bluuebunny/crossref_metadata_2025_split huggingface dataset:
PIKfyve deficiency in myeloid cells impairs lysosomal homeostasis in macrophages and promotes systemic inflammation in mice
Authors: Min Sang Hee , Suzuki Aae , Weaver Lehn , Guzman Jessica , Zhao Liang , Gonzalez Francina , Spruce Lynn A. , Seeholzer Steven H. , Behrens Edward , Abrams Charles S. 
Published: April 2019

AbstractMacrophages are professional phagocytes that are essential for host defense and tissue homeostasis. Proper membrane trafficking and degradative functions of the endolysosomal system is known to be critical for the function of these cells. We have found that PIKfyve, the kinase that synthesizes the endosomal phosphoinositide PI(3,5)P2, is an essential regulator of lysosomal biogenesis and degradative functions in macrophages. Genetically engineered mice lacking PIKfyve in their myeloid cells (PIKfyvefl/fl LysM-Cre) develop diffuse tissue infiltration of foamy macrophages, hepatosplenomegaly, and systemic inflammation. PIKfyve loss in macrophages causes enlarged endolysosomal compartments and impairs the lysosomal degradative function. Moreover, PIKfyve deficiency increases the cellular levels of lysosomal proteins. Although PIKfyve deficiency reduced the activation of mTORC1 pathway and was associated with increased cleavage of TFEB proteins, this does not translate into transcriptional activation of lysosomal genes, suggesting that PIKfyve modulates the abundance of lysosomal proteins by affecting the degradation of these proteins. Taken together, our study shows that PIKfyve modulation of lysosomal degradative activity and protein expression is essential to maintain lysosomal homeostasis in macrophages.
Protein-protein interaction network topology as a measure of bacterial plasmid-chromosome co-evolution
Authors: Tran Nghia T.H. , Decano Arun , Downing Tim , Rahm Alexander D. 
Published: April 2019

AbstractIn this work, we investigate the evolvability of plasmids by examining the topology of plasmid-chromosome gene interactions in Escherichia coli ST131. We discover a convergence of the ratio of non-trivial loops per protein-protein interaction, which allows us to introduce a new invariant of bacterial PPINs: the indirect connectivity value.
Accurate Prediction of Genome-wide RNA Secondary Structure Profile Based On Extreme Gradient Boosting
Authors: Ke Yaobin , Rao Jiahua , Zhao Huiying , Lu Yutong , Xiao Nong , Yang Yuedong 
Published: April 2019

AbstractMotivationMany studies have shown that RNA secondary structure plays a vital role in fundamental cellular processes, such as protein synthesis, mRNA processing, mRNA assembly, ribosome function and eukaryotic spliceosomes. Identification of RNA secondary structure is a key step to understand the common mechanisms underlying the translation process. Recently, a few experimental methods were developed to measure genome-wide RNA secondary structure profile through high-throughput sequencing techniques, and have been successfully applied to genomes including yeast and human. However, these high-throughput methods usually have low precision and are hard to cover all nucleotides on the RNA due to limited sequencing coverage.ResultsIn this study, we developed a new method for the prediction of genome-wide RNA secondary structure profile (TH-GRASP) from RNA sequence based on eXtreme Gradient Boosting (XGBoost). The method achieves an prediction with areas under the receiver operating characteristic curve (AUC) values greater than 0.9 on three different datasets, and AUC of 0.892 by an independent test on the recently released Zika virus RNA dataset. These AUCs represent a consistent increase of >6% than the recently developed method CROSS trained by a shallow neural network. A further analysis on the 1000-Genome Project data showed that our predicted unpaired probability at mutations sites are highly correlated with the minor allele frequencies (MAF) of synonymous, non-synonymous mutations, and mutations in 3’ and 5’UTR with Pearson Correlation Coefficients all above 0.8. These PCCs are consistently higher than those generated by RNAplfold method. Moreover, an investigation over all human mRNA indicated a periodic distribution of the predicted unpaired probability on codons, and a decrease of paired probability in the boundary with 5’ and 3’ untranslated regions. These results highlighted TH-GRASP is effective to remove experimental noises and to have ability to make predictions on nucleotides with low or no coverage by fitting high-throughput genomic data for RNA secondary structure profiles, and also suggested that building model on high throughput experimental data might be a future direction to substitute analytical methods.AvailabilityThe TH-GRASP is available for academic use athttps://github.com/sysu-yanglab/TH-GRASP.Supplementary informationSupplementary data are available online.
The molecular aetiology of tRNA synthetase depletion: induction of aGCN4amino acid starvation response despite homeostatic maintenance of charged tRNA levels
Authors: McFarland Matthew R. , Keller Corina D. , Childers Brandon M. , Adeniyi Stephen A. , Corrigall Holly , Raguin Adélaïde , Romano M. Carmen , Stansfield Ian 
Published: April 2019

ABSTRACTDuring protein synthesis, charged tRNAs deliver amino acids to translating ribosomes, and are then re-charged by tRNA synthetases (aaRS). In humans, mutant aaRS cause a diversity of neurological disorders, but their molecular aetiologies are incompletely characterised. To understand system responses to aaRS depletion, the yeast glutamine aaRS gene (GLN4) was transcriptionally regulated using doxycycline bytet-offcontrol. Depletion of Gln4p inhibited growth, and induced aGCN4amino acid starvation response, indicative of uncharged tRNA accumulation and Gcn2 kinase activation. Using a global model of translation that included aaRS recharging, Gln4p depletion was simulated, confirming slowed translation. Modelling also revealed that Gln4p depletion causes negative feedback that matches translational demand for Gln-tRNAGlnto aaRS recharging capacity. This maintains normal charged tRNAGlnlevels despite Gln4p depletion, confirmed experimentally using tRNA Northern blotting. Model analysis resolves the paradox that Gln4p depletion triggers aGCN4response, despite maintenance of tRNAGlncharging levels, revealing that normally, the aaRS population can sequester free, uncharged tRNAs during aminoacylation. Gln4p depletion reduces this sequestration capacity, allowing uncharged tRNAGlnto interact with Gcn2 kinase. The study sheds new light on mutant aaRS disease aetiologies, and explains how aaRS sequestration of uncharged tRNAs can preventGCN4activation under non-starvation conditions.
YFR016c/Aip5 is part of an actin nucleation complex in budding yeast cells
Authors: Glomb Oliver , Bareis Lara , Johnsson Nils 
Published: April 2019

AbstractThe polarisome comprises a network of proteins that organizes polar growth in yeast and filamentous fungi. The yeastSaccharomyces cerevisiaeformin Bni1 and the actin-nucleation-promoting factor Bud6 are subunits of the polarisome that together catalyse the formation of actin filaments below the tip of budding yeast cells. We identified YFR016c (Aip5) as interaction partner of Bud6 and the polarisome scaffold Spa2. Yeast cells lacking Aip5 display a reduced number of actin cables. Aip5 binds with its N-terminal region to Spa2 and with its C-terminal region to Bud6. Both interactions collaborate to localize Aip5 at bud tip and neck, and are required to stimulate the formation of actin cables. Our experiments characterize Aip5 as a novel subunit of a complex that regulates the number of actin filaments at sites of polar growth.Summary statementYFR016c/Aip5 binds to the polarisome components Bud6 and Spa2 and supports the polarisome in the formation of actin filaments in yeast cells.
Characterizing the molecular and metabolic mechanisms of insecticide resistance in Anopheles gambiae s.l. in Faranah, Guinea
Authors: Stica Caleb , Jeffries Claire L. , Irish Seth R. , Barry Yaya , Camara Denka , Yansane Ismael , Kristan Mojca , Walker Thomas , Messenger Louisa A. 
Published: April 2019

AbstractBackgroundIn recent years, the scale-up of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) has greatly reduced malaria transmission. However, malaria remains a global public health concern with the majority of disease burden in sub-Saharan Africa. Insecticide resistance is a growing problem among Anopheles vector populations, with potential implications for the continued effectiveness of available control interventions. Improved understanding of current resistance levels and underlying mechanisms is essential to design appropriate management strategies and to mitigate future selection for resistance.MethodsAnopheles gambiae s.l. mosquitoes were collected from three villages in Faranah Prefecture, Guinea and their levels of susceptibility to seven insecticides were measured using CDC resistance intensity bioassays. Synergist assays with piperonyl butoxide (PBO) were also undertaken to assess the role of elevated mixed-function oxidases in resistance. RNA was extracted from 563 individuals and PCR was performed on cDNA to determine vector species, presence of target site mutations (L1014F kdr, N1575Y and G119S Ace-1), Plasmodium falciparum infection, and relative expression of three metabolic genes (CYP6M2, CYP6P3 and GSTD3).ResultsIn Faranah, resistance to permethrin and deltamethrin was observed, as well as possible resistance to bendiocarb. All assayed vector populations were fully susceptible to alpha-cypermethrin, pirimiphos-methyl, clothianidin and chlorfenapyr. Plasmodium falciparum infection was detected in 7.3% (37/508) mosquitoes tested. The L1014F kdr mutation was found in 100% of a sub-sample of 60 mosquitoes, supporting its fixation in the region. The N1575Y mutation was identified in 20% (113/561) of individuals, with ongoing selection evidenced by significant deviations from Hardy-Weinberg equilibrium. The G119S Ace-1 mutation was detected in 62.1% (18/29) of mosquitoes tested and was highly predictive of bendiocarb bioassay survival. The metabolic resistance genes, CYP6M2, CYP6P3 and GSTD3, were found to be overexpressed in wild resistant and susceptible An. gambiae s.s. populations, compared to a susceptible G3 colony. Furthermore, CYP6P3 was significantly overexpressed in bendiocarb survivors, implicating its potential role in carbamate resistance in Faranah.ConclusionsIdentification of intense resistance to permethrin and deltamethrin in Faranah, is of concern, as the Guinea National Malaria Control Program (NMCP) relies exclusively on the distribution of pyrethroid-treated LLINs for vector control. Study findings will be used to guide current and future control strategies in the region.
Optimized but not maximized cue integration for 3D visual perception
Authors: Chang Ting-Yu , Kim Byounghoon , Thompson Lowell , Sunkara Adhira , Doudlah Raymond , Rosenberg Ari 
Published: April 2019

AbstractReconstructing three-dimensional (3D) scenes from two-dimensional (2D) retinal images is an ill-posed problem. Despite this, our 3D perception of the world based on 2D retinal images is seemingly accurate and precise. The integration of distinct visual cues is essential for robust 3D perception in humans, but it is unclear if this mechanism is conserved in non-human primates, and how the underlying neural architecture constrains 3D perception. Here we assess 3D perception in macaque monkeys using a surface orientation discrimination task. We find that perception is generally accurate, but precision depends on the spatial pose of the surface and available cues. The results indicate that robust perception is achieved by dynamically reweighting the integration of stereoscopic and perspective cues according to their pose-dependent reliabilities. They further suggest that 3D perception is influenced by a prior for the 3D orientation statistics of natural scenes. We compare the data to simulations based on the responses of 3D orientation selective neurons. The results are explained by a model in which two independent neuronal populations representing stereoscopic and perspective cues (with perspective signals from the two eyes combined using nonlinear canonical computations) are optimally integrated through linear summation. Perception of combined-cue stimuli is optimal given this architecture. However, an alternative architecture in which stereoscopic cues and perspective cues detected by each eye are represented by three independent populations yields two times greater precision than observed. This implies that, due to canonical computations, cue integration for 3D perception is optimized but not maximized.Author summaryOur eyes only sense two-dimensional projections of the world (like a movie on a screen), yet we perceive the world in three dimensions. To create reliable 3D percepts, the human visual system integrates distinct visual signals according to their reliabilities, which depend on conditions such as how far away an object is located and how it is oriented. Here we find that non-human primates similarly integrate different 3D visual signals, and that their perception is influenced by the 3D orientation statistics of natural scenes. Cue integration is thus a conserved mechanism for creating robust 3D percepts by the primate brain. Using simulations of neural population activity, based on neuronal recordings from the same animals, we show that some computations which occur widely in the brain facilitate 3D perception, while others hinder perception. This work addresses key questions about how neural systems solve the difficult problem of generating 3D percepts, identifies a plausible neural architecture for implementing robust 3D vision, and reveals how neural computation can simultaneously optimize and curb perception.
Uncovering the Binding Mode of γ-Secretase Inhibitors
Authors: Hitzenberger M. , Zacharias M. 
Published: April 2019

AbstractKnowledge of how transition state inhibitors bind to γ-secretase is of major importance for the design of new Alzheimer’s disease therapies. Based on the known structure of γ-secretase in complex with a fragment of the amyloid precursor protein we have generated a structural model of γ-secretase in complex with the effective L-685,458 transition state inhibitor. The predicted binding mode is in excellent agreement with experimental data, mimicking all enzyme-substrate interactions at the active site and forming the relevant transition state geometry with the active site aspartate residues. In addition, we found that the stability of the complex is very likely also sensitive to the pH value. Comparative simulations on the binding of L-685,458 and the epimer L682,679 allowed us to explain the strongly reduced affinity of the epimer for γ-secretase. The structural model could form a valuable basis for the design of new or modified γ-secretase inhibitors.
Expansion of a fly TBI model to four levels of injury severity reveals synergistic effects of repetitive injury for moderate injury conditions
Authors: Putnam Lauren J , Willes Ashley M , Kalata Brooke E , Disher Nathaniel D , Brusich Douglas J 
Published: April 2019

ABSTRACTSeveral million traumatic brain injury (TBI) events are reported in the United States annually. However, mild TBI events often go unreported, and mild and repetitive mild TBI conditions are challenging to model. Fruit flies (Drosophila melanogaster) have gained traction for the study of TBI. The best-characterized fly TBI model is the high-impact trauma (HIT) method. We replicated the HIT method and confirmed several previous findings at the standard level of injury severity. We then expanded upon the HIT model by characterizing mortality across three reduced levels of injury severity. Importantly, we found reduced mortality with reduced injury severity and synergistic effects on mortality in response to repetitive TBI by our moderate injury conditions. Last, we compared moderate, repetitive TBI to a single severe TBI via assessment of the pattern of mortality and geotaxis performance in the 24 h following TBI. We found the number and severity of injuries could result in different patterns of death, while all TBI conditions led to impaired geotaxis compared to uninjured flies at 0.5 h and 6 h post-TBI. Thus, we have extended a well-characterized model of TBI in flies, and shown the utility of this model for making unique insights into TBI across various severities, injury numbers, and time-points post-injury.
Competitive Productivity (CP) at macro–meso–micro levels
Authors: Baumann Chris , Cherry Michael , Chu Wujin 
Published: April 2019

Purpose
The purpose of this paper is to advance our understanding of competitiveness. The authors introduce the concept of Competitive Productivity (CP), supplementing shortcomings of traditional understandings of national, organisational and individual productivity which overlook the nature of competitiveness, i.e. outperforming the competition, or at least bettering one’s own performance. The authors offer definitions, components and construct measurements of CP at three levels: macro, meso and micro.

Design/methodology/approach
A review of the literature was conducted to evaluate the need for combining productivity and competitiveness into one new construct. There are theories that combine these ideas – e.g., the resource-based theory of the firm – but the authors are presenting these concepts differently, or in a novel way. The authors’ focus on CP makes necessary a new group of construct measures which are different from that of the strategy literature: the authors measure an agent’s tendency “to be better than the competition” along multiple dimensions. Based on the CP construct, the authors present three testable models to uncover determinants of CP at three levels (macro, meso and micro). Finally, the work around “emergent property” can be applied to examine CP itself as being a determinant for other higher-order outcomes such as welfare, profits and life satisfaction. CP forms a platform to explore likely interplay (bottom-up and/or top-down mechanisms) within the micro–meso–macro architecture.

Findings
Three CP models were developed and are briefly discussed in this paper: first, a National Competitive Productivity (NCP) model to capture the components/drivers of national CP (macro level). Second, a Firm Competitive Productivity (FCP) model to capture the components/drivers of firm CP within an industry context (meso). And finally, an Individual Competitive Productivity (ICP) model capturing the components/drivers of CP at the individual (micro) level.

Originality/value
The study provides a combined approach to capture productivity and competitiveness within one innovative concept: CP. It can be used by government and policy makers (NCP model), managers and organisations (FCP model), and individuals such as workers and students (ICP model) to evaluate and enhance their performance. A better understanding of the components/drivers of CP at the three levels and the suggested measurement of CP should provide a stronger theory of competitiveness of nations, firms and individuals. Not least should a focus on the three levels (macro, meso and micro) better prepare citizens, firms, workers and students to effectively function and work in the marketplace and in society. The authors’ work should eventually contribute to more effective benchmarking and continuous improvement in the competitiveness domain. Crucially, this conceptual paper forms the foundation for future empirical testing of CP components in the context of the relative values and moderated behaviour as captured by the ReVaMB model.
When free gifts hurt the promoted product
Authors: Park Yookyung , Yi Youjae 
Published: April 2019

Purpose
The present study aims to demonstrate that providing a free gift upon purchase may induce consumers to devaluate the main product promoted with the offer. The mediating role of persuasion knowledge and the moderating role of consumer shopping orientation are also examined.

Design/methodology/approach
Three studies with between-subject designs are conducted to test the influence of product–gift fit on evaluations of the promoted product.

Findings
When a low-fit gift (vs a high-fit gift) is provided as a promotional offer, consumers’ evaluations of the promoted product are undermined. These negative effects are driven by consumers’ activation of persuasion knowledge on the company’s ulterior motive to entice consumers to make a purchase. Such devaluation effects occur especially for consumers with a task-focused shopping orientation, whereas they are mitigated for consumers with an experiential shopping orientation.

Research limitations/implications
This research extends the conceptualization of product–gift fit and challenges the common claim that free gift promotions maintain the value of the promoted product. By instigating a mechanism underlying consumers’ objections toward low-fit gifts, this research implies that consumers may think of an implicit cost to a free offer based on their knowledge of companies’ tactics.

Practical implications
Marketers should be aware of the fact that a certain gift may come at a cost for companies and bring about negative inferences regarding the main product. They need not only to select a gift that drives sales but also to be cautious about the gift’s influence on perceptions of the main product. Marketers should ensure that the gift has a good fit with the product while trying to discover a unique gift for consumers. Marketers should also provide an offer that matches shopping orientation of the target consumers.

Originality/value
This research reveals counterevidence to prior research claiming that free gift promotion does not hurt the perceived value of the promoted product. It enhances a theoretical understanding of devaluation effects and provides useful implications for designing and targeting free gift promotion.
Dynamic prediction of cardiovascular disease using improved LSTM
Authors: Junwei Kuang , Yang Hangzhou , Junjiang Liu , Zhijun Yan 
Published: April 2019

Purpose
Previous dynamic prediction models rarely handle multi-period data with different intervals, and the large-scale patient hospital records are not effectively used to improve the prediction performance. This paper aims to focus on the prediction of cardiovascular disease using the improved long short-term memory (LSTM) model.

Design/methodology/approach
A new model based on the traditional LSTM was proposed to predict cardiovascular disease. The irregular time interval is smoothed to obtain the time parameter vector, and it is used as the input of the forgetting gate of LSTM to overcome the prediction obstacle caused by the irregular time interval.

Findings
The experimental results show that the dynamic prediction model proposed in this paper obtained a significant better classification performance compared with the traditional LSTM model.

Originality/value
In this paper, the authors improved the LSTM by smoothing the irregular time between different medical stages of the patient to obtain the temporal feature vector.