bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using genetic instruments to estimate interactions in Mendelian Randomization studies
Authors: North Teri-Louise , Davies Neil M , Harrison Sean , Carter Alice R , Hemani Gibran , Sanderson Eleanor , Tilling Kate , Howe Laura D 
Published: February 2019

ABSTRACTBACKGROUNDThe interactive effect of two exposures on an outcome can be confounded. We demonstrate the use of Mendelian Randomization (MR) to estimate unconfounded additive interactions.METHODSUsing simulation, we test an extension to multivariable MR using two-stage least squares to estimate the additive interaction between two continuous exposures on a continuous outcome, including scenarios where one exposure has a causal effect on the other (mediation). The interaction parameters were set to be one third of the main effect’s parameters to impose a limit on the variance explained by interaction terms. We compare the performance of the two-stage least squares estimator to a Factorial MR design, in which genetic risk scores for each exposure are dichotomised to create four groups, akin to a factorial randomized controlled trial. As an illustrative example, we apply factorial MR and the 2SLS estimator to the interactive effect of education and BMI on systolic blood pressure in UK Biobank.RESULTSOur simulations demonstrate that factorial MR has very low statistical power; 5-7% at N=50,000 and 8-23% at N=500,000 across the range of parameters tested. The two-stage least squares estimator had higher power to detect interactions than factorial MR and a lower type I error. For N=500,000, the two-stage least squares estimator had a power ranging from 29.7-92.9% and a type I error ranging from 4-6%. 95% Monte Carlo confidence intervals suggested that the estimator was unbiased to a reasonable degree of accuracy at this sample size. In comparison, the power at N=50,000 was 7-55%.CONCLUSIONSA two-stage least squares estimator using genetic risk scores for each exposure is a more powerful alternative for detecting an unconfounded additive interaction of two exposures on an outcome than existing approaches that rely on dichotomising genetic risk scores, but it requires a large sample size and instruments of adequate strength.
Adhesive defence mucus secretions in the red triangle slug (Triboniophorus graeffei) can incapacitate adult frogs
Authors: Gould John , Valdez Jose W. , Upton Rose 
Published: February 2019

AbstractGastropods are known to secrete mucus for a variety of purposes, including locomotion, reproduction, adhesion to surfaces, and lubrication. A less commonly known function of mucus secretion in this group involves its use as a defence against predation. Among the terrestrial slugs, mucus that serves this particular purpose has been studied for only a handful of species under laboratory conditions, where it is thought to be produced for self-fouling or to make individuals difficult to consume. However, the mechanisms of how these defensive secretions operate and their effectiveness in deterring predation in the natural world have not be described in much detail. In this study, we provide evidence of adhesive mucus secretions in the red triangle slug (Triboniophorus graeffei) as an adaptation against predation. Field observations of a large red-eyed green tree frog (Litoria chloris) trapped in the mucus secretions of a nearbyT. graeffeirevealed that this mucus serves to incapacitate predators rather than just simply as an overall deterrence. Mechanical stimulation ofT. graeffeiunder laboratory conditions revealed that adhesive secretions were produced from discrete sections of the dorsal surface when disturbed, leading to the production of a highly sticky and elastic mucus that was unlike the thin and slippery mucus used during locomotion. The adhesiveness of the defensive secretions was strengthened and reactivated when in contact with water. This appears to not only be the first description of defensive mucus production in this slug species but one of the first natural observations of the use of adhesive defence secretions to incapacitate a predator. The biomechanical properties of this mucus and its ability to maintain and strengthen its hold under wet conditions make it potentially useful in the development of new adhesive materials.
Microclimate predicts frost-hardiness of alpineArabidopsis thalianapopulations better than altitude because the microclimate effect increases with altitude
Authors: Lampei Christian , Wunder Jörg , Wilhalm Thomas , Schmid Karl J. 
Published: February 2019

AbstractIn mountain regions average temperatures decrease at higher altitudes. In addition, microenvironmental conditions can strongly affect microclimate and may counteract average effects of altitude.We investigated winter frost hardiness ofArabidopsis thalianaaccessions originating from 13 sites along altitudinal gradients in the Southern Alps during three winters on an experimental field station on the Swabian Jura and compared levels of frost damage with the observed number of frost days (<1°C) in eight collection sites.We found that frost-hardiness increased with altitude in a log-linear fashion. This is consistent with adaptation to higher frequency of frost conditions, but also indicates a decreasing rate of change in frost hardiness with increasing altitude. Moreover, the number of frost days measured with temperature loggers at the original collection sites correlated much better with frost-hardiness than the altitude of collection sites, suggesting that populations were adapted to their local microclimate. Notably, the variance in frost days across sites increased exponentially with altitude.Together, our results suggest that strong microclimate heterogeneity of high alpine environments may preserve functional genetic diversity in small populations. This challenges the suitability of habitat predictions based on large scale climatic variables (or proxies, such as altitude) for topographically complex areas.
Object Detection Networks and Augmented Reality for Cellular Detection in Fluorescence Microscopy Acquisition and Analysis
Authors: Waithe D , Brown JM , Reglinski K , Diez-Sevilla I , Roberts D , Eggeling Christian 
Published: February 2019

AbstractIn this paper we demonstrate the application of object detection networks for the classification and localization of cells in fluorescence microscopy. We benchmark two leading object detection algorithms across multiple challenging 2-D microscopy datasets as well as develop and demonstrate an algorithm which can localize and image cells in 3-D, in real-time. Furthermore, we exploit the fast processing of these algorithms and develop a simple and effective Augmented Reality (AR) system for fluorescence microscopy systems. Object detection networks are well-known high performance networks famously applied to the task of identifying and localizing objects in photography images. Here we show their application and efficiency for localizing cells in fluorescence microscopy images. Object detection algorithms are typically trained on many thousands of images, which can be prohibitive within the biological sciences due to the cost of imaging and annotating large amounts of data. Through taking different cell types and assays as an example, we show that with some careful considerations it is possible to achieve very high performance with datasets with as few as 26 images present. Using our approach, it is possible for relatively non-skilled users to automate detection of cell classes with a variety of appearances and enable new avenues for automation of conventionally manual fluorescence microscopy acquisition pipelines.
Evaluation of Enhanced Learning Techniques for Segmenting Ischaemic Stroke Lesions in Brain Magnetic Resonance Perfusion Images using a Convolutional Neural Network Scheme
Authors: Malla Carlos Uziel Perez , Valdes Hernandez Maria del C. , Rachmadi Muhammad Febrian , Komura Taku 
Published: February 2019

ABSTRACTMagnetic resonance (MR) perfusion imaging non-invasively measures cerebral perfusion, which describes the blood’s passage through the brain’s vascular network. Therefore it is widely used to assess cerebral ischaemia. Convolutional Neural Networks (CNN) constitute the state-of-the-art method in automatic pattern recognition and hence, in segmentation tasks. But none of the CNN architectures developed to date have achieved high accuracy when segmenting ischaemic stroke lesions, being the main reasons their heterogeneity in location, shape, size, image intensity and texture, especially in this imaging modality. We use a freely available CNN framework, developed for MR imaging lesion segmentation, as core algorithm to evaluate the impact of enhanced machine learning techniques, namely data augmentation, transfer learning and post-processing, in the segmentation of stroke lesions using the ISLES 2017 dataset, which contains expert annotated diffusion-weighted perfusion and diffusion brain MRI of 43 stroke patients. Of all the techniques evaluated, data augmentation with binary closing achieved the best results, improving the mean Dice score in 17% over the baseline model. Consistent with previous works, better performance was obtained in the presence of large lesions.
A global to local genomics analysis ofClostridioides difficileST1/RT027 identifies cryptic transmission events in a northern Arizona healthcare network
Authors: Williamson Charles H.D. , Stone Nathan E. , Nunnally Amalee E. , Hornstra Heidie M. , Wagner David M. , Roe Chandler C. , Vazquez Adam J. , Nandurkar Nivedita , Vinocur Jacob , Terriquez Joel , Gillece John , Travis Jason , Lemmer Darrin , Keim Paul , Sahl Jason W. 
Published: February 2019

AbstractClostridioides difficileis a ubiquitous, diarrheagenic pathogen often associated with healthcare-acquired infections that can cause a range of symptoms from mild, self-limiting disease to toxic megacolon and death. Since the early 2000s, a large proportion ofC. difficilecases have been attributed to the ribotype 027 (RT027) lineage, which is associated with sequence type 1 (ST1) in theC. difficilemultilocus sequence typing (MLST) scheme. The spread of ST1 has been attributed, in part, to resistance to fluoroquinolones used to treat un-related infections, which creates conditions ideal forC. difficilecolonization and proliferation. In this study, we analyzed 27 isolates from a healthcare network in northern Arizona, USA, and 1,352 public ST1 genomes to place locally-sampled isolates into a global context. Core genome, single nucleotide polymorphism (SNP) analysis demonstrated that at least 6 separate introductions of ST1 were observed in healthcare facilities in northern Arizona over an 18-month sampling period. A reconstruction of transmission networks identified potential nosocomial transmission of isolates following two of these introductions, which were only identified via whole genome sequence analysis. Antibiotic resistance heterogeneity was observed among ST1 genomes, including variability in resistance profiles among locally sampled ST1 isolates. To investigate why ST1 genomes are so common globally, we compared all high-qualityC. difficilegenomes and identified that ST1 genomes have gained and lost a number of genomic regions compared to all otherC. difficilegenomes; analyses of other toxigenicC. difficilesequence types demonstrates that this loss may be anomalous and could be related to niche specialization. These results suggest that a combination of antimicrobial resistance and gain and loss of specific genes may explain the prominent association of this sequence type withC. difficileinfection cases worldwide. The degree of genetic variability in ST1 suggests that classifying all ST1 genomes into a quinolone-resistant hypervirulent clone category may not be appropriate. Whole genome sequencing of clinicalC. difficileisolates provides a high-resolution surveillance strategy for monitoring persistence and transmission ofC. difficileand for assessing the performance of infection prevention and control strategies.
Oscillating-flow Thermal Gradient PCR
Authors: Kopparthy Varun L. , Crews Niel D. 
Published: February 2019

ABSTRACTWe report the development of a versatile system based on oscillating-flow methodology in a thermal gradient system for nucleic acid analysis. Analysis of DNA and RNA samples were performed in the device, without additional temperature control and complexity. The technique reported in this study eliminates the need for predetermined fluidic channels for thermocycles, and complexity involved with additional incubation steps required for RNA amplification. A microfluidic device was fabricated using rapid prototyping by simply sandwiching dual side adhesive Kapton tape and a PDMS spacer between glass microscope slides. Amplification of the 181-bp segment of a viral phage DNA (ΦX174) and B2M gene in human RNA samples was demonstrated using the system. The developed system enables simultaneous acquisition of amplification and melt curves, eliminating the need for post-processing.
Updated MS2PIP web server delivers fast and accurate MS2 peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques
Authors: Gabriels Ralf , Martens Lennart , Degroeve Sven 
Published: February 2019

ABSTRACTMS2PIP is a data-driven tool that accurately predicts peak intensities for a given peptide’s fragmentation mass spectrum. Since the release of the MS2PIP web server in 2015, we have brought significant updates to both the tool and the web server. Next to the original models for CID and HCD fragmentation, we have added specific models for the TripleTOF 5600+ mass spectrometer, for TMT-labeled peptides, for iTRAQ-labeled peptides and for iTRAQ-labeled phosphopeptides. Because the fragmentation pattern is heavily altered in each of these cases, these additional models greatly improve the prediction accuracy for their corresponding data types. We have also substantially reduced the computational resources required to run MS2PIP, and have completely rebuilt the web server, which now allows predictions of up to 100.000 peptide sequences in a single request. The MS2PIP web server is freely available at https://iomics.ugent.be/ms2pip/.
Computational Insights Into Avidity of Polymeric Multivalent Binders
Authors: Zumbro E , Witten J , Alexander-Katz A 
Published: February 2019

AbstractMultivalent binding interactions are commonly found throughout biology to enhance weak monovalent binding such as between glycoligands and protein receptors. Designing multivalent polymers to bind to viruses and toxic proteins is a promising avenue for inhibiting their attachment and subsequent infection of cells. Several studies have focused on oligomeric multivalent inhibitors and how changing parameters such as ligand shape and size, and linker length and flexibility affect binding. However, experimental studies of how larger structural parameters of multivalent polymers such as degree of polymerization affect binding avidity to targets have mixed results with some finding an improvement with longer polymers and some finding no effect. Here, we use Brownian dynamics simulations to provide a theoretical understanding of how degree of polymerization affects the binding avidity of multivalent polymers. We show that longer polymers increase binding avidity to multivalent targets, but reach a limit in binding avidity at high degrees of polymerization. We also show that when interacting with multiple targets simultaneously, longer polymers are able to use inter-target interactions to promote clustering and improve binding efficiency. We expect our results to narrow the design space for optimizing the structure and effectiveness of multivalent inhibitors, as well as be useful to understand biological design strategies for multivalent binding.
Development of a fixed list of descriptors for the qualitative behavioural assessment of shelter dogs
Authors: Arena Laura , Wemelsfelder Françoise , Messori Stefano , Ferri Nicola , Barnard Shanis 
Published: February 2019

ABSTRACTThe shelter environment may have a severe impact on the quality of life of dogs, and there is thus a need to develop valid tools to assess their welfare. These tools should be sensitive not only to the animals’ physical health but also to their mental health, including the assessment of positive and negative emotions. Qualitative Behaviour Assessment (QBA) is an integrative ‘whole animal’ measure that captures the expressive quality of an animal’s demeanour, using descriptors such as ‘relaxed’, ‘anxious’, and ‘playful’. In this study, for the first time, we developed and tested a fixed-list of qualitative QBA descriptors for application to dogs living in kennels. A list of 20 QBA descriptors was developed based on literature search and an expert opinion survey. Inter-observer reliability was investigated by asking 11 observers to use these descriptors to score 13 video clips of kennelled dogs. Principal Component Analysis (PCA) was used to extract four main dimensions together explaining 70.9% of the total variation between clips. PC1 characterised curious/playful/excitable, sociable demeanour, PC2 ranged from comfortable/relaxed to anxious/nervous/stressed expression, PC3 described fearful demeanour, and PC4 characterized bored/depressed demeanour. Observers’ agreement on the ranking of video clips on these four expressive dimensions was good (Kendall’s W: 0.60-0.80). ANOVA showed a significant effect of observer on mean clip score on all PCs (p<0.05) due to a few observers scoring differently from the rest of the group. These results indicate the potential of the proposed list of QBA terms for sheltered dogs to serve as a non-invasive, easy-to-use assessment tool. However, the observers’ effect on mean scores points towards the need for adequate observer training. The QBA scoring tool can be integrated with existing welfare assessment protocols for shelter dogs and strengthen the power of those protocols to assess and evaluate the animals’ experience in shelters.
Unscrambling Fluorophore Blinking for Comprehensive Cluster Detection via Photoactivated Localization Microscopy
Authors: Platzer Rene , Rossboth Benedikt K. , Schneider Magdalena C. , Sevcsik Eva , Baumgart Florian , Stockinger Hannes , Schütz Gerhard J. , Huppa Johannes B. , Brameshuber Mario 
Published: February 2019

ABSTRACTDetermining nanoscale protein distribution via Photoactivated Localization Microscopy (PALM) mandates precise knowledge of the applied fluorophore’s blinking properties to counteract overcounting artifacts that distort the resulting biomolecular distributions. Here, we present a readily applicable methodology to determine, optimize and quantitatively account for the blinking behavior of any PALM-compatible fluorophore. Using a custom-designed platform we revealed complex blinking of two photoswitchable fluorescence proteins (PS-CFP2 and mEOS3.2) and two photoactivatable organic fluorophores (PA Janelia Fluor 549 and Abberior CAGE 635) with blinking cycles on time scales of several seconds. Incorporating such detailed information in our simulation-based analysis package allowed for robust evaluation of molecular clustering based on individually recorded single molecule localization maps.GRAPHICAL ABSTRACT
Microtubules form by progressively faster tubulin accretion, not by nucleation-elongation
Authors: Rice Luke M. , Moritz Michelle , Agard David A. 
Published: February 2019

AbstractMicrotubules are dynamic polymers that play fundamental roles in all eukaryotes. Despite their importance, how new microtubules form is poorly understood. Textbooks have focused on variations of a nucleation-elongation mechanism in which monomers rapidly equilibrate with an unstable oligomer (nucleus) that limits the rate of polymer formation; once formed, the polymer then elongates efficiently from this nucleus by monomer addition. Such models faithfully describe actin assembly, but they fail to account for how more complex polymers like hollow microtubules assemble. Here we articulate a new model for microtubule formation that has three key features: i) microtubules initiate via rectangular, sheet-like structures which grow faster the larger they become; ii) the dominant pathway proceeds via accretion, stepwise addition of longitudinal or lateral layers; iii) a ‘straightening penalty’ to account for the energetic cost of tubulin’s curved-to-straight conformational transition. This model can quantitatively fit experimental assembly data, providing new insights into biochemical determinants and assembly pathways for microtubule nucleation.
A Type III-A CRISPR-Cas system employs degradosome nucleases to ensure robust immunity
Authors: Chou-Zheng Lucy , Hatoum-Aslan Asma 
Published: February 2019

AbstractCRISPR-Cas systems provide sequence-specific immunity against phages and mobile genetic elements using CRISPR-associated nucleases guided by short CRISPR RNAs (crRNAs). Type III systems exhibit a robust immune response that can lead to the extinction of a phage population, a feat coordinated by a multi-subunit effector complex that destroys invading DNA and RNA. Here, we demonstrate that a model Type III system in Staphylococcus epidermidis relies upon the activities of two degradosome-associated nucleases, PNPase and RNase J2, to mount a successful defense. Genetic, molecular, and biochemical analyses reveal that PNPase promotes crRNA maturation, and both nucleases are required for efficient clearance of phage-derived nucleic acids. Furthermore, functional assays show that RNase J2 is essential for immunity against diverse mobile genetic elements originating from plasmid and phage. Altogether, our observations reveal the evolution of a critical collaboration between two nucleic acid degrading machines which ensures cell survival when faced with phage attack.
Symmetry transitions during gating of the TRPV2 ion channel in lipid membranes
Authors: Zubcevic Lejla , Hsu Allen L. , Borgnia Mario J. , Lee Seok-Yong 
Published: February 2019

AbstractThe Transient Receptor Potential Vanilloid 2 (TRPV2) channel is a member of the temperature-sensing thermoTRPV family. Recent advances in cryo-electronmicroscopy (cryo-EM) and X-ray crystallography have provided many important insights into the gating mechanisms of thermoTRPV channels. Interestingly, crystallographic studies of ligand-dependent TRPV2 gating have shown that the TRPV2 channel adopts two-fold symmetric arrangements during the gating cycle. However, it was unclear if crystal packing forces played a role in stabilizing the two-fold symmetric arrangement of the channel. Here we employ cryo-EM to elucidate the structure of full-length rabbit TRPV2 in complex with the agonist resiniferatoxin (RTx) in nanodiscs and amphipol. We show that RTx induces two-fold symmetric conformations of TRPV2 in both environments. However, the two-fold symmetry is more pronounced in the native-like lipid environment of the nanodiscs. Our data offers insights into a gating pathway in TRPV2 involving symmetry transitions.
Opportunities for improved surveillance and control of infectious diseases from age-specific case data
Authors: Rodríguez-Barraquer Isabel , Salje Henrik , Cummings Derek AT 
Published: February 2019

AbstractOne of the challenges faced by global disease surveillance efforts is the lack of comparability across systems. Reporting commonly focuses on overall incidence, despite differences in surveillance quality between and within countries. For most immunizing infections, the age-distribution of incident cases provides a more robust picture of trends in transmission. We present a framework to estimate transmission intensity for dengue virus from age-specific incidence data, and apply it to 363 administrative units in Thailand, Colombia, Brazil and Mexico. Our estimates correlate well with those derived from seroprevalence data (the gold-standard), capture the expected spatial heterogeneity in risk, and correlate with known environmental drivers of transmission. We show how this approach could be used to guide the implementation of control strategies such as vaccination. Since age-specific counts are routinely collected by many surveillance systems, they represent a unique opportunity to further our understanding of disease burden and risk for many diseases.