Giving structure to the biofilm matrix: an overview of individual strategies and emerging common themes

Biofilms are communities of microbial cells that underpin diverse processes including sewage bioremediation, plant growth promotion, chronic infections and industrial biofouling. The cells resident in the biofilm are encased within a self-produced exopolymeric matrix that commonly comprises lipids, proteins that frequently exhibit amyloid-like properties, eDNA and exopolysaccharides. This matrix fulfils a variety of functions for the community, from providing structural rigidity and protection from the external environment to controlling gene regulation and nutrient adsorption. Critical to the development of novel strategies to control biofilm infections, or the capability to capitalize on the power of biofilm formation for industrial and biotechnological uses, is an in-depth knowledge of the biofilm matrix. This is with respect to the structure of the individual components, the nature of the interactions between the molecules and the three-dimensional spatial organization. We highlight recent advances in the understanding of the structural and functional role that carbohydrates and proteins play within the biofilm matrix to provide three-dimensional architectural integrity and functionality to the biofilm community. We highlight, where relevant, experimental techniques that are allowing the boundaries of our understanding of the biofilm matrix to be extended using Escherichia coli, Staphylococcus aureus, Vibrio cholerae, and Bacillus subtilis as exemplars.

Double ionization in R-matrix theory using a two-electron outer region

We have developed a two-electron outer region for use within R-matrix theory to describe double ionisation processes. The capability of this method is demonstrated for single-photon double ionisation of He in the photon energy region between 80 eV to 180 eV. The cross sections are in agreement with established data. The extended RMT method also provides information on higher-order processes, as demonstrated by the identification of signatures for sequential double ionisation processes involving an intermediate He⁺ state with n=2.

'The Blazing Torch': New Light on English Balladry as a Multi-Media Matrix

This paper investigates the inter-twining histories of two highly successful broadside ballads during the seventeenth century. Neither has been systematically studied before. A set of cultural relationships is opened for consideration by these songs: first, between the two ballads, which are different in several ways but set to the same tune; second, between the selected songs and other ballads on comparable themes; and third, between different editions of the two featured songs. In discussing each of these relationships, attention is paid not only to the texts but to the pictures and the tunes that helped to bring balladry to life for early-modern consumers. It is argued that balladry should be studied as an interconnected web and that individual publications drew significance from the manner in which they associated themselves – through shared pictures, tunes and narratives – with other examples of the genre.

Photoionization cross sections for O-like S IX: a Breit-Pauli R-matrix calculation

In this paper we present photoionization cross sections for the lowest five states of O-like S IX (1s(2)2s(2)2p(4) P-3(0,1,2), D-1(2), S-1(0)). The relativistic Breit-Pauli R-matrix codes were utilized including all terms of the 2s(2)2p(3), 2s2p(4), 2p(5), 2s(2)2p(2)3s, 3p, 3d and 2s2p(3)3s, 3p, 3d configurations in the expansion of the collision wavefunction for S X. It was also found that to achieve convergence of the low-lying energy separations of the target levels, an additional 21 configuration functions needed to be included in the configuration interaction expansion, incorporating two-electron excitations from the 2s and 2p shells to the 3s, 3p and 3d shells. The present work thus constitutes the most sophisticated photoionization evaluation for ground and metastable levels of the S IX ion. Direct comparisons have been made with the only available data found on the OPEN-ADAS database between level resolved contributions of the spectrum. This comparison for the background cross section exhibits excellent agreement at all photon energies for each partial photoionization cross section contribution investigated. Finally, the autoionizing bound states arising from numerous open channels have also been investigated and identified using the QB approach, a procedure for analyzing resonances in atomic and molecular collision theory which exploits the analytic properties of R-matrix theory. Major Rydberg resonance series are also presented and tabulated for the dominant linewidths considered.

Regenerated cellulose matrix-encapsulated active substances and method therefor.

The process involves encapsulation or immobilization of the active solid substance in a cellulose framework by regenerating cellulose dissolved in an ionic liq. solvent in a regenerating soln. The active substance can be initially present in the ionic liq. or in the regenerating solvent either as a soln. or dispersion. The invention is applicable to mol. encapsulation and to entrapping of larger particles including enzymes, nanoparticles and macroscopic components, and to the formation of bulk materials with a wide range of morphol. forms. Thus, carbamoylmethylphosphine oxide (I) encapsulated in a cellulose matrix was realized by adding I to a 10% soln. of cellulose in 1-butyl-3-methylimidazolium chloride (ionic liq.) under vigorous stirring and then removing the ionic liq. with water. [on SciFinder(R)]

Comprehensive profiling and localisation of the matrix metalloproteinases in urothelial carcinoma

The matrix metalloproteinases (MMPs) are endopeptidases which break down the extracellular matrix and regulate cytokine and growth factor activity. Several MMPs have been implicated in the promotion of invasion and metastasis in a broad range of tumours including urothelial carcinoma. In this study, RNA from 132 normal bladder and urothelial carcinoma specimens was profiled for each of the 24 human MMPs, the four endogenous tissue inhibitors of MMPs (TIMPs) and several key growth factors and their receptors using quantitative real time RT-PCR. Laser capture microdissection (LCM) of RNA from 22 tumour and 11 normal frozen sections was performed allowing accurate RNA extraction from either stromal or epithelial compartments. This study confirms the over expression in bladder tumour tissue of well-documented MMPs and highlights a range of MMPs which have not previously been implicated in the development of urothelial cancer. In summary, MMP-2, MT1-MMP and the previously unreported MMP-28 were very highly expressed in tumour samples while MMPs 1, 7, 9, 11, 15, 19 and 23 were highly expressed. There was a significant positive correlation between transcript expression and tumour grade for MMPs 1, 2, 8, 10, 11, 12, 13, 14, 15 and 28 (P < 0.001). At the same confidence interval, TIMP-1 and TIMP-3 also correlated with increasing tumour grade. LCM revealed that most highly expressed MMPs are located primarily within the stromal compartment except MMP-13 which localised to the epithelial compartment. This work forms the basis for further functional studies, which will help to confirm the MMPs as potential diagnostic and therapeutic targets in early bladder cancer.

Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization

How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain activity, as well as the behavioral responses. We show that this is an instance of the Coupled Matrix-Tensor Factorization (CMTF) problem. We propose Scoup-SMT, a novel, fast, and parallel algorithm that solves the CMTF problem and produces a sparse latent low-rank subspace of the data. In our experiments, we find that Scoup-SMT is 50-100 times faster than a state-of-the-art algorithm for CMTF, along with a 5 fold increase in sparsity. Moreover, we extend Scoup-SMT to handle missing data without degradation of performance. We apply Scoup-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Scoup-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy. Finally, we demonstrate the generality of Scoup-SMT, by applying it on a Facebook dataset (users, friends, wall-postings); there, Scoup-SMT spots spammer-like anomalies.