bluuebunny/crossref_metadata_2025 huggingface dataset:
NMR Methods for Quantitative Isotopomer Rates in Real-Time Metabolism of Cells
Authors: Reed Michelle AC , Roberts Jennie , Gierth Peter , Kupče Ēriks , Günther Ulrich L
Published: February 2019

Tracer-based metabolism is becoming increasingly important to study metabolic mechanisms in cells. NMR offers several approaches to measure label incorporation in metabolites, including 13C and 1H-detected spectra. The latter are generally more sensitive but quantification depends on the proton carbon 1JCH coupling constant which varies significantly between different metabolites. It is therefore not possible to have one experiment optimised for all metabolites and quantification of 1H-edited spectra such as HSQCs requires precise knowledge of coupling constants. Increasing interest in tracer-based and metabolic flux analysis requires robust analyses with reasonably small acquisition times. Here we compare 13C-filtered and 13C-edited methods for quantification with a special focus towards application in real-time NMR of cancer cells under near-physiological conditions. We find an approach using a double-filter most suitable and sufficiently robust to reliably obtain 13C-incorporations from difference spectra. This is demonstrated for JJN3 multiple myeloma cells processing glucose over 24h.
Drying enhances signal intensity for global GC-MS metabolomics
Authors: Liebeke Manuel , Puskas Erik
Published: February 2019

We report here that a straightforward change of standard derivatization procedure for GC-MS metabolomics is leading to a strong increase in metabolite signal intensity. Drying samples between methoxymation and trimethylsilylation significantly increased signals by two-to tenfold in extracts of yeast cells, plant and animal tissue and human urine. This easy step reduces the cost of sample material and the need for expensive new hardware.
A shared pathway of exosome biogenesis operates at plasma and endosome membranes
Authors: Fordjour Francis K. , Daaboul George G. , Gould Stephen J.
Published: February 2019

Eukaryotic cells secrete exosomes, which are small (~30-200 nm dia.), single membrane-bound organelles that transmit signals and molecules to other cells. Exosome-mediated signaling contributes to diverse physiological and disease processes, rendering their biogenesis of high biomedical importance. The prevailing hypothesis is that exosomes bud exclusively at endosome membranes and are released only upon endosome fusion with the plasma membrane. Here we tested this hypothesis by examining the intracellular sorting and exosomal secretion of the exosome cargo proteins CD63, CD9, and CD81. We report here that CD9 and CD81 are both localized to the plasma membrane and bud >5-fold more efficiently than endosome-localized CD63. Furthermore, we show that redirecting CD63 from endosomes to the plasma membrane by mutating its endocytosis signal (CD63/Y235A) increased its exosomal secretion ~6-fold, whereas redirecting CD9 to endosomes by adding an endosome targeting signal (CD9/YEVM) reduced its exosomal secretion ~5-fold. These data demonstrate that the plasma membrane is a major site of exosome biogenesis, and more importantly, that cells possess a common pathway for exosome protein budding that operates at both plasma and endosome membranes. Using a combination of single-particle interferometry reflectance (SPIR) imaging and immunofluorescence (IF) microscopy, we also show that variations in exosome composition are controlled by differential intracellular protein trafficking rather than by separate mechanisms of exosome biogenesis. This new view of exosome biogenesis offers a simple explanation for the pronounced compositional heterogeneity of exosomes and a validated roadmap for exosome engineering.

This study of exosome cargo protein budding reveals that cells use a common pathway for budding exosomes from plasma and endosome membranes, providing a new mechanistic explanation for exosome heterogeneity and a rational roadmap for exosome engineering.
Discovering dynamic functional networks in the human neonatal brain with electric source imaging
Authors: Mehrkanoon Steve
Published: February 2019

When the human brain manifests the birth of organised communication among local and large-scale neuronal populations activity remains undescribed. We report, in resting-state EEG source-estimates of 100 infants at term age, the existence of macro-scale dynamic functional connectivity, which have rich topological organisations, distinct spectral fingerprints and scale-invariance temporal dynamics. These functional networks encompass the default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor and visual-limbic system confined in the delta and low-alpha frequency intervals (1-8 Hz). The temporal dynamics of these networks not only are nested within much slower timescale (¡ 0.1 Hz) but also correlated in a hierarchical leading-following organisation. We show that the anatomically constrained richly organised spatial topologies, spectral contents and temporal fluctuations of resting-state networks reflect an established intrinsic dynamic functional connectome in the human brain at term age. The graph theoretical analysis of the spatial architectures of the networks revealed small-world topology and distinct rich-club organisations of interconnected cortical hubs that exhibit rich synchronous dynamics at multiple timescales. The approach opens new avenues to advance our understanding about the early configuration organisation of dynamic networks in the human brain and offers a novel monitoring platform to investigate functional brain network development in sick preterm infants.
Draft Genome Assembly and Annotation of Red Raspberry Rubus Idaeus
Authors: Wight Haley , Zhou Junhui , Li Muzi , Hannenhalli Sridhar , Mount Stephen M. , Liu Zhongchi
Published: February 2019

The red raspberry, Rubus idaeus, is widely distributed in all temperate regions of Europe, Asia, and North America and is a major commercial fruit valued for its taste, high antioxidant and vitamin content. However, Rubus breeding is a long and slow process hampered by limited genomic and molecular resources. Genomic resources such as a complete genome sequencing and transcriptome will be of exceptional value to improve research and breeding of this high value crop. Using a hybrid sequence assembly approach including data from both long and short sequence reads, we present the first assembly of the Rubus idaeus genome (Joan J. variety). The de novo assembled genome consists of 2,145 scaffolds with a genome completeness of 95.3% and an N50 score of 638 KB. Leveraging a linkage map, we anchored 80.1% of the genome onto seven chromosomes. Using over 1 billion paired-end RNAseq reads, we annotated 35,566 protein coding genes with a transcriptome completeness score of 97.2%. The Rubus idaeus genome provides an important new resource for researchers and breeders.
Implementations of the chemical structural and compositional similarity metric in R and Python
Authors: Brejnrod Asker , Ernst Madeleine , Dworzynski Piotr , Rasmussen Lasse Buur , Dorrestein Pieter C. , van der Hooft Justin J.J. , Arumugam Manimozhiyan
Published: February 2019

Motivation

Tandem mass spectrometry (MS/MS) has the potential to substantially improve metabolomics by acquiring spectra of fragmented ions. These fragmentation spectra can be represented as a molecular network, by measuring cosine distances between them, thus identifying signals from the same or similar molecules. Metrics that enable comparison between pairs of samples based on their metabolite profiles are in great need. Taking inspiration from the successful phylogeny-aware beta-diversity measures used in microbiome research, integrating chemical similarity information about the features in addition to their abundances could lead to better insights when comparing metabolite profiles. Chemical Structural and Compositional Similarity (CSCS) is a recently published similarity metric comparing the full set of signals and their chemical similarity between two samples. Efficient, scalable and easily accessible implementations of this algorithm is currently lacking. Here, we present an easily accessible and scalable implementation of CSCS in both python and R, including a version not weighted by intensity information.

Results

We provide a new implementation of the CSCS algorithm that is over 300 times faster than the published implementation in R, making the algorithm suitable for large-scale metabolomics applications. We also show that adding chemical information enriches existing methods. Furthermore, the R implementation includes functions for exporting molecular networks directly from the mass spectral molecular networking platform GNPS for ease of use for downstream applications.

Contact

brejnrod@sund.ku.dk

Availability

github.com/askerdb/rCSCS,github.com/askerdb/pyCSCS
Optimality of the spontaneous prophage induction rate
Authors: Cortes Michael , Krog Jonathan , Balázsi Gábor
Published: February 2019

Lysogens are bacterial cells that have survived after being infected by bacterial viruses called bacteriophages. Instead of being killed by the virus, the infected cell survives by integrating the viral DNA into its own genome. This is only possible with “temperate” bacteriophages which do not always lyse their host to reproduce, but sometimes replicate passively using the lysogenic pathway. After an infection resulting in lysogeny, the lysogen continues to grow and divide normally, seemingly unaffected by the integrated viral genome which is now referred to as a prophage. However, the prophage can have an impact on the host’s phenotype and overall fitness in certain environments. This makes competition between the lysogen and its nonlysogen counterpart possible because both cells have different genomes and potentially different growth rates. Additionally, the prophages within the lysogens are capable of spontaneously reverting back to the lytic pathway via spontaneous prophage induction (SPI), causing death of the lysogen and the release of new progeny phages. These new phages can then lyse or lysogenize other susceptible nonlysogens, thereby impacting the competition between lysogens and nonlysogens. In a scenario with differing growth rates, it is not clear whether SPI would be beneficial or detrimental to the lysogens since it directly causes cell death but also attacks nonlysogenic competitiors, either lysing or lysogenizing them. In this work we study the evolutionary dynamics of a mixture of lysogens and nonlysogens and derive general conditions on the rate of SPI resulting in lysogens displacing nonlysogens. We show that there exists an optimal SPI rate, and apply the model to bacteriophageλ. We find that the model can explain why the experimentally measured SPI rate for phageλis so low. We also investigate the impact of stochasticity and conclude that even at low copy numbers the SPI rate can still be fairly low while still providing an advantage to the lysogens.
Novel Methodology to Detect Physical Interaction of Inositol Phospholipid with Potassium Ion Channel Using Luminescence Resonance Energy Transfer
Authors: Chin Felix , Cheng Ping-Chin
Published: February 2019

Membrane proteins like ion channels are located within a lipid environment. While the bulk lipids provide a supporting architecture for proteins, some lipids also play important signaling roles in modulating protein activity. This modulation can occur through direct interaction with proteins without involving second messenger pathways. Phosphoinositides are one such lipids, which have been implicated in interactions with a diverse range of proteins and such interactions mediate a variety of cellular functions. Towards understanding how these lipids play their roles in regulating protein functions It is necessary to detect interactions between proteins and lipids and to identify binding sites on proteins. However, detection of protein-lipid interactions has been difficult especially in their native environment because only a fraction of lipids are bound to proteins while the bulk is freely diffusing. The purpose of this study is to develop an experimental method capable of identifying protein-lipid interactions in membrane environments. The strategy involves luminescence energy transfer to locally illuminate lipids around proteins thereby suppressing the large background of light from unbound lipid molecules. The approach is applied to an inward rectifier potassium ion channel for its interactions with phosphoinositide lipids. Experiments show that it can successfully detect phosphoinositides bound to proteins, and when combined with mutagenic approaches, can further identify binding site. The approach thus provides a valuable methodology for probing protein-lipid interactions in a native-like lipid environment.
Neuronal memory for language processing
Authors: Fitz Hartmut , Uhlmann Marvin , van den Broek Dick , Duarte Renato , Hagoort Peter , Petersson Karl Magnus
Published: February 2019

In language processing, an interpretation is computed incrementally within memory while utterances unfold in time. Here, we investigate the nature of this processing memory in a spiking network model of sentence comprehension. We show that the history dependence of neuronal responses endows circuits of biological neurons with adequate memory to assign semantic roles and resolve binding relations between words in a stream of language input. A neurobiological read-write memory is proposed where short-lived spiking activity encodes information into coupled dynamic variables that move at slower timescales. This state-dependent network does not rely on persistent activity, excitatory feedback, or synaptic plasticity for storage. Instead, information is maintained in adaptive neuronal conductances and can be accessed directly during comprehension without cued retrieval of previous input words. This work provides a step towards a computational neurobiology of language.
The crystal structure of the naturally split gp41-1 intein guides the engineering of orthogonal split inteins from acis-splicing intein
Authors: Beyer Hannes M. , Mikula Kornelia M. , Li Mi , Wlodawer Alexander , Iwaï Hideo
Published: February 2019

Proteintrans-splicing catalyzed by split inteins has increasingly become useful as a protein engineering tool. The 1.0 Å-resolution crystal structure of a variant from naturally split gp41-1 intein, identified from the environmental metagenomic sequence data, revealed an improved pseudo-C2-symmetry commonly found in the Hedgehog/Intein (HINT) superfamily with extensive charge-charge interactions between the split N-and C-terminal intein fragments. We successfully created orthogonal split inteins by engineering a similar charge network in the same region of acis-splicing intein. The same strategy could be applicable for creating novel natural-like split inteins from other, more prevalentcis-splicing inteins.
Resourceful mice do not starve: feeding efforts and decision-making process under a restricted unknown food source
Authors: Hernández Ma Carmen , Navarro-Castilla Álvaro , Barja Isabel
Published: February 2019

Foraging decisions must balance the energy gained, the time investment and the influence of key environmental factors. In our work, we aimed to examine the importance of predation risk cues and experience in the feeding efforts and decision-making process when a novel food resource is presented. To achieve this, free ranging wood miceApodemus sylvaticuswere live-trapped in “Monte de Valdelatas” (Madrid) by setting 80 Sherman traps in 4 plots. Traps were subjected to two food access difficulties three-night consecutive treatments: open plastic bottles and closed bottles, both using corn as bait. To generate predation risk, we set fox faeces in half of the traps in each plot. Also, we considered indirect predator cues as the moon phase. We analyse whether mice had bitten the bottles and the area gnawed of each bottle was measured. We discovered that mice feeding decisions and efforts were driven by food access difficulty, experience and predation risk. The ability of mice to properly balance their energy budget was probed since they bit and performed bigger orifices in the closed bottles, hence, individuals can adapt the feeding effort when a new food source is available. Moreover, experience was determinant in the use of this new resource since recaptured mice gnawed the bottles more successfully and the skill was improved each time an individual was recaptured. Additionally, direct predation risk cues prompt mice to bite the bottles whereas the effect of different moon phases varied among the treatments. This is the first study that provides direct evidence of wild mice formidable efficacy to exploit a new nutrient resource while deepening in crucial environmental factors that shape decision-making procedure.
Assemblage of Focal Species Recognizers - AFSR: A technique for decreasing false positive rates of acoustic automatic identification in a multiple species context
Authors: Campos Ivan Braga , Landers Todd J. , Lee Kate D. , Lee William George , Friesen Megan R. , Gaskett Anne C. , Ranjard Louis
Published: February 2019

Passive acoustic monitoring (PAM) coupled with automated species identification is a promising tool for species monitoring and conservation worldwide. However, high false positive rates are still an important limitation and a crucial factor for acceptance of these techniques in wildlife surveys. Here we present the Assemblage of Focal Species Recognizers - AFSR, a novel approach for decreasing false positives and increasing models’ precision in multispecies contexts. AFSR focusses on decreasing false positives by excluding unreliable sound file segments that are prone to misidentification. We used MatlabHTK, a hidden Markov models interface for bioacoustics analyses, for illustrating AFSR technique by comparing two approaches, 1) a multispecies recognizer where all species are identified simultaneously, and 2) an assemblage of focal species recognizers (AFSR), where several recognizers that each prioritise a single focal species are then summarised into a single output, according to a set of rules designed to exclude unreliable segments. Both approaches (the multispecies recognizer and AFSR) used the same sound files training dataset, but different processing workflow. We applied these recognisers to PAM recordings from a remote island colony with five seabird species and compared their outputs with manual species identifications. False positive rates and precision improved for all the five species when using AFSR, achieving remarkable 0% false positives and 100% precision for three of five seabird species, and < 6% false positive rates, and >90% precision for the other two species. AFSR’ output was also used to generate daily calling activity patterns for each species. Instead of attempting to withdraw useful information from every fragment in a sound recording, AFSR prioritises more trustworthy information from sections with better quality data. AFSR can be applied to automated species identification from multispecies PAM recordings worldwide.
Predictor species: Improving assessments of rare species occurrence by modelling environmental co-responses
Authors: Thompson Peter R. , Fagan William F. , Staniczenko Phillip P.A.
Published: February 2019

Designing an effective conservation strategy requires understanding where rare species are located. Although species distribution models are primarily used to identify patterns at large spatial scales, their general methodology is relevant for predicting the occurrence of individual species at specific locations. Here we present a new approach that uses Bayesian networks to improve predictions by modelling environmental co-responses among species. For species from a European peat bog community, our approach consistently performs better than single-species models, and better than conventional multi-species models for rare species when calibration data are limited. Furthermore, we identify a group of “predictor species” that are relatively common, insensitive to the presence of other species, and can be used to improve occurrence predictions of rare species. Predictor species are distinct from other categories of conservation surrogates such as umbrella or indicator species, which motivates focused data collection of predictor species to enhance conservation practices.
Ordered patterning of the sensory system is susceptible to stochastic features of gene expression
Authors: Giri Ritika , Papadopoulos Dimitrios K. , Posadas Diana M. , Potluri Hemanth K. , Tomancak Pavel , Mani Madhav , Carthew Richard W.
Published: February 2019

Sensory neuron numbers and positions are precisely organized to accurately map environmental signals in the brain. However, this precision must emerge from biochemical processes within and between cells that are stochastic. We measured intrinsic noise insenselessprotein output, a key determinant of sensory fate, duringDrosophiladevelopment. Perturbing microRNA regulation or genomic locus ofsenselesstranscription produced distinct noise signatures. Genomic location altered protein stochasticity in an allelic-pairing dependent manner (transvection). This generated sensory pattern disorder without perturbing protein abundance. In contrast, loss of microRNA repression ofsenselessincreased protein abundance but not sensory pattern disorder. This suggests that gene expression stochasticity is a critical feature that must be constrained during development to allow rapid yet accurate cell fate resolution.

One Sentence Summary

Life on the Margin: balancing speed and accuracy during animal development.
Assessment of kinship detection using RNA-seq data
Authors: Blay Natalia , Casas Eduard , Galván-Femenía Iván , Graffelman Jan , de Cid Rafael , Vavouri Tanya
Published: February 2019

Analysis of RNA sequencing (RNA-seq) data from related individuals is widely used in clinical and molecular genetics studies. Sample labelling mistakes are estimated to affect more than 4% of published samples. Therefore, as a method of data quality control, a way to reconstruct pedigrees from RNA-seq data would be useful for confirming the expected relationships. Currently, reconstruction of pedigrees is based mainly on SNPs or microsatellites, obtained from genotyping arrays, whole genome sequencing and whole exome sequencing. Potential problems with using RNA-seq data for kinship detection are the low proportion of the genome that it covers, the highly skewed coverage of exons of different genes depending on expression level and allele-specific expression.

In this study we assess the use of RNA-seq data to detect kinship between individuals, through pairwise identity-by-descent (IBD) estimates. First, we obtained high quality SNPs after successive filters to minimize the effects due to allelic imbalance as well as errors in sequencing, mapping and genotyping. Then, we used these SNPs to calculate pairwise IBD estimates. By analysing both real and simulated RNA-seq data we show that it is possible to identify up to second degree relationships using RNA-seq data of even low to moderate sequencing depth.
CXCR3-expressing metastasis-initiating cells induce and exploit a fibroblast niche in the lungs to fuel metastatic colonization
Authors: Pein Maren , Insua-Rodríguez Jacob , Meier Jasmin , Hongu Tsunaki , Wiedmann Lena , Essers Marieke A.G. , Sinn Hans-Peter , Spaich Saskia , Sütterlin Marc , Schneeweiss Andreas , Trumpp Andreas , Oskarsson Thordur
Published: February 2019

Metastatic colonization relies on interactions between disseminated cancer cells and the microenvironment in secondary organs. Here, we show that disseminated breast cancer cells evoke major phenotypic changes in lung fibroblasts to form a metastatic niche that supports malignant growth. Colonization of the lungs by cancer cells confers an inflammatory phenotype in associated fibroblasts, where IL-1α and IL-1β, secreted by breast cancer cells, induceCXCL9andCXCL10production in metastasis-associated fibroblasts via NF-κB signaling. These paracrine interactions fuel the growth of lung metastases. Notably, we find that the chemokine receptor CXCR3, that binds CXCL9/10, is specifically expressed in a small subset of breast cancer cells with stem/progenitor cell properties and high tumor-initiating ability when co-transplanted with fibroblasts. CXCR3-expressing cancer cells show high JNK signaling that drives IL-1α/β expression. Thus, CXCR3 marks a population of breast cancer cells that induces CXCL9/10 production in fibroblast, but can also respond to and benefit from these chemokines. Importantly, disruption of this intercellular JNK-IL-1-CXCL9/10-CXCR3 axis significantly reduces metastatic colonization in xenograft and syngeneic mouse models. These data mechanistically demonstrate an essential role for this molecular crosstalk between breast cancer cells and their fibroblast niche in the progression of metastasis.
World’s Fastest Brain-Computer Interface: Combining EEG2Code with Deep Learning
Authors: Nagel Sebastian , Spüler Martin
Published: February 2019

In this paper, we present a Brain-Computer Interface (BCI) that is able to reach an information transfer rate (ITR) of more than 1200 bit/min using non-invasively recorded EEG signals. By combining the EEG2Code method with deep learning, we present an extremely powerful approach for decoding visual information from EEG. This approach can either be used in a passive BCI setting to predict properties of a visual stimulus the person is viewing, or it can be used to actively control a BCI spelling application. The presented approach was tested in both scenarios and achieved an average ITR of 701 bit/min in the passive BCI approach with the best subject achieving an online ITR of 1237 bit/min. The presented BCI is more than three times faster than the previously fastest BCI and allows to discriminate 500,000 different visual stimuli based on 2 seconds of EEG data with an accuracy of up to 100 %. When using the approach in an asynchronous BCI for spelling, we achieved an average utility rate of 175 bit/min, which corresponds to an average of 35 error-free letters per minute. As we observe a ceiling effect where more powerful approaches for brain signal decoding do not translate into better BCI control anymore, we discuss if BCI research has reached a point where the performance of non-invasive BCI control cannot be substantially improved anymore.
Satiety, Thermosensation and Mechanosensation Regulate a Spontaneous C. elegans Sleep State
Authors: Gonzales Daniel L. , Zhou Jasmine , Robinson Jacob T.
Published: February 2019

One remarkable feature of the nervous system is its ability to rapidly and spontaneously switch between activity states. In the extreme example of sleep, animals arrest locomotion, reduce their sensitivity to sensory stimuli, and dramatically alter their neural activity. Small organisms are useful models to better understand these sudden changes in neural states because we can simultaneously observe whole-brain activity, monitor behavior and precisely regulate the external environment. Here, we show a spontaneous sleep-like behavior in C. elegans that is associated with a distinct global-brain state and regulated by both the animal’s internal physiological state and input from multiple sensory circuits. Specifically, we found that when confined in microfluidic chambers, adult worms spontaneously transition between periods of normal activity and short quiescent bouts, with behavioral state transitions occurring every few minutes. This quiescent state, which we call μSleep, meets the behavioral requirements of C. elegans sleep, is dependent on known sleep-promoting neurons ALA and RIS, and is associated with a global down-regulation of neural activity. Consistent with prior studies of C. elegans sleep, we found that μSleep is regulated by satiety and temperature. In addition, we show for the first time that quiescence can be either driven or suppressed by thermosensory input, and that animal restraint induces quiescence through mechanosensory pathways. Together, these results establish a rich model system for studying how neural and behavioral state transitions are influenced by multiple physiological and environmental conditions.

Significance Statement

Unique brain states govern animal behaviors like sleep and wakefulness; however, how the brain regulates these dramatic state transitions is not well understood. Brain activity can be influenced by a complex interaction between sensory circuits that monitor the external environment, neural circuits that control behavior, and internal chemical signaling. Here, we describe a platform to study behavioral states in a context that allows us to record whole-brain activity while controlling the environment and monitoring animal behavior. Specifically, we identify a pattern of sleep bouts in the roundworm C. elegans that occur when they are confined to microscopic fluidic chambers. This behavior platform provides a powerful system to study how neural circuits interact with chemical signaling to drive brain state transitions.
The kinetics of nucleotide binding to isolatedChlamydomonasaxonemes using UV-TIRF microscopy
Authors: Feofilova M. , Mahamdeh M. , Howard J.
Published: February 2019

Cilia and flagella are long, slender organelles found in many eukaryotic cells where they have sensory, developmental and motile functions. All cilia and flagella contain a microtubule-based structure called the axoneme. In motile cilia and flagella, which drive cell locomotion and fluid transport, the axoneme contains, along most of its length, motor proteins from the axonemal dynein family. These motor proteins drive motility by using energy derived from the hydrolysis of ATP to generate a bending wave, which travels down the axoneme. As a first step towards visualizing the ATPase activity of the axonemal dyneins during bending, we have investigated the kinetics of nucleotide binding to axonemes. Using a specially built UV-TIRF microscope, we found that the fluorescent ATP analog mantATP (methylanthraniloyl adenosine triphosphate), which has been shown to support axonemal motility, binds all along isolated, immobilized axonemes. By studying the recovery of fluorescence after photobleaching, we found that there are three mantATP binding sites: one that bleaches rapidly (time constant ≈ 1.7 s) and recovers slowly (time constant ≈ 44 s), one that bleaches with the same time constant but does not recover and one that does not bleach. By reducing the dynein content in the axoneme using mutants and salt extraction, we provide evidence that the slow-recovering component corresponds to axonemal dyneins. The recovery rate of this component, however, is too slow to be consistent with the activation of beating observed at higher mantATP concentrations; this indicates that the dyneins may be inhibited due to their immobilization at the surface. The development of this method is a first step towards direct observation of the travelling wave of dynein activity.
Coinfection of semi-infectious particles can contribute substantially to influenza infection dynamics
Authors: Farrell Alex , Brooke Christopher , Koelle Katia , Ke Ruian
Published: February 2019

Influenza is an RNA virus with a genome comprised of eight gene segments. Recent experiments show that the vast majority of virions fail to express one or more gene segments and thus cannot cause a productive infection on their own. These particles, called semi-infectious particles (SIPs), can induce virion production through complementation when multiple SIPs are present in an infected cell. Previous within-host influenza models ignore the potential effects of coinfection and SIPs during virus infection. Here, to investigate the extent that SIPs and coinfection impact viral dynamics, we constructed two within-host models that explicitly keep track of SIPs and coinfection, and fitted the models to clinical data published previously. We found that the model making a more realistic assumption that viruses can only reach a limited number of target cells allows for frequent co-infection during early viral exponential growth and predicts that SIPs contribute substantially to viral load. Furthermore, the model provides a new interpretation of the determinants of viral growth and predicts that the virus within-host growth rate (a measure of viral fitness) is relatively insensitive to the fraction of virions being SIPs, consistent with biological observations. Our results highlight the important role that cellular co-infection can play in regulating infection dynamics and provide a potential explanation for why SIP production is not highly deleterious. More broadly, the model can be used as a general framework to understand coinfection/superinfection in other viral infections.

Author Summary

Influenza A viruses (IAVs) represent a large public health burden across the world. Currently, our understanding of their infection dynamics is incomplete, which hinders the development of effective vaccines and treatment strategies. Recently, it was shown that a large fraction of virions, called semi-infectious particles, do not cause productive infection on their own; however, coinfection of these particles leads to productive infection. The extent that semi-infectious particles and, more broadly, coinfection contribute to overall influenza infection dynamics is not clear. To address this question, we constructed mathematical models explicitly keeping track of semi-infectious particles and coinfection. We show that coinfection can be frequent over the course of infection and that SIPs play an important role in regulating infection dynamics. Our results have implications towards developing effective therapeutics.
Data management and processing workflow for the Materials Physics and Engineering group beamlines at the Advanced Photon Source
Authors: Park Jun-Sang , Horn Connor , Ramanathan Prithvi , Kenesei Peter , Veseli Siniša
Published: February 2019

The ability to store, organize, process and distribute experimental data effectively, efficiently and securely is particularly important for large user facilities like the Advanced Photon Source. In this article, the deployment of the APS Data Management System (DM) at the 1-ID and 6-BM beamlines of the APS is described. These two beamlines support a wide range of experimental techniques and generate data at relatively high rates, making them ideal candidates to illustrate the deployment and customization of the DM system and its tools. Using several usage examples at these beamlines, various capabilities of the DM system are described.
Application of interference fits on cylindrical monochromator crystals to overcome clamping and cooling deformations
Authors: Stimson Joshua , Ward Michael , Sutter John , Diaz-Moreno Sofia , Alcock Simon , Docker Peter
Published: February 2019

In order to provide adequate cryogenic cooling of both existing and next-generation crystal monochromators, a new approach to produce an optimum thermal interface between the first crystal and its copper heat exchanger is proposed. This will ensure that the increased heat load deposited by higher X-ray powers can be properly dissipated. Utilizing a cylindrical silicon crystal, a tubular copper heat exchanger and by exploiting the differing thermal and mechanical properties of the two, a very good thermal interface was achieved at liquid-nitrogen temperatures. The surface flatness of the diffracting plane at one end of the cylindrical crystal was measured at room temperature while unconstrained. The crystal was then placed into the copper heat exchanger, a slide fit at room temperature, and then cooled to liquid-nitrogen temperature. At −200°C the slide fit became an interference fit. This room-temperature `loose' fit was modelled using finite-element analysis to obtain the desired fit at cryogenic temperatures by prescribing the fit at room temperature. Under these conditions, the diffraction surface was measured for distortion due to thermal and mechanical clamping forces. The total deformation was measured to be 30 nm, an order of magnitude improvement over deformation caused by cooling alone with the original side-clamped design this concept method is set to replace. This new methodology also has the advantage that it is repeatable and does not require macro-scale tools to acquire a nanometre-accuracy mounting.
Synthesis, crystal structure and photoluminescence of a three-dimensional zinc coordination compound with NBO-type topology
Authors: Liu Xi , Fu Bo , Li Lin , Jian Yun-Fei , Shu Si
Published: February 2019

The assembly of metal–organic frameworks (MOFs) with metal ions and organic ligands is currently attracting considerable attention in crystal engineering and materials science due to their intriguing architectures and potential applications. A new three-dimensional MOF, namely poly[[diaqua(μ8-para-terphenyl-3,3′,5,5′-tetracarboxylato)dizinc(II)] dimethylformamide disolvate monohydrate], {[Zn2(C22H10O8)(H2O)2]·2C3H7NO·H2O}
n
, was synthesized by the self-assembly of Zn(NO3)2·6H2O and para-terphenyl-3,3′,5,5′-tetracarboxylic acid (H4TPTC) under solvothermal conditions. The compound was structurally characterized by FT–IR spectroscopy, elemental analysis and single-crystal X-ray diffraction analysis. Each ZnII ion is located in a square-pyramidal geometry and is coordinated by four carboxylate O atoms from four different TPTC4− ligands. Pairs of adjacent equivalent ZnII ions are bridged by four carboxylate groups, forming [Zn2(O2CR)4] (R = terphenyl) paddle-wheel units. One aqua ligand binds to each ZnII centre along the paddle-wheel axis. Each [Zn2(O2CR)4] paddle wheel is further linked to four terphenyl connectors to give a three-dimensional framework with NBO-type topology. The thermal stability and solid-state photoluminescence properties of the title compound have also been investigated.
Resolving 500 nm axial separation by multi-slice X-ray ptychography
Authors: Huang Xiaojing , Yan Hanfei , He Yan , Ge Mingyuan , Öztürk Hande , Fang Yao-Lung L. , Ha Sungsoo , Lin Meifeng , Lu Ming , Nazaretski Evgeny , Robinson Ian K. , Chu Yong S.
Published: February 2019

Multi-slice X-ray ptychography offers an approach to achieve images with a nanometre-scale resolution from samples with thicknesses larger than the depth of field of the imaging system by modeling a thick sample as a set of thin slices and accounting for the wavefront propagation effects within the specimen. Here, we present an experimental demonstration that resolves two layers of nanostructures separated by 500 nm along the axial direction, with sub-10 nm and sub-20 nm resolutions on two layers, respectively. Fluorescence maps are simultaneously measured in the multi-modality imaging scheme to assist in decoupling the mixture of low-spatial-frequency features across different slices. The enhanced axial sectioning capability using correlative signals obtained from multi-modality measurements demonstrates the great potential of the multi-slice ptychography method for investigating specimens with extended dimensions in 3D with high resolution.
Grazing-incidence small-angle X-ray scattering study of correlated lateral density fluctuations in W/Si multilayers
Authors: Nikolaev K. V. , Yakunin S. N. , Makhotkin I. A. , Rie J. de la , Medvedev R. V. , Rogachev A. V. , Trunckin I. N. , Vasiliev A. L. , Hendrikx C. P. , Gateshki M. , Kruijs R. W. E. van de , Bijkerk F.
Published: February 2019

A structural characterization of W/Si multilayers using X-ray reflectivity (XRR), scanning transmission electron microscopy (STEM) and grazing-incidence small-angle X-ray scattering (GISAXS) is presented. STEM images revealed lateral, periodic density fluctuations in the Si layers, which were further analysed using GISAXS. Characteristic parameters of the fluctuations such as average distance between neighbouring fluctuations, average size and lateral distribution of their position were obtained by fitting numerical simulations to the measured scattering images, and these parameters are in good agreement with the STEM observations. For the numerical simulations the density fluctuations were approximated as a set of spheroids distributed inside the Si layers as a 3D paracrystal (a lattice of spheroids with short-range ordering but lacking any long-range order). From GISAXS, the density of the material inside the density fluctuations is calculated to be 2.07 g cm−3 which is 89% of the bulk value of the deposited layer (2.33 g cm−3).
Crystal structure and magnetic properties of (tris{4-[1-(2-methoxyethyl)imidazol-2-yl]-3-azabut-3-enyl}amine)iron(II) bis(hexafluoridophosphate)
Authors: Znovjyak Kateryna , Fritsky Igor O. , Golenya Iryna A. , Sliva Tatiana Y. , Haukka Matti
Published: February 2019

In the complex cation of the title compound, [Fe(C27H41N10O3)](PF6)2, the tripodal tris{4-[1-(2-methoxyethyl)imidazol-2-yl]-3-azabut-3-enyl}amine ligand is coordinated to an FeII ion through the nitrogen atoms of three imidazole and three imino groups. The Fe atom exhibits a distorted octahedral geometry. In the crystal, L and D antipodes are arranged in layers in the bc plane. Weak C...F and C—H...F/O contacts exist between the ligands of the complex cation and the PF6
− anions, generating a three-dimensional network. At 120 K, the FeII ion is in a low-spin state, with an average Fe—N bond distance of 1.970 (2) Å. On heating, the FeII ion converts to the high-spin state, as demonstrated by magnetic susceptibility measurements.
Crystal structure and Hirshfeld surface analysis of a Schiff base: (Z)-6-[(5-chloro-2-methoxyanilino)methylidene]-2-hydroxycyclohexa-2,4-dien-1-one
Authors: Demir Kanmazalp Sibel , Doĝan Onur Erman , Taşdemir Volkan , Dege Necmi , Aĝar Erbil , Fritsky Igor O.
Published: February 2019

The title compound, C14H12ClNO3, is a Schiff base that exists in the keto–enamine tautomeric form and adopts a Z configuration. In the crystal, the dihedral angle between the planes of the benzene rings is 5.34 (15)°. The roughly planar geometry of the molecule is stabilized by a strong intramolecular N—H...O hydrogen bond. In the crystal, pairs of centrosymmetrically related molecules are linked by O—H...O hydrogen bonds, forming R
2
2(10) rings. Besides this, the molecules form stacks along the [001] direction with C—H...π and C—H...Cl contacts between the stacks. The intermolecular interactions in the crystal were analysed using Hirshfeld surfaces. The most significant contribution to the crystal packing is from H...H contacts (30.8%).
5-[(4-Chlorophenyl)diazenyl]-2-[5-(4-fluorophenyl)-3-(furan-2-yl)-4,5-dihydro-1H-pyrazol-1-yl]-4-methylthiazole
Authors: El-Hiti Gamal A , Abdel-Wahab Bakr F. , Yousif Emad , Alotaibi Mohammad Hayal , Hegazy Amany S. , Kariuki Benson M.
Published: February 2019

The title compound, C23H17ClFN5OS, comprises fluorophenyl (A), furanyl (B), pyrazolyl (C), methylthiazoyl (D) and chlorophenyl (E) rings. The B–C–D–E linked ring system is close to planar with the dihedral angles B/C, C/D and D/E being 7.6 (1), 3.4 (1) and 8.4 (1)°, respectively. The fluorophenyl group is almost perpendicular to the pyrazoyl ring, as indicated by an A/C twist angle of 79.4 (1)°. In the crystal, inversion dimers linked by pairs of C—H...S contacts are observed.
Entrepreneurial competencies and SMEs’ growth: the mediating role of network competence
Authors: Tehseen Shehnaz , Ahmed Farhad Uddin , Qureshi Zuhaib Hassan , Uddin Mohammad Jasim , T. Ramayah
Published: February 2019

Purpose

The purpose of this paper is twofold. First, to examine the influence of two dimensions of entrepreneurial competencies, namely, strategic competency and ethical competency on the growth of small and medium enterprises (SMEs); and second, to explore the role of network competence as a mediator among these understudied variables.

Design/methodology/approach

The data for this study were collected from wholesale and retail-based SMEs in Malaysia through a standard structured questionnaire. PLS–SEM approach was utilised to analyse the data.

Findings

Although the findings did not reveal a direct effect of strategic and ethical competencies of entrepreneurs on SMEs’ growth, these competences, however, were found to be influential in driving their growth when network competence was used as a mediator.

Originality/value

The existence of a mediation effect between strategic and ethical competencies and SMEs’ growth via network competence has provided insights which add new knowledge to the extant entrepreneurship and SMEs’ performance literature.
To investigate the determinants of cloud computing adoption in the manufacturing micro, small and medium enterprises
Authors: Raut Rakesh D. , Gardas Bhaskar B. , Narkhede Balkrishna E. , Narwane Vaibhav S.
Published: February 2019

Purpose

The purpose of this paper is to identify the critical factors influencing the cloud computing adoption (CCA) in the manufacturing micro, small and medium enterprises (MSMEs) by employing a decision-making trial and evaluation laboratory (DEMATEL) methodology.

Design/methodology/approach

Through literature review and expert opinions, 30 significant factors were identified, and then a DEMATEL approach was applied for exploring the cause–effect relationship between the factors.

Findings

The results of study highlighted that five factors, namely, “hardware scalability and standardisation”, “cost (subscription fees, maintenance cost and implementation cost (CS1)”, “innovation”, “installation and up gradation (CS28)”, and “quality of service” were the most significant factors influencing the CCA in the case sector.

Research limitations/implications

The DEMATEL model was developed by considering expert inputs, and these inputs could be biased which can influence the reliability of the model. This study guides the organisational managers, cloud service providers and governmental organisations in formulating the new policies/strategies or modifying the existing ones for the effective CCA in the case sector.

Originality/value

For the first time. interdependency between the critical factors influencing CCA was discussed by employing the DEMATEL approach in the Indian manufacturing MSMEs context.
The adoption of soft skills in supply chain and understanding their current role in supply chain management skills agenda
Authors: Bak Ozlem , Jordan Christine , Midgley James
Published: February 2019

Purpose

With supply chains expanding in scope and scale globally, the academic literature underlined the increasing role and importance of soft skills. Traditionally, the supply chain literature geared towards hard skills including functional and technical skill sets with limited discussion on soft skills. Therefore, the purpose of this paper is to assess and explore the soft skills demand in supply chain management arena.

Design/methodology/approach

This study has utilised a mixed methods study in two phases, with the first stage including a questionnaire distributed to 120 supply chain employees in the UK, followed by six interviews with supply chain experts in the UK.

Findings

The results suggest that soft skills, especially behavioural skills such as communication, planning, initiative and negotiation, were seen to be more important when compared to decision making, negotiation and management skills. The findings indicate that the changing supply chain scope encourages the requisition and development of different supply chain soft skills with varied levels of emphasis in relation to 15 soft skills identified in the literature.

Research limitations/implications

This study employs a mixed-method approach to establish the perceived importance of soft skills in the UK supply chains. This limits the generalisability of the results to other contextual settings.

Practical implications

This paper presents soft skills impact upon the supply chain. Specific soft skills are critical to supply chain employees compared to others (e.g. behavioural and people management skills), which may lead to articulation of supply chain soft skills training initiatives.

Originality/value

This paper contributes to the soft skills discussion in the supply chain context and discusses the role of soft skills. Topical gaps in the literature are identified as areas for future research. The findings have generated additional supply chain skills to the academic literature as well as provided an understanding of the weighting of soft skills in terms of their importance and application to industry needs.