeO t /(FeO t +MgO) values (< 0.75) as well as low Nb, Y and K 2 O contents of the investigated rocks resemble the calc-alkaline series. Low SiO 2 , K 2 O/Na 2 O and Al 2 O 3 accompanied by high CaO and FeO contents indicate melting of metabasites as an appropriate source for the intrusions. Negative Ti and Nb anomalies verify a metaluminous crustal origin for the protoliths of the investigated igneous rocks. These are comparable with compositions of the associated mafic migmatites, in the Takab metamorphic complex, which originated from the partial melting of amphibolites. Therefore, crustal melting and a collision-related origin for the Takab calc-alkaline intrusions are proposed here on the basis of mineralogy and geochemical characteristics. The P–T evolution during magmatic crystallization and subsolidus cooling stages is determined by the study of mineral chemistry of the granodiorite and the quartz diorite. Magmatic crystallization pressure and temperature for the quartz-diorite and the granodiorite are estimated to be P ∼ 7.8 ± 2.5 kbar, T ∼ 760 ± 75 ◦C and P ∼ 5 ± 1 kbar, T ∼ 700 ◦C, respectively. Subsolidus conditions are consistent with temperatures of ∼ 620 ◦C and ∼ 600 ◦C, and pressures of ∼ 5 kbar and ∼ 3.5 kbar for the quartz-diorite and the granodiorite, respectively.