Structural characterization of intrinsically disordered proteins by NMR spectroscopy.

Recent advances in NMR methodology and techniques allow the structural investigation of biomolecules of increasing size with atomic resolution. NMR spectroscopy is especially well-suited for the study of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) which are in general highly flexible and do not have a well-defined secondary or tertiary structure under functional conditions. In the last decade, the important role of IDPs in many essential cellular processes has become more evident as the lack of a stable tertiary structure of many protagonists in signal transduction, transcription regulation and cell-cycle regulation has been discovered. The growing demand for structural data of IDPs required the development and adaption of methods such as 13C-direct detected experiments, paramagnetic relaxation enhancements (PREs) or residual dipolar couplings (RDCs) for the study of 'unstructured' molecules in vitro and in-cell. The information obtained by NMR can be processed with novel computational tools to generate conformational ensembles that visualize the conformations IDPs sample under functional conditions. Here, we address NMR experiments and strategies that enable the generation of detailed structural models of IDPs

Star formation in disk galaxies driven by primordial H_2

We show that gaseous \HI disks of primordial composition irradiated by an external radiation field can develop a multiphase medium with temperatures between 10^2 and 10^4 K due to the formation of molecular hydrogen. For a given \HI column density there is a critical value of the radiation field below which only the cold \HI phase can exist. Due to a time decreasing quasar background, the gas starts cooling slowly after recombination until the lowest stable temperature in the warm phase is reached at a critical redshift $z=z_{cr}$. Below this redshift the formation of molecular hydrogen promotes a rapid transition towards the cold \HI phase. We find that disks of protogalaxies with 10^{20}\simlt N_{HI}\simlt 10^{21} cm^{-2} are gravitationally stable at $T\sim 10^4$ K and can start their star formation history only at z \simlt z_{cr}\sim 2, after the gas in the central portion of the disk has cooled to temperatures T\simlt 300 K. Such a delayed starbust phase in galaxies of low gas surface density and low dynamical mass can disrupt the disks and cause them to fade away. These objects could contribute significantly to the faint blue galaxy population.Comment: 16 pages (LaTeX), 2 Figures to be published in Astrophysical Journal Letter

Compact smallest eigenvalue expressions in Wishart-Laguerre ensembles with or without fixed-trace

The degree of entanglement of random pure states in bipartite quantum systems can be estimated from the distribution of the extreme Schmidt eigenvalues. For a bipartition of size M\geq N, these are distributed according to a Wishart-Laguerre ensemble (WL) of random matrices of size N x M, with a fixed-trace constraint. We first compute the distribution and moments of the smallest eigenvalue in the fixed trace orthogonal WL ensemble for arbitrary M\geq N. Our method is based on a Laplace inversion of the recursive results for the corresponding orthogonal WL ensemble by Edelman. Explicit examples are given for fixed N and M, generalizing and simplifying earlier results. In the microscopic large-N limit with M-N fixed, the orthogonal and unitary WL distributions exhibit universality after a suitable rescaling and are therefore independent of the constraint. We prove that very recent results given in terms of hypergeometric functions of matrix argument are equivalent to more explicit expressions in terms of a Pfaffian or determinant of Bessel functions. While the latter were mostly known from the random matrix literature on the QCD Dirac operator spectrum, we also derive some new results in the orthogonal symmetry class.Comment: 25 pag., 4 fig - minor changes, typos fixed. To appear in JSTA

The Social context of motorcycle riding and the key determinants influencing rider behavior: A qualitative investigation

Objective: Given the increasing popularity of motorcycle riding and heightened risk of injury or death associated with being a rider, this study explored rider behaviour as a determinant of rider safety and, in particular, key beliefs and motivations which influence such behaviour. To enhance the effectiveness of future education and training interventions, it is important to understand riders’ own views about what influences how they ride. Specifically, this study sought to identify key determinants of riders’ behaviour in relation to the social context of riding including social and identity-related influences relating to the group (group norms and group identity) as well as the self (moral/personal norm and self-identity). ----- ----- Method: Qualitative research was undertaken via group discussions with motorcycle riders (n = 41). Results: The findings revealed that those in the group with which one rides represent an important source of social influence. Also, the motorcyclist (group) identity was associated with a range of beliefs, expectations, and behaviours considered to be normative. Exploration of the construct of personal norm revealed that riders were most cognizant of the “wrong things to do” when riding; among those issues raised was the importance of protective clothing (albeit for the protection of others and, in particular, pillion passengers). Finally, self-identity as a motorcyclist appeared to be important to a rider’s self-concept and was likely to influence their on-road behaviour. ----- ----- Conclusion: Overall, the insight provided by the current study may facilitate the development of interventions including rider training as well as public education and mass media messages. The findings suggest that these interventions should incorporate factors associated with the social nature of riding in order to best align it with some of the key beliefs and motivations underpinning riders’ on-road behaviours

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation

BACKGROUND PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. METHODS Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. RESULTS In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. CONCLUSIONS The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer

Universal correlations and power-law tails in financial covariance matrices

Signatures of universality are detected by comparing individual eigenvalue distributions and level spacings from financial covariance matrices to random matrix predictions. A chopping procedure is devised in order to produce a statistical ensemble of asset-price covariances from a single instance of financial data sets. Local results for the smallest eigenvalue and individual spacings are very stable upon reshuffling the time windows and assets. They are in good agreement with the universal Tracy-Widom distribution and Wigner surmise, respectively. This suggests a strong degree of robustness especially in the low-lying sector of the spectra, most relevant for portfolio selections. Conversely, the global spectral density of a single covariance matrix as well as the average over all unfolded nearest-neighbour spacing distributions deviate from standard Gaussian random matrix predictions. The data are in fair agreement with a recently introduced generalised random matrix model, with correlations showing a power-law decay

Supersymmetric Vacua in Random Supergravity

We determine the spectrum of scalar masses in a supersymmetric vacuum of a general N=1 supergravity theory, with the Kahler potential and superpotential taken to be random functions of N complex scalar fields. We derive a random matrix model for the Hessian matrix and compute the eigenvalue spectrum. Tachyons consistent with the Breitenlohner-Freedman bound are generically present, and although these tachyons cannot destabilize the supersymmetric vacuum, they do influence the likelihood of the existence of an `uplift' to a metastable vacuum with positive cosmological constant. We show that the probability that a supersymmetric AdS vacuum has no tachyons is formally equivalent to the probability of a large fluctuation of the smallest eigenvalue of a certain real Wishart matrix. For normally-distributed matrix entries and any N, this probability is given exactly by P = exp(-2N^2|W|^2/m_{susy}^2), with W denoting the superpotential and m_{susy} the supersymmetric mass scale; for more general distributions of the entries, our result is accurate when N >> 1. We conclude that for |W| \gtrsim m_{susy}/N, tachyonic instabilities are ubiquitous in configurations obtained by uplifting supersymmetric vacua.Comment: 26 pages, 6 figure

In-cell NMR characterization of the secondary structure populations of a disordered conformation of α-Synuclein within E. coli cells

α-Synuclein is a small protein strongly implicated in the pathogenesis of Parkinson’s disease and related neurodegenerative disorders. We report here the use of in-cell NMR spectroscopy to observe directly the structure and dynamics of this protein within E. coli cells. To improve the accuracy in the measurement of backbone chemical shifts within crowded in-cell NMR spectra, we have developed a deconvolution method to reduce inhomogeneous line broadening within cellular samples. The resulting chemical shift values were then used to evaluate the distribution of secondary structure populations which, in the absence of stable tertiary contacts, are a most effective way to describe the conformational fluctuations of disordered proteins. The results indicate that, at least within the bacterial cytosol, α-synuclein populates a highly dynamic state that, despite the highly crowded environment, has the same characteristics as the disordered monomeric form observed in aqueous solution

Metabolomics guides rational development of a simplified cell culture medium for drug screening against <i>Trypanosoma brucei</i>

n vitro culture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream form &lt;i&gt;Trypanosoma brucei&lt;/i&gt;. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supports in vitro growth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (&#60;3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening