Creatine kinase B deficient neurons exhibit an increased fraction of motile mitochondria

Background  

Neurons require an elaborate system of intracellular transport to distribute cargo throughout axonal and dendritic projections. Active anterograde and retrograde transport of mitochondria serves in local energy distribution, but at the same time also requires input of ATP. Here we studied whether brain-type creatine kinase (CK-B), a key enzyme for high-energy phosphoryl transfer between ATP and CrP in brain, has an intermediary role in the reciprocal coordination between mitochondrial motility and energy distribution. Therefore, we analysed the impact of brain-type creatine kinase (CK-B) deficiency on transport activity and velocity of mitochondria in primary murine neurons and made a comparison to the fate of amyloid precursor protein (APP) cargo in these cells, using live cell imaging.     

Critical petermann K factor for intensity noise squeezing

We investigate the impact of the Petermann-excess-noise factor K>/=1 on the possibility of intensity noise squeezing of laser light below the standard quantum limit. Using an N-mode model, we show that squeezing is limited to a floor level of 2(K-1) times the shot noise limit. Thus, even a modest Petermann factor significantly impedes squeezing, which becomes impossible when K>/=1.5. This appears as a serious limitation for obtaining sub-shot-noise light from practical semiconductor lasers. We present experimental evidence for our theory.     

Common vertex matrix: A novel characterization of molecular graphs by counting

We present a novel matrix representation of graphs based on the count of equal‐distance common vertices to each pair of vertices in a graph. The element (i, j) of this matrix is defined as the number of vertices at the same distance from vertices (i, j). As illustrated on smaller alkanes, these novel matrices are very sensitive to molecular branching and the distribution of vertices in a graph. In particular, we show that ordered row sums of these novel matrices can facilitate solving graph isomorphism for acyclic graphs. This has been illustrated on all undecane isomers C₁₁H₂₄ having the same path counts (total of 25 molecules), on pair of graphs on 18 vertices having the same distance degree sequences (Slater's graphs), as well as two graphs on 21 vertices having identical several topological indices derived from information on distances between vertices. © 2013 Wiley Periodicals, Inc.     

Degradation and Dissipation Studies of Isoproturon in a Silty Clay Loam from Norway

Degradation and dissipation studies in laboratory and field were performed with isoproturon (IPU) to produce data for modelling the fate of an autumn applied pesticide in a Gleyic Podzoluvisol in Norway. Transformation rate studies of IPU in the laboratory during 8 weeks displayed a DT 50 of 13 days in topsoil (0-20 cm) and 21 days in subsoil (20-40 cm) at 20°C. In topsoil, a decline in the content of the metabolite monodesmethyl-isoproturon (MMU) was observed along with an initial production of didesmethyl-isoproturon (MU) after 4 weeks. In subsoil, the content of MMU was stabilized and no decrease was observed during the experiment. Only trace amounts of MU were found in the subsoil. Field dissipation of IPU was investigated in a silty clay loam following post-emergence application to winter wheat (September 1999). A bromide tracer was used to monitor the water flow in the soil profile. Soil was sampled from the 0-20, 20-40, 40-60 and 60-80 cm layers after 1, 2, 4, 13, 62, 232 and 371 days. 13 days after herbicide application, the waterfront had reached a depth of 80 cm and as a result an amount of 7 mg IPU m m 3 could be recovered from this depth, representing 2% of the initial amount of herbicide applied. Less than 9% of the herbicide applied could be seen to penetrate below 20 cm soil depth. After 62 days, only 18% of the initial IPU amount applied could be recovered from the profile. Using the results from the laboratory degradation study, a theoretical DT 50 of IPU in the field was estimated to 18-25 days ( Q 10 = 2.2). The theoretical DT 50 corresponded well with the actual dissipation of IPU observed in the field. This indicated that degradation of IPU was the primary contribution to the fast dissipation of IPU in the field, and that the risk of runoff of IPU was negligible. Appearance of the major degradation product MMU in the field was monitored during the entire experimental period, at most representing 11% of the initial herbicide concentration. Field studies showed that MMU was more easily transported below the plough layer than isoproturon. Traces of IPU and MMU could be found in soil one year after application. A second degradation product, MU, could not be recovered in quantifiable amounts in the soil samples.     

Milestones in graphical bioinformatics

After reviewing the field of graphical bioinformatics, we have selected two dozen of the most significant publications that represent milestones of graphical bioinformatics. These publications can be viewed as forming the backbone of graphical bioinformatics, the branch of bioinformatics that initiates analysis of DNA, RNA, and proteins by considering various graphical representations of these sequences. Graphical bioinformatics, a division of bioinformatics that analyzes sequences of DNA, RNA, proteins, and proteomics maps by developing and using tools of discrete mathematics and graph theory in particular, has expanded since the year 2000, although pioneering contributions date back to Hamory (1983) and Jeffrey (1990). We chronologically follow the development of graphical bioinformatics, without assuming that readers are familiar with discrete mathematics or graph theory. Readers unfamiliar with graph theory may even have some advantage over those who have been only superficially exposed to graph theory, inview of wide misconceptions and misinformation about chemical graph theory among quantum chemists, physical chemists, and medicinal chemists in past decades. © 2013 Wiley Periodicals, Inc.     

On graphical and numerical characterization of proteomics maps

We outlined a mathematical approach suitable for characterization of experimental data given by 2-D densitograms. In particular we consider numerical characterization of proteomics maps. The basis of our approach is to order "spots" of a 2-D map and assign them unique labels (that in general will depend on the criteria used for ordering). In this way a map is "translated" into a sequence. In the next step one associates with the generated sequence a geometrical path and views such a path as a mathematical object that needs characterization. We have ordered spots representing proteins in 2-D gel plates according to their relative intensities which results in a zigzag path that produces a complicated "fingerprint" pattern. Mathematical characterization of zigzag pattern follows similar mathematical characterizations of embedded patterns based on matrices, the elements of which are given as quotients of Euclidean distance between spots and the distance along the zigzag path. The leading eigenvalue of constructed matrices is taken to represent characterization of the original 2-D map. Comparison of different 2-D maps (simulated by using random generator) allows one to construct partial order, which although qualitative in nature gives some insight into perturbation induced by foreign agents to the proteome of the control cell.     

The variable connectivity index 1chi(f) versus the traditional molecular descriptors: a comparative study of 1chi(f) against descriptors of CODESSA.

In this study we compared the prediction abilities of the variable connectivity index 1chi(f) (not included in CODESSA) with topological indices available from CODESSA. We selected the boiling points of n = 100 alcohols as the property and examined the pool of 56 topological indices. Prediction capabilities of the developed models were evaluated by classical training/test set approach. RMS errors calculated from the prediction set for the MLR models obtained from CODESSA software with 1, 2, 3, 4, and 5 parameters were 9.06, 5.69, 5.40, 4.9, and 3.37 degrees C, respectively. Using the variable connectivity index with weights x = 0.10 and y = -0.92 for carbon and oxygen atom respectively, we obtain regression BP = 38.12 1chi(f) - 37.56 with the correlation coefficient r = 0.9915, RMS error 4.21 degrees C calculated from the test set, and Fisher ratio F = 5691. Prediction capability of the variable connectivity index was better than for MLR regression model with up to four parameters.     

On the centrality of vertices of molecular graphs

For acyclic systems the center of a graph has been known to be either a single vertex of two adjacent vertices, that is, an edge. It has not been quite clear how to extend the concept of graph center to polycyclic systems. Several approaches to the graph center of molecular graphs of polycyclic graphs have been proposed in the literature. In most cases alternative approaches, however, while being apparently equally plausible, gave the same results for many molecules, but occasionally they differ in their characterization of molecular center. In order to reduce the number of vertices that would qualify as forming the center of the graph, a hierarchy of rules have been considered in the search for graph centers. We reconsidered the problem of “the center of a graph” by using a novel concept of graph theory, the vertex “weights,” defined by counting the number of pairs of vertices at the same distance from the vertex considered. This approach gives often the same results for graph centers of acyclic graphs as the standard definition of graph center based on vertex eccentricities. However, in some cases when two nonequivalent vertices have been found as graph center, the novel approach can discriminate between the two. The same approach applies to cyclic graphs without additional rules to locate the vertex or vertices forming the center of polycyclic graphs, vertices referred to as central vertices of a graph. In addition, the novel vertex “weights,” in the case of acyclic, cyclic, and polycyclic graphs can be interpreted as vertex centralities, a measure for how close or distant vertices are from the center or central vertices of the graph. Besides illustrating the centralities of a number of smaller polycyclic graphs, we also report on several acyclic graphs showing the same centrality values of their vertices. © 2013 Wiley Periodicals, Inc.     

On conjugated molecules with identical topological spectra

Properties of molecular graphs having identical topological spectra are investigated in some detail. It has been established that whole families of isospectral graphs can be derived from a molecular skeleton of vinyl benzene. A pair of isospectral graphs are obtained by an exchange of two non-equivalent residuals attached to particular sites of the skeleton. Additional pairs of isospectral graphs can be derived from related skeletons in which ortho positions of vinyl benzene are occupied by substituents. No constraints have to be imposed on the nature and form of the residuals or the substituting groups. This allows construction of larger isospectral systems including polymeric species. The theoretical foundation for the construction of isospectral graphs described in this work rests on the factorization of the eigenvalue problem of the adjacency matrix associated with molecular graphs which is analogous to a fragmentation of a secular determinant of a Hückel MO problem as outlined some time ago by Heilbronner. A formal proof of the procedure, expressed in a symbolic form, is presented in the Appendix. A discussion of some interesting features of isospectral systems reflected in special properties of topological eigenfunctions is presented.