Background and ObjectiveIrritable Bowel Syndrome (IBS) has a substantial impact on health-related quality of life (HR-QoL) but high-quality data pre- and post-treatment using the IBS–Quality of Life (IBS-QOL) measure are limited. The objective of this study was to evaluate the changes from baseline of the IBS-QOL scores, symptom scores and health economic data in IBS patients, after 4 and 8 weeks of treatment with mebeverine hydrochloride or pinaverium bromide.MethodsThis was a prospective observational cohort study in patients with IBS, diagnosed using the Rome III criteria in four countries (Poland, Egypt, Mexico and China).ResultsA total of 607 patients were enrolled. At baseline, the IBS-QOL total scores were 52.0 in Poland, 48.9 in Egypt, 51.9 in Mexico, 76.4 in China and 56.4 overall. Increases in IBS-QOL total score were statistically significant at Weeks 4 and 8 overall and in each country (overall: 11.8 at Week 4, 24.3 at Week 8; p < 0.001). Improvements were shown in all IBS-QOL subscales and scores. Symptoms and health economic outcomes were improved. Furthermore, the favourable safety profile of these treatments was confirmed in this study.ConclusionsThis study demonstrated that IBS patients have a substantially reduced HR-QoL and that treatment with mebeverine hydrochloride or pinaverium bromide improved HR-QoL.

In complex simulation environments, certain parameter space regions may result in non-convergent or unphysical outcomes. All parameters can therefore be labeled with a binary class describing whether or not they lead to valid results. In general, it can be very difficult to determine feasible parameter regions, especially without previous knowledge. We propose a novel algorithm to explore such an unknown parameter space and improve its feasibility classification in an iterative way. Moreover, we include an additional optimization target in the algorithm to guide the exploration towards regions of interest and to improve the classification therein. In our method we make use of well-established concepts from the field of machine learning like kernel support vector machines and kernel ridge regression. From a comparison with a Kriging-based exploration approach based on recently published results we can show the advantages of our algorithm in a binary feasibility classification scenario with a discrete feasibility constraint violation. In this context, we also propose an improvement of the Kriging-based exploration approach. We apply our novel method to a fully realistic, industrially relevant chemical process simulation to demonstrate its practical usability and find a comparably good approximation of the data space topology from relatively few data points.

We developed a Bayesian method to extract macromolecular structure information from sparse single-molecule x-ray free-electron laser diffraction images. The method addresses two possible scenarios. First, using a "seed" structural model, the molecular orientation is determined for each of the provided diffraction images, which are then averaged in three-dimensional reciprocal space. Subsequently, the real space electron density is determined using a relaxed averaged alternating reflections algorithm. In the second approach, the probability that the "seed" model fits to the given set of diffraction images as a whole is determined and used to distinguish between proposed structures. We show that for a given x-ray intensity, unexpectedly, the achievable resolution increases with molecular mass such that structure determination should be more challenging for small molecules than for larger ones. For a sufficiently large number of recorded photons (>200) per diffraction image an M 1/6 scaling is seen. Using synthetic diffraction data for a small glutathione molecule as a challenging test case, successful determination of electron density was demonstrated for 20 000 diffraction patterns with random orientations and an average of 82 elastically scattered and recorded photons per image, also in the presence of up to 50% background noise. The second scenario is exemplified and assessed for three biomolecules of different sizes. In all cases, determining the probability of a structure given set of diffraction patterns allowed successful discrimination between different conformations of the test molecules. A structure model of the glutathione tripeptide was refined in a Monte Carlo simulation from a random starting conformation. Further, effective distinguishing between three differently arranged immunoglobulin domains of a titin molecule and also different states of a ribosome in a tRNA translocation process was demonstrated. These results show that the proposed method is robust and enables structure determination from sparse and noisy x-ray diffraction images of single molecules spanning a wide range of molecular masses.

Abstract. Degeneration of the intervertebral disc (IVD) is the main cause of age-related damage of spinal tissues. Using multipotent mesenchymal stromal cells (MSCs) regenerative medicine intends to restore the IVD components of annulus fibrosus (AF) and nucleus pulposus (NP). In the present study NP cells (NPCs) and MSCs obtained from adolescent patients suffering from scoliosis were used. IVDs and vertebrae were obtained during surgery and subsequently processed in order to establish cultures of NPCs and MSCs. The two cell types were co-cultured in 1-µm pore size insert system (indirect co-culture) or on one surface (direct co-culture). Prior to co-culture in these systems one of the cell types was stained by lipophilic fluorescent dye DiD (red). The results demonstrated that regardless of the cell type, the flow of DiD from stained to non-stained cells was more efficient in the direct co-culture in comparison with the insert system. Moreover, in the direct system the DiD flow was more efficient from MSCs towards NPCs compared with that in the opposite direction. These data indicated that the membrane interchange between the two cell types was asymmetric. To discriminate the subpopulation of cells that underwent membrane interchange, cells were double stained with DiD and DiO (green). In the first part of the experiment NPCs were stained by DiO and MSCs by DiD. In the second, NPCs were stained by DiD and MSCs by DiO. The cells were co-cultured in the direct system for 8 days and subsequently analyzed by flow cytometry and confocal microscopy.This analysis revealed that >50% of cells were stained by the DiO and DiD dyes. NPCs and MSCs formed structures similar to tunnelling nanotubes (TnT). In conclusion, the formation of TnT-like structures is able to promote, phenotypic changes during the direct co-culture of NPCs with MSCs.

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