bluuebunny/crossref_metadata_2025_split huggingface dataset:
Local nucleation of microtubule bundles through tubulin concentration into a condensed tau phase
Authors: Hernández-Vega Amayra , Braun Marcus , Scharrel Lara , Jahnel Marcus , Wegmann Susanne , Hyman Bradley T. , Alberti Simon , Diez Stefan , Hyman Anthony A. 
Published: April 2017

SUMMARYNon-centrosomal microtubule bundles play important roles in cellular organization and function. Although many diverse proteins are known that can bundle microtubules, biochemical mechanisms by which cells could locally control the nucleation and formation of microtubule bundles are understudied. Here, we demonstrate that concentration of tubulin into a condensed, liquid-like compartment composed of the unstructured neuronal protein tau is sufficient to nucleate microtubule bundles. We show that under conditions of macro-molecular crowding, tau forms liquid drops. Tubulin partitions into these drops, efficiently increasing tubulin concentration and driving the nucleation of microtubules. These growing microtubules form bundles enclosed in a liquid sheath of tau. Our data suggest that condensed compartments of microtubule bundling proteins could promote the local formation of microtubule bundles in neurons by acting as non-centrosomal microtubule nucleation centers, and that liquid-like tau encapsulation could provide both stability and plasticity to long axonal microtubule bundles.
On reciprocal causation in the evolutionary process
Authors: Svensson Erik I. 
Published: April 2017

AbstractRecent calls for a revision of standard evolutionary theory (SET) are based in part on arguments about the reciprocal causation. Reciprocal causation means that cause-effect relationships are obscured, as a cause could later become an effect andvice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and Standard Evolutionary Theory (SET), which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. I critically examine these claims, with a special focus on the last conjecture and conclude – on the contrary– that reciprocal causation has long been recognized as important both in SET and in the MS tradition, although it remains underexplored. Numerous empirical examples of reciprocal causation in the form of positive and negative feedbacks are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedbacks were already recognized by Richard Levins and Richard Lewontin, well before the recent call for an EES. Reciprocal causation and dynamic feedbacks is one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory, and should be recognized as such. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. While reciprocal causation have helped us to understand many evolutionary processes, I caution against uncritical extension of dialectics towards heredity and constructive development, particularly if such extensions involves attempts to restore Lamarckian or “soft inheritance”.
Derivation and Validation of a Record Linkage Algorithm between EMS and the Emergency Department
Authors: Redfield Colby , Tlimat Abdulhakim , Halpern Yoni , Schoenfeld David , Ullman Edward , Sontag David A , Nathanson Larry A , Horng Steven 
Published: April 2017

AbstractBackgroundLinking EMS electronic patient care reports (ePCRs) to ED records can provide clinicians access to vital information that can alter management. It can also create rich databases for research and quality improvement. Unfortunately, previous attempts at ePCR - ED record linkage have had limited success.ObjectiveTo derive and validate an automated record linkage algorithm between EMS ePCR’s and ED records using supervised machine learning.MethodsAll consecutive ePCR’s from a single EMS provider between June 2013 and June 2015 were included. A primary reviewer matched ePCR’s to a list of ED patients to create a gold standard. Age, gender, last name, first name, social security number (SSN), and date of birth (DOB) were extracted. Data was randomly split into 80%/20% training and test data sets. We derived missing indicators, identical indicators, edit distances, and percent differences. A multivariate logistic regression model was trained using 5k fold cross-validation, using label k-fold, L2 regularization, and class re-weighting.ResultsA total of 14,032 ePCRs were included in the study. Inter-rater reliability between the primary and secondary reviewer had a Kappa of 0.9. The algorithm had a sensitivity of 99.4%, a PPV of 99.9% and AUC of 0.99 in both the training and test sets. DOB match had the highest odd ratio of 16.9, followed by last name match (10.6). SSN match had an odds ratio of 3.8.ConclusionsWe were able to successfully derive and validate a probabilistic record linkage algorithm from a single EMS ePCR provider to our hospital EMR.
pomp-astic Inference for Epidemic Models: Simple vs. Complex
Authors: Stocks Theresa , Britton Tom , Höhle Michael 
Published: April 2017

AbstractInfectious disease surveillance data often provides only partial information about the progression of the disease in the individual while disease transmission is often modelled using complex mathematical models for large populations, where variability only enters through a stochastic observation process. In this work it is shown that a rather simplistic, but truly stochastic transmission model, is competitive with respect to model fit when compared with more detailed deterministic transmission models and even preferable because the role of each parameter and its identifiability is clearly understood in the simpler model. The inference framework for the stochastic model is provided by iterated filtering methods which are readily implemented in theR package pomp. We illustrate our findings on German rotavirus surveillance data from 2001 to 2008 and calculate a model based estimate for the basic reproduction numberR0using these data.
Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance
Authors: Glomb Katharina , Ponce-Alvarez Adrián , Gilson Matthieu , Ritter Petra , Deco Gustavo 
Published: April 2017

AbstractSpontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These “resting state networks” (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a non-stationary process which could be described as state switching.In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal.We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also encounter interesting characteristics that are not explained in this way. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics.
Slow conformational exchange and overall rocking motion in ubiquitin protein crystals
Authors: Kurauskas Vilius , Izmailov Sergei A. , Rogacheva Olga N. , Hessel Audrey , Ayala Isabel , Woodhouse Joyce , Shilova Anastasya , Xue Yi , Yuwen Tairan , Coquelle Nicolas , Colletier Jacques-Philippe , Skrynnikov Nikolai R. , Schanda Paul 
Published: April 2017

AbstractProteins perform their functions in solution but their structures are most frequently studied inside crystals. Here we probe how the crystal packing alters microsecond dynamics, using solid-state NMR measurements and multi-microsecond MD simulations of different crystal forms of ubiquitin. In particular, NEar-Rotary-resonance Relaxation Dispersion (NERRD) experiments probe angular backbone motion, while Bloch-McConnell Relaxation Dispersion data report on fluctuations of the local electronic environment. These experiments and simulations reveal that the packing of the protein can significantly alter the thermodynamics and kinetics of local conformational exchange. Moreover, we report small-amplitude reorientational motion of protein molecules in the crystal lattice with a ∼3-5° amplitude on a tens-of-microseconds time scale in one of the crystals, but not in others. An intriguing possibility arises that overall motion is to some extent coupled to local dynamics. Our study highlights the importance of considering the packing when analyzing dynamics of crystalline proteins.
Nanopore Long-Read RNAseq Reveals Widespread Transcriptional Variation Among the Surface Receptors of Individual B cells
Authors: Byrne Ashley , Beaudin Anna E. , Olsen Hugh E. , Jain Miten , Cole Charles , Palmer Theron , DuBois Rebecca M. , Forsberg E. Camilla , Akeson Mark , Vollmers Christopher 
Published: April 2017

ABSTRACTUnderstanding gene regulation and function requires a genome-wide method capable of capturing both gene expression levels and isoform diversity at the single cell level. Short-read RNAseq, while the current standard for gene expression quantification, is limited in its ability to resolve complex isoforms because it fails to sequence full-length cDNA copies of RNA molecules. Here, we investigated whether RNAseq using the long-read single-molecule Oxford Nanopore MinION sequencing technology (ONT RNAseq) would be able to identify and quantify complex isoforms without sacrificing accurate gene expression quantification. After successfully benchmarking our experimental and computational approaches on a mixture of synthetic transcripts, we analyzed individual murine B1a cells using a new cellular indexing strategy. Using theMandalorionanalysis pipeline we developed, we identified thousands of unannotated transcription start and end sites, as well as hundreds of alternative splicing events in these B1a cells. We also identified hundreds of genes expressed across B1a cells that displayed multiple complex isoforms, including several B cell specific surface receptors and the antibody heavy chain (IGH) locus. Our results show that not only can we identify complex isoforms, but also quantify their expression, at the single cell level.
Characterizing RNA Pseudouridylation by Convolutional Neural Networks
Authors: He Xuan , Zhang Sai , Zhang Yanqing , Jiang Tao , Zeng Jianyang 
Published: April 2017

AbstractThe most prevalent post-transcriptional RNA modification, pseudouridine (Ψ), also known as the fifth ribonucleoside, is widespread in rRNAs, tRNAs, snRNAs, snoRNAs and mRNAs. Pseudouridines in RNAs are implicated in many aspects of post-transcriptional regulation, such as the maintenance of translation fidelity, control of RNA stability and stabilization of RNA structure. However, our understanding of the functions, mechanisms as well as precise distribution of pseudourdines (especially in mRNAs) still remains largely unclear. Though thousands of RNA pseudouridylation sites have been identified by high-throughput experimental techniques recently, the landscape of pseudouridines across the whole transcriptome has not yet been fully delineated. In this study, we present a highly effective model, called PULSE (PseudoUridyLationSitesEstimator), to predict novel Ψ sites from large-scale profiling data of pseudouridines and characterize the contextual sequence features of pseudouridylation. PULSE employs a deep learning framework, called convolutional neural network (CNN), which has been successfully and widely used for sequence pattern discovery in the literature. Our extensive validation tests demonstrated that PULSE can outperform conventional learning models and achieve high prediction accuracy, thus enabling us to further characterize the transcriptome-wide landscape of pseudouridine sites. Overall, PULSE can provide a useful tool to further investigate the functional roles of pseudouridylation in post-transcriptional regulation.
Modulation of Genome Editing Outcomes by Cell Cycle Control of Cas9 Expression
Authors: Huang Yuping , McCann Caitlin , Samsonov Andrey , Malkov Dmitry , Davis Gregory D , Ji Qingzhou 
Published: April 2017

ABSTRACTTargeting specific chromosomal sequences for genome modification or regulation during particular phases of the cell cycle may prove useful in creating more precise, predictable genetic changes. Here, we present a system using a fusion protein comprised of a programmable DNA modification protein, Cas9, linked to a cell cycle regulated protein, geminin, as well as green fluorescent protein (GFP) for visualization. Despite the large size of Cas9 relative to geminin, cells were observed to express Cas9-GFP-geminin at levels which oscillate with the cell cycle. These fusion proteins are also shown to retain double-strand break (DSB) activity at specific chromosomal sequences to produce both indels and targeted integration of donor ssDNA. Most importantly, the ratio of ssDNA donor integration to non-homologous end joining (NHEJ) was observed to increase, suggesting that cell cycle control Cas9 expression may be an effective strategy to bias DNA repair outcomes.
Acute transient cognitive dysfunction and acute brain injury induced by systemic inflammation occur by dissociable IL-1-dependent mechanisms
Authors: Skelly Donal T. , Griffin Éadaoin W. , Murray Carol L. , Harney Sarah , O’Boyle Conor , Hennessy Edel , Rawlins J Nicholas , Bannerman David M. , Cunningham Colm 
Published: April 2017

AbstractSystemic inflammation can impair cognition with relevance to dementia, delirium and post-operative cognitive dysfunction. Acute episodes of delirium also contribute significantly to rates of long-term cognitive decline, implying thatde novopathology occurs during these acute episodes. Whether systemic inflammation-induced acute dysfunction and acute brain injury occur by overlapping or discrete mechanisms has not been investigated. Here we show that systemic inflammation, induced by bacterial LPS, produces both working memory deficits and acute brain injury in the degenerating brain and that these occur by dissociable IL-1-dependent processes. In normal C57BL/6 mice, LPS (100μg/kg) did not affect working memory but robustly impaired contextual fear conditioning (CFC). However prior hippocampal synaptic loss left mice selectively vulnerable to LPS-induced working memory deficits. Systemically administered IL-1 receptor antagonist (IL-1RA) was protective against, and systemic IL-1β replicated, these working memory deficits. Although LPS-induced deficits still occured in IL-1RI-/-mice, systemic TNF-α was sufficient to induce similar deficits, indicating redundancy among these cytokines. Dexamethasone abolished systemic cytokine synthesis and was protective against working memory deficits despite failing to block brain IL-1β synthesis. Direct application of IL-1β to ex vivo hippocampal slices induced non-synaptic depolarisation and irrevesible loss of membrane potential in CA1 neurons from diseased animals and systemic LPS increased apoptosis in the degenerating brain, in an IL-1RI-/-dependent-fashion. The data suggest that LPS induces working memory dysfunction via circulating IL-1β but dysfunction leading to neuronal death is mediated by hippocampal IL-1β. The data suggest that acute systemic inflammation produces both reversible cognitive deficits, resembling delirium, and acute brain injury that may lead to long-term cognitive impairment but that these events are mechanistically dissociable. This would have significant implications for management of cognitive dysfunction and decline during acute illness.
Do gametes woo? Evidence for non-random unions at fertilization
Authors: Nadeau Joseph H. 
Published: April 2017

AbstractA fundamental tenet of inheritance in sexually reproducing organisms such as humans and laboratory mice is that genetic variants combine randomly at fertilization, thereby ensuring a balanced and statistically predictable representation of inherited variants in each generation. This principle is encapsulated in Mendel’s First Law. But exceptions are known. With transmission ratio distortion (TRD), particular alleles are preferentially transmitted to offspring without reducing reproductive productivity. Preferential transmission usually occurs in one sex but not both and is not known to require interactions between gametes at fertilization. We recently discovered, in our work in mice and in other reports in the literature, instances where any of 12 mutant genes bias fertilization, with either too many or too few heterozygotes and too few homozygotes, depending on the mutant gene and on dietary conditions. Although such deviations are usually attributed to embryonic lethality of the under-represented genotypes, the evidence is more consistent with genetically-determined preferences for specific combinations of egg and sperm at fertilization that results in genotype bias without embryo loss. These genes and diets could bias fertilization in at least three not mutually exclusive ways. They could trigger a reversal in the order of meiotic divisions during oogenesis so that the genetics of fertilizing sperm elicits preferential chromatid segregation, thereby dictating which allele remains in the egg versus the 2ndpolar body. Bias could also result from genetic- and diet-induced anomalies in polyamine metabolism on which function of haploid gametes normally depends. Finally, secreted and cell-surface factors in female reproductive organs could control access of sperm to eggs based on their genetic content. This unexpected discovery of genetically-biased fertilization in mice could yield insights about the molecular and cellular interactions between sperm and egg at fertilization, with implications for our understanding of inheritance, reproduction, population genetics, and medical genetics.
Local processing of visual information in neurites of VGluT3-expressing amacrine cells
Authors: Hsiang Jen-Chun , Johnson Keith , Madisen Linda , Zeng Hongkui , Kerschensteiner Daniel 
Published: April 2017

AbstractSynaptic inputs to neurons are distributed across extensive neurite arborizations. To what extent arbors process inputs locally or integrate them globally is, for most neurons, unknown. This question is particularly relevant for amacrine cells, a diverse class of retinal interneurons, which receive input and provide output through the same neurites. Here, we used two-photon Ca2+imaging to analyze visual processing in VGluT3-expressing amacrine cells (VG3-ACs), an important component of object motion sensitive circuits in the retina. VG3-AC neurites differed in their preferred stimulus contrast (ON vs. OFF); and ON and OFF responses varied in transience and preferred stimulus size. Contrast preference changed predictably with the laminar position of neurites in the inner plexiform layer. Yet, neurites at all depths were strongly activated by local but not by global image motion. Thus, VG3-AC neurites process visual information locally, exhibiting diverse responses to contrast steps, but uniform object motion selectivity.
Acyl-CoA:Lysophosphatidylethanolamine Acyltransferase Activity Regulates Growth of Arabidopsis
Authors: Jasieniecka-Gazarkiewicz Katarzyna , Lager Ida , Carlsson Anders S. , Gutbrod Katharina , Peisker Helga , Dörmann Peter , Stymne Sten , Banaś Antoni 
Published: April 2017

Abstract
Arabidopsis (Arabidopsis thaliana) contains two enzymes (encoded by the At1g80950 and At2g45670 genes) preferentially acylating lysophosphatidylethanolamine (LPE) with acyl-coenzyme A (CoA), designated LYSOPHOSPHATIDYLETHANOLAMINE ACYLTRANSFERASE1 (LPEAT1) and LPEAT2. The transfer DNA insertion mutant lpeat2 and the double mutant lpeat1 lpeat2 showed impaired growth, smaller leaves, shorter roots, less seed setting, and reduced lipid content per fresh weight in roots and seeds and large increases in LPE and lysophosphatidylcholine (LPC) contents in leaves. Microsomal preparations from leaves of these mutants showed around 70% decrease in acylation activity of LPE with 16:0-CoA compared with wild-type membranes, whereas the acylation with 18:1-CoA was much less affected, demonstrating that other lysophospholipid acyltransferases than the two LPEATs could acylate LPE. The above-mentioned effects were less pronounced in the single lpeat1 mutant. Overexpression of either LPEAT1 or LPEAT2 under the control of the 35S promotor led to morphological changes opposite to what was seen in the transfer DNA mutants. Acyl specificity studies showed that LPEAT1 utilized 16:0-CoA at the highest rate of 11 tested acyl-CoAs, whereas LPEAT2 utilized 20:0-CoA as the best acyl donor. Both LPEATs could acylate either sn position of ether analogs of LPC. The data show that the activities of LPEAT1 and LPEAT2 are, in a complementary way, involved in growth regulation in Arabidopsis. It is shown that LPEAT activity (especially LPEAT2) is essential for maintaining adequate levels of phosphatidylethanolamine, LPE, and LPC in the cells.
The mediating role of ambidextrous capability in learning orientation and new product performance
Authors: Huang Jing-Wen , Li Yong-Hui 
Published: April 2017

Purpose
Learning orientation is critical in new product development. However, research has disregarded how learning orientation operates via the potential mediator to influence new product performance. The purpose of this study is to examine the mediating role of ambidextrous capability in the relationship between learning orientation and new product performance.

Design/methodology/approach
The empirical study uses a questionnaire approach designed to collect data for testing research hypotheses. This study tests the hypotheses using structural equation model in a sample of 336 firms in Taiwan.

Findings
The findings indicate that learning orientation relates positively to ambidextrous capability and new product performance. Ambidextrous capability, in turn, relates positively to new product performance. The results also support the argument that ambidextrous capability plays a mediating role in learning orientation and new product performance.

Originality/value
The value of this study is to identify ambidextrous capability as the potential mediator in the relationship between learning orientation and new product performance. The results enrich the understanding of learning orientation in new product project teams and suggest important implications for new product development and future research.