Global phylogenomic analysis of nonencapsulated Streptococcus pneumoniae reveals a deep-branching classic lineage that is distinct from multiple sporadic lineages.

The surrounding capsule of Streptococcus pneumoniae has been identified as a major virulence factor and is targeted by pneumococcal conjugate vaccines (PCV). However, nonencapsulated Streptococcus pneumoniae (Non-Ec-Sp) have also been isolated globally, mainly in carriage studies. It is unknown if Non-Ec-Sp evolve sporadically, if they have high antibiotic non-susceptiblity rates and a unique, specific gene content. Here, whole genome sequencing of 131 Non-Ec-Sp isolates sourced from 17 different locations around the world was performed. Results revealed a deep-branching classic lineage that is distinct from multiple sporadic lineages. The sporadic lineages clustered with a previously sequenced, global collection of encapsulated S. pneumoniae (Ec-Sp) isolates while the classic lineage is comprised mainly of the frequently identified multi-locus sequences types ST344 (n=39) and ST448 (n=40). All ST344 and nine ST448 isolates had high non-susceptiblity rates to β-lactams and other antimicrobials. Analysis of the accessory genome reveals that the classic Non-Ec-Sp contained an increased number of mobile elements, than Ec-Sp and sporadic Non-Ec-Sp. Performing adherence assays to human epithelial cells for selected classic and sporadic Non-Ec-Sp revealed that the presence of a integrative conjugative element (ICE) results in increased adherence to human epithelial cells (P=0.005). In contrast, sporadic Non-Ec-Sp lacking the ICE had greater growth in vitro possibly resulting in improved fitness. In conclusion, Non-Ec-Sp isolates from the classic lineage have evolved separately. They have spread globally, are well adapted to nasopharyngeal carriage and are able to coexist with Ec-Sp. Due to continued use of pneumococcal conjugate vaccines, Non-Ec-Sp may become more prevalent.

Saddlepoint approximations to sensitivities of tail probabilities of random sums and comparisons with Monte Carlo estimators

This article proposes computing sensitivities of upper tail probabilities of random sums by the saddlepoint approximation. The considered sensitivity is the derivative of the upper tail probability with respect to the parameter of the summation index distribution. Random sums with Poisson or Geometric distributed summation indices and Gamma or Weibull distributed summands are considered. The score method with importance sampling is considered as an alternative approximation. Numerical studies show that the saddlepoint approximation and the method of score with importance sampling are very accurate. But the saddlepoint approximation is substantially faster than the score method with importance sampling. Thus, the suggested saddlepoint approximation can be conveniently used in various scientific problems.

Overexpression of EphB4 in the mammary epithelium shifts the differentiation pathway of progenitor cells and promotes branching activity and vascularization

Postnatally, the mammary gland undergoes continuous morphogenesis and thereby is especially prone to malignant transformation. Thus, the maintenance of the epithelium depends on a tight control of stem cell recruitment. We have previously shown that epithelial overexpression of the EphB4 receptor results in defective mammary epithelial development and conferred a metastasizing tumor phenotype on experimental mouse mammary tumors accompanied by a preponderance of progenitor cells. To analyze the effect of EphB4 overexpression on mammary epithelial cell fate, we have used Fluorescence Activated Cell Sorting (FACS) analyses to quantify epithelial sub-populations and repopulation assays of cleared fat pads to investigate their regenerative potential. These experiments revealed that deregulated EphB4 expression leads to an augmentation of bi-potent progenitor cells and to a shift of the differentiation pathway towards the luminal lineage. The analyses of the ductal outgrowths indicated that EphB4 overexpression leads to enforced branching activity, impedes ductal differentiation and stimulates angiogenesis. To elucidate the mechanisms forwarding EphB4 signals, we have compared the expression profile of defined cell populations between EphB4 transgene and wild type mammary glands concentrating on the wnt signaling pathway and on genes implicated in cell migration. With respect to wnt signaling, the progenitor cell population was the most affected, whereas the stem cell-enriched population showed the most pronounced deregulation of migration-associated genes. Thus, the luminal epithelial EphB4 signaling contributes, most likely via wnt signaling, to the regulation of migration and cell fate of early progenitors and is involved in the determination of branching points along the ductal tree.

Classification of interstitial lung disease patterns using local DCT features and random forest.

Over the last decade, a plethora of computer-aided diagnosis (CAD) systems have been proposed aiming to improve the accuracy of the physicians in the diagnosis of interstitial lung diseases (ILD). In this study, we propose a scheme for the classification of HRCT image patches with ILD abnormalities as a basic component towards the quantification of the various ILD patterns in the lung. The feature extraction method relies on local spectral analysis using a DCT-based filter bank. After convolving the image with the filter bank, q-quantiles are computed for describing the distribution of local frequencies that characterize image texture. Then, the gray-level histogram values of the original image are added forming the final feature vector. The classification of the already described patches is done by a random forest (RF) classifier. The experimental results prove the superior performance and efficiency of the proposed approach compared against the state-of-the-art.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.

Regularity conditions in the realisability problem in applications to point processes and random closed sets

We study existence of random elements with partially specified distributions. The technique relies on the existence of a positive ex-tension for linear functionals accompanied by additional conditions that ensure the regularity of the extension needed for interpreting it as a probability measure. It is shown in which case the extens ion can be chosen to possess some invariance properties. The results are applied to the existence of point processes with given correlation measure and random closed sets with given two-point covering function or contact distribution function. It is shown that the regularity condition can be efficiently checked in many cases in order to ensure that the obtained point processes are indeed locally finite and random sets have closed realisations.

On degeneracy and invariances of random fields paths with applications in Gaussian process modelling

We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy properties under well-chosen linear operators. We first show in a second order set-up that almost sure degeneracy of random field paths under some class of linear operators defined in terms of signed measures can be controlled through the two first moments. A special focus is then put on the Gaussian case, where these results are revisited and extended to further linear operators thanks to state-of-the-art representations. Several degeneracy properties are tackled, including random fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process modelling. In a first numerical experiment, it is shown that dedicated kernels can be used to infer an axis of symmetry. Our second numerical experiment deals with conditional simulations of a solution to the heat equation, and it is found that adapted kernels notably enable improved predictions of non-linear functionals of the field such as its maximum.

“But look: we have sat here too long”: Hilary Mantel’s tightrope walk of present-tense usage

Even after Hilary Mantel has won the Man Booker prize two times in a row with Wolf Hall and Bring up the Bodies, her novelistic account of the life of Thomas Cromwell, her intriguing decision to write these historical novels in the present tense gave cause to surprisingly little extended comment beyond a perfunctory nod to its evocation of immediacy. This presents not only a lacunae in the discussion about Mantel’s novels, but is also symptomatic for a change in the contemporary critical evaluation of present-tense narration in general. If present-tense narration once used to be a marker for experimental daring and might even have implied a certain hostility towards fictionality, Mantel’s novels give ample evidence that literary sensibilities have changed. In order to understand the scope and nature of this change, my paper puts Mantel’s use of the present tense in the context of both the historical development of present-tense usage and the ample contemporary landscape of present-tense narration. This allows me to show that the complexities of present-tense usage belie a reduction of its effect to an evocation of immediacy. Rather, I argue, Mantel uses it for a delicate tightrope walk between proximity and distance, history and fiction, authenticity and imagination.