Periodic limb movements in patients with suspected obstructive sleep apnea without comorbid conditions.

Background: Periodic limb movement disorder (PLMD) and obstructive sleep apnea (OSA) are overlapping clinical syndromes with common risk factors. However, current literature has failed to establish a clear pathophysiological link between them. Thus, little is known about periodic limb movements (PLM) in otherwise healthy patients with suspected OSA. Methods: We performed a retrospective analysis of 112 patients (age: 44.5 ± 12.0 years, 14.3% female) with suspected OSA who underwent full night polysomnography for the first time. Patients with chronic diseases of any kind, recent infections, malignancies, or daily or regular use of any type of medication were excluded. Group comparisons were made based on the severity of OSA (using the apnea hypopnea index, AHI) or the periodic limb movement index (PLMI). Results: Both, PLMI and the total number of periodic limb movements during sleep (PLMS), showed a significant increase in patients with severe OSA. In addition, AHI and apnea index (AI) were significantly higher in patients with PLMI >15/h, with a similar trend for hypopnea index (HI) (p < 0.001, p < 0.001, and p > 0.05, respectively). PLMI was significantly positive correlated with AHI, AI, and HI (r = 0.392, p < 0.001; r = 0.361, p < 0.001; and r = 0.212, p < 0.05, respectively). Patients with PLMI >15/h were significantly older (p < 0.001). There was no significant association between body mass index (BMI) and PLMI >15/h. Conclusion: We found a significant association between the severity of OSA and PLM in our study population with suspected OSA but without other comorbidities. PLMI and PLMS were significantly increased in patients with severe OSA. Future prospective studies with larger collectives should verify the presented results and should include mechanistic aspects in their evaluation.

Review of Diet Quality Indices that can be Applied to the Environmental Assessment of Foods and Diets.

PURPOSE OF REVIEW: The aim was to identify indices of diet quality and health that could be applied to the environmental assessment of foods in order to provide metrics that collectively assess nutritional, health and environmental dimensions. RECENT FINDINGS: The review identified five major groups of indices: nutrient-food quantity-based; guideline-based; diversity-based; nutrient quality-based; health-based. Nutrient-food quantity-based and guideline type indices were the most frequently used to evaluate diet quality. Scaled assessment using a nutritional functional unit is the most common integration of diet quality with the environmental analysis of foods. There are fewer indices that measure the heath impacts of foods, but epidemiological dietary risk factors seem a promising approach to integrate diet and health impacts into the environmental assessment of foods. Five groups of nutritional and health indices were identified that can be applied when performing an environmental assessment of foods. This review proposes different methodological insights when doing such assessments to ensure transparency and comparability of the results.

Large-scale benchmark study of survival prediction methods using multi-omics data.

Multi-omics data, that is, datasets containing different types of high-dimensional molecular variables, are increasingly often generated for the investigation of various diseases. Nevertheless, questions remain regarding the usefulness of multi-omics data for the prediction of disease outcomes such as survival time. It is also unclear which methods are most appropriate to derive such prediction models. We aim to give some answers to these questions through a large-scale benchmark study using real data. Different prediction methods from machine learning and statistics were applied on 18 multi-omics cancer datasets (35 to 1000 observations, up to 100 000 variables) from the database 'The Cancer Genome Atlas' (TCGA). The considered outcome was the (censored) survival time. Eleven methods based on boosting, penalized regression and random forest were compared, comprising both methods that do and that do not take the group structure of the omics variables into account. The Kaplan-Meier estimate and a Cox model using only clinical variables were used as reference methods. The methods were compared using several repetitions of 5-fold cross-validation. Uno's C-index and the integrated Brier score served as performance metrics. The results indicate that methods taking into account the multi-omics structure have a slightly better prediction performance. Taking this structure into account can protect the predictive information in low-dimensional groups-especially clinical variables-from not being exploited during prediction. Moreover, only the block forest method outperformed the Cox model on average, and only slightly. This indicates, as a by-product of our study, that in the considered TCGA studies the utility of multi-omics data for prediction purposes was limited. Contact:moritz.herrmann@stat.uni-muenchen.de, +49 89 2180 3198 Supplementary information: Supplementary data are available at Briefings in Bioinformatics online. All analyses are reproducible using R code freely available on Github.

Bacterial lipopolysaccharides form physically cross-linked, two-dimensional gels in the presence of divalent cations.

We established a bacterial membrane model with monolayers of bacterial lipopolysaccharides (LPS Re and LPS Ra) and quantified their viscoelastic properties by using an interfacial stress rheometer coupled to a Langmuir film balance. LPS Re monolayers exhibited purely viscous behaviour in the absence of calcium ions, while the same monolayers underwent a viscous-to-elastic transition upon compression in the presence of Ca(2+). Our results demonstrated for the first time that LPSs in bacterial outer membranes can form two-dimensional elastic networks in the presence of Ca(2+). Different from LPS Re monolayers, the LPS Ra monolayers showed a very similar rheological transition both in the presence and absence of Ca(2+), suggesting that longer saccharide chains can form 2D physical gels even in the absence of Ca(2+). By exposure of the monolayers to the antimicrobial peptide protamine, we could directly monitor the differences in resistance of bacterial membranes according to the presence of calcium.

Comparative analysis of metazoan chromatin organization.

Genome function is dynamically regulated in part by chromatin, which consists of the histones, non-histone proteins and RNA molecules that package DNA. Studies in Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular mechanisms of genome function in humans, and have revealed conservation of chromatin components and mechanisms. Nevertheless, the three organisms have markedly different genome sizes, chromosome architecture and gene organization. On human and fly chromosomes, for example, pericentric heterochromatin flanks single centromeres, whereas worm chromosomes have dispersed heterochromatin-like regions enriched in the distal chromosomal 'arms', and centromeres distributed along their lengths. To systematically investigate chromatin organization and associated gene regulation across species, we generated and analysed a large collection of genome-wide chromatin data sets from cell lines and developmental stages in worm, fly and human. Here we present over 800 new data sets from our ENCODE and modENCODE consortia, bringing the total to over 1,400. Comparison of combinatorial patterns of histone modifications, nuclear lamina-associated domains, organization of large-scale topological domains, chromatin environment at promoters and enhancers, nucleosome positioning, and DNA replication patterns reveals many conserved features of chromatin organization among the three organisms. We also find notable differences in the composition and locations of repressive chromatin. These data sets and analyses provide a rich resource for comparative and species-specific investigations of chromatin composition, organization and function.