Flexible non-parametric tests of sample exchangeability and feature independence

In scientific studies involving analyses of multivariate data, two questions often arise for the researcher. First, is the sample exchangeable, meaning that the joint distribution of the sample is invariant to the ordering of the units? Second, are the features independent of one another, or can the features be grouped so that the groups are mutually independent? We propose a non-parametric approach that addresses these two questions. Our approach is conceptually simple, yet fast and flexible. It controls the Type I error across realistic scenarios, and handles data of arbitrary dimensions by leveraging large-sample asymptotics. In the exchangeability detection setting, through extensive simulations and a comparison against unsupervised tests of stratification based on random matrix theory, we find that our approach compares favorably in various scenarios of interest. We apply our method to problems in population and statistical genetics, including stratification detection and linkage disequilibrium splitting. We also consider other application domains, applying our approach to post-clustering single-cell chromatin accessibility data and World Values Survey data, where we show how users can partition features into independent groups, which helps generate new scientific hypotheses about the features.Comment: Main Text: 25 pages Supplementary Material: 39 page

Improved delineation of short cortical association fibers and gray/white matter boundary using whole-brain three-dimensional diffusion tensor imaging at submillimeter spatial resolution.

Recent emergence of human connectome imaging has led to a high demand on angular and spatial resolutions for diffusion magnetic resonance imaging (MRI). While there have been significant growths in high angular resolution diffusion imaging, the improvement in spatial resolution is still limited due to a number of technical challenges, such as the low signal-to-noise ratio and high motion artifacts. As a result, the benefit of a high spatial resolution in the whole-brain connectome imaging has not been fully evaluated in vivo. In this brief report, the impact of spatial resolution was assessed in a newly acquired whole-brain three-dimensional diffusion tensor imaging data set with an isotropic spatial resolution of 0.85 mm. It was found that the delineation of short cortical association fibers is drastically improved as well as the definition of fiber pathway endings into the gray/white matter boundary-both of which will help construct a more accurate structural map of the human brain connectome

Myonuclear accretion is a determinant of exercise-induced remodeling in skeletal muscle.

Skeletal muscle adapts to external stimuli such as increased work. Muscle progenitors (MPs) control muscle repair due to severe damage, but the role of MP fusion and associated myonuclear accretion during exercise are unclear. While we previously demonstrated that MP fusion is required for growth using a supra-physiological model (Goh and Millay, 2017), questions remained about the need for myonuclear accrual during muscle adaptation in a physiological setting. Here, we developed an 8 week high-intensity interval training (HIIT) protocol and assessed the importance of MP fusion. In 8 month-old mice, HIIT led to progressive myonuclear accretion throughout the protocol, and functional muscle hypertrophy. Abrogation of MP fusion at the onset of HIIT resulted in exercise intolerance and fibrosis. In contrast, ablation of MP fusion 4 weeks into HIIT, preserved exercise tolerance but attenuated hypertrophy. We conclude that myonuclear accretion is required for different facets of exercise-induced adaptive responses, impacting both muscle repair and hypertrophic growth

Machine learning predicts 3D printing performance of over 900 drug delivery systems

Three-dimensional printing (3DP) is a transformative technology that is advancing pharmaceutical research by producing personalized drug products. However, advances made via 3DP have been slow due to the lengthy trial-and-error approach in optimization. Artificial intelligence (AI) is a technology that could revolutionize pharmaceutical 3DP through analyzing large datasets. Herein, literature-mined data for developing AI machine learning (ML) models was used to predict key aspects of the 3DP formulation pipeline and in vitro dissolution properties. A total of 968 formulations were mined and assessed from 114 articles. The ML techniques explored were able to learn and provide accuracies as high as 93% for values in the filament hot melt extrusion process. In addition, ML algorithms were able to use data from the composition of the formulations with additional input features to predict the drug release of 3D printed medicines. The best prediction was obtained by an artificial neural network that was able to predict drug release times of a formulation with a mean error of ±24.29 min. In addition, the most important variables were revealed, which could be leveraged in formulation development. Thus, it was concluded that ML proved to be a suitable approach to modelling the 3D printing workflow

In crystallo-screening for discovery of human norovirus 3C-like protease inhibitors.

Outbreaks of human epidemic nonbacterial gastroenteritis are mainly caused by noroviruses. Viral replication requires a 3C-like cysteine protease (3CLpro) which processes the 200 kDa viral polyprotein into six functional proteins. The 3CLpro has attracted much interest due to its potential as a target for antiviral drugs. A system for growing high-quality crystals of native Southampton norovirus 3CLpro (SV3CP) has been established, allowing the ligand-free crystal structure to be determined to 1.3 Å in a tetrameric state. This also allowed crystal-based fragment screening to be performed with various compound libraries, ultimately to guide drug discovery for SV3CP. A total of 19 fragments were found to bind to the protease out of the 844 which were screened. Two of the hits were located at the active site of SV3CP and showed good inhibitory activity in kinetic assays. Another 5 were found at the enzyme's putative RNA-binding site and a further 11 were located in the symmetric central cavity of the tetramer

Room temperature plasmon laser by total internal reflection

Plasmon lasers create and sustain intense and coherent optical fields below light's diffraction limit with the unique ability to drastically enhance light-matter interactions bringing fundamentally new capabilities to bio-sensing, data storage, photolithography and optical communications. However, these important applications require room temperature operation, which remains a major hurdle. Here, we report a room temperature semiconductor plasmon laser with both strong cavity feedback and optical confinement to 1/20th of the wavelength. The strong feedback arises from total internal reflection of surface plasmons, while the confinement enhances the spontaneous emission rate by up to 20 times.Comment: 8 Page, 2 Figure

Evaluating the feasibility of using candidate DNA barcodes in discriminating species of the large Asteraceae family

<p>Abstract</p> <p>Background</p> <p>Five DNA regions, namely, <it>rbcL</it>, <it>matK</it>, ITS, ITS2, and <it>psbA-trnH</it>, have been recommended as primary DNA barcodes for plants. Studies evaluating these regions for species identification in the large plant taxon, which includes a large number of closely related species, have rarely been reported.</p> <p>Results</p> <p>The feasibility of using the five proposed DNA regions was tested for discriminating plant species within Asteraceae, the largest family of flowering plants. Among these markers, ITS2 was the most useful in terms of universality, sequence variation, and identification capability in the Asteraceae family. The species discriminating power of ITS2 was also explored in a large pool of 3,490 Asteraceae sequences that represent 2,315 species belonging to 494 different genera. The result shows that ITS2 correctly identified 76.4% and 97.4% of plant samples at the species and genus levels, respectively. In addition, ITS2 displayed a variable ability to discriminate related species within different genera.</p> <p>Conclusions</p> <p>ITS2 is the best DNA barcode for the Asteraceae family. This approach significantly broadens the application of DNA barcoding to resolve classification problems in the family Asteraceae at the genera and species levels.</p

Head Position in Stroke Trial (HeadPoST)- sitting-up vs lying-flat positioning of patients with acute stroke: study protocol for a cluster randomised controlled trial

Background Positioning a patient lying-flat in the acute phase of ischaemic stroke may improve recovery and reduce disability, but such a possibility has not been formally tested in a randomised trial. We therefore initiated the Head Position in Stroke Trial (HeadPoST) to determine the effects of lying-flat (0°) compared with sitting-up (≥30°) head positioning in the first 24 hours of hospital admission for patients with acute stroke. Methods/Design We plan to conduct an international, cluster randomised, crossover, open, blinded outcome-assessed clinical trial involving 140 study hospitals (clusters) with established acute stroke care programs. Each hospital will be randomly assigned to sequential policies of lying-flat (0°) or sitting-up (≥30°) head position as a ‘business as usual’ stroke care policy during the first 24 hours of admittance. Each hospital is required to recruit 60 consecutive patients with acute ischaemic stroke (AIS), and all patients with acute intracerebral haemorrhage (ICH) (an estimated average of 10), in the first randomised head position policy before crossing over to the second head position policy with a similar recruitment target. After collection of in-hospital clinical and management data and 7-day outcomes, central trained blinded assessors will conduct a telephone disability assessment with the modified Rankin Scale at 90 days. The primary outcome for analysis is a shift (defined as improvement) in death or disability on this scale. For a cluster size of 60 patients with AIS per intervention and with various assumptions including an intracluster correlation coefficient of 0.03, a sample size of 16,800 patients at 140 centres will provide 90 % power (α 0.05) to detect at least a 16 % relative improvement (shift) in an ordinal logistic regression analysis of the primary outcome. The treatment effect will also be assessed in all patients with ICH who are recruited during each treatment study period. Discussion HeadPoST is a large international clinical trial in which we will rigorously evaluate the effects of different head positioning in patients with acute stroke. Trial registration ClinicalTrials.gov identifier: NCT02162017 (date of registration: 27 April 2014); ANZCTR identifier: ACTRN12614000483651 (date of registration: 9 May 2014). Protocol version and date: version 2.2, 19 June 2014

A Unifying Model of Genome Evolution Under Parsimony

We present a data structure called a history graph that offers a practical basis for the analysis of genome evolution. It conceptually simplifies the study of parsimonious evolutionary histories by representing both substitutions and double cut and join (DCJ) rearrangements in the presence of duplications. The problem of constructing parsimonious history graphs thus subsumes related maximum parsimony problems in the fields of phylogenetic reconstruction and genome rearrangement. We show that tractable functions can be used to define upper and lower bounds on the minimum number of substitutions and DCJ rearrangements needed to explain any history graph. These bounds become tight for a special type of unambiguous history graph called an ancestral variation graph (AVG), which constrains in its combinatorial structure the number of operations required. We finally demonstrate that for a given history graph $G$, a finite set of AVGs describe all parsimonious interpretations of $G$, and this set can be explored with a few sampling moves.Comment: 52 pages, 24 figure

Strategies to Suppress Hydrogen-Consuming Microorganisms Affect Macro and Micro Scale Structure and Microbiology of Granular Sludge

Treatment of anaerobic granules with heat and two chemical treatments, contacting with 2-bromoethanesulfonate (BES) and with BESþChloroform, were applied to suppress hydrogen-consuming microorganisms. Three mesophilic expanded granular sludge bed (EGSB) reactors— RHeat, RBES, and RBESþChlo—were inoculated with the treated sludges and fed with synthetic sugar-based wastewater (5 gCOD L 1, HRT 20–12 h). Morphological integrity of granules and bacterial communities were assessed by quantitative image analysis and 16S rRNA gene based techniques, respectively. Hydrogen production in RHeat was under 300mLH2 L 1 day 1, with a transient peak of 1,000 mLH2 L 1 day 1 after decreasing HRT. In RBESþChlo hydrogen production rate did not exceed 300mLH2 L 1 day 1 and there was granule fragmentation, release of free filaments from aggregates, and decrease of granule density. In RBES, there was an initial period with unstable hydrogen production, but a pulse of BES triggered its production rate to 700 200mLH2 L 1 day 1. This strategy did not affect granules structure significantly. Bacteria branching within Clostridiaceae and Ruminococcaceae were present in this sludge. This work demonstrates that, methods applied to suppress H2-consuming microorganisms can cause changes in the macro- and microstructure of granular sludge, which can be incompatible with the operation of high-rate reactors.European Community fund FEDER Contract grant number: FCOMP-01-0124-FEDER-007087; PTDC/BIO/69745/2006; SFRH/ BD/29823/2006; SFRH/BD/48965/2008Fundação para a Ciência e a Tecnologia (FCT