bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dietary polyunsaturated fatty acid supply improves Daphnia performance during vertical migration
Authors: Navarro Jana Isanta , Fromherz Matthias , Dietz Michelle , Zeis Bettina , Schwarzenberger Anke , Martin-Creuzburg Dominik 
Published: May 2019

AbstractDiel vertical migration (DVM) is a common predator avoidance strategy of zooplankton. Migration to deeper water layers during the day to escape visually hunting predators most likely requires physiological adaptations to periodically changing temperatures. Polyunsaturated fatty acids (PUFA) are essential nutrients that play crucial roles in membrane temperature acclimation. Exposure to cold temperatures typically results in an increase in the relative abundance of PUFA in cell membranes and PUFA requirements of Daphnia have been shown to increase with decreasing temperatures.To assess the significance of dietary PUFA for coping with temperature fluctuations experienced during DVM, we reared Daphnia magna at either constantly warm or fluctuating temperatures simulating DVM both with and without dietary PUFA supplementation.We show that the well-known positive effect of dietary eicosapentaenoic acid (EPA) supplementation on offspring production and population growth rates of Daphnia is more pronounced at alternating temperatures than at constantly warm temperatures. Exposure to alternating temperatures caused modification in body PUFA concentrations and, consequently, increased lipid peroxidation. However, detrimental effects of lipid peroxidation were not evident.Our data demonstrate that the capacity to cope with the distinct temperature fluctuations experienced during DVM increases with dietary EPA supplementation, suggesting that an adequate dietary PUFA supply is crucial especially for migrating Daphnia populations. A dietary deficiency in long-chain PUFA may thus severely constrain predator evasion, potentially resulting in increased mortality and cascading effects on lower trophic levels.
Modelling tick bite risk by combining random forests and count data regression models
Authors: Garcia-Marti Irene , Zurita-Milla Raul , Swart Arno 
Published: May 2019

AbstractThe socio-economic and demographic changes occurred over the past 50 years have dramatically expanded urban areas around the globe, thus bringing urban settlers in closer contact with nature. Ticks have trespassed the limits of forests and grasslands to start inhabiting green spaces within metropolitan areas. Hence, the transmission of pathogens causing tick-borne diseases is an important threat to public health. Using volunteered tick bite reports collected by two Dutch initiatives, here we present a method to model tick bite risk using human exposure and tick hazard predictors. Our method represents a step forward in risk modelling, since we combine a well-known ensemble learning method, Random Forest, with four count data models of the (zero-inflated) Poisson family. This combination allows us to better model the disproportions inherent in the volunteered tick bite reports.Unlike canonical machine learning models, our method can capture the overdispersion or zero-inflation inherent in data, thus yielding tick bite risk predictions that resemble the original signal captured by volunteers. Mapping model predictions enables a visual inspection of the spatial patterns of tick bite risk in the Netherlands. The Veluwe national park and the Utrechtse Heuvelrug forest, which are large forest-urban interfaces with several cities, are areas with high tick bite risk. This is expected, since these are popular places for recreation and tick activity is high in forests. However, our model can also predict high risk in less-intensively visited recreational areas, such as the patchy forests in the northeast of the country, the natural areas along the coastline, or some of the Frisian Islands. Our model could help public health specialists to design mitigation strategies for tick-borne diseases, and to target risky areas with awareness and prevention campaigns.
Circulating electrolytes and the prevalence of atrial fibrillation and supraventricular ectopy: the Atherosclerosis Risk in Communities (ARIC) Study
Authors: Alonso Alvaro , Rooney Mary R. , Chen Lin Yee , Norby Faye L. , Saenger Amy K. , Soliman Elsayed Z. , O’Neal Wesley T. , Hootman Katie C. , Selvin Elizabeth , Lutsey Pamela L. 
Published: May 2019

ABSTRACTBackgroundEvaluating associations of circulating electrolytes with atrial fibrillation (AF) and burden of supraventricular arrhythmias can give insights into arrhythmia pathogenesis.MethodsWe conducted a cross-sectional analysis of 6,398 participants of the Atherosclerosis Risk in Communities (ARIC) study, ages 71-90, with data on serum electrolytes (magnesium, calcium, potassium, phosphorus, chloride, sodium). Prevalence of AF was determined from study 12-lead electrocardiograms and prior history of AF-related hospitalizations. A subset of 317 participants also underwent electrocardiographic recordings for up to 14 days using the Zio®patch. Burden of other supraventricular arrhythmias [premature atrial contractions (PACs), supraventricular tachycardia] was determined with the Zio®patch. We used multivariable logistic and linear regression adjusting for potential confounders to determine associations of electrolytes with arrhythmia prevalence and burden.ResultsAmong 6,394 eligible participants, 614 (10%) had prevalent AF. Participants in the top quintiles of magnesium [odds ratio (OR) 0.82, 95% confidence interval (CI) 0.62, 1.08], potassium (OR 0.82, 95%CI 0.68, 1.00), and phosphorus (OR 0.73, 95%CI 0.59, 0.89) had lower prevalence of AF compared to those in the bottom quintiles. No clear association was found for circulating chloride, calcium or sodium. Higher concentrations of circulating calcium were associated with lower prevalence of PACs using a standard 12-lead electrocardiogram, while higher concentrations of potassium, chloride and sodium were associated with higher PAC prevalence. Circulating electrolytes were not significantly associated with the burden of PACs or supraventricular tachycardia among a subset of 317 participants with extended electrocardiographic monitoring.ConclusionConcentrations of circulating electrolytes present complex associations with selected supraventricular arrhythmias. Future studies should evaluate underlying mechanisms.
Electron cryo-microscopy of Bacteriophage PR772 reveals the composition and structure of the elusive vertex complex and the capsid architecture
Authors: Reddy Hemanth. K. N. , Hajdu Janos , Carroni Marta , Svenda Martin 
Published: May 2019

AbstractBacteriophage PR772, a member of theTectiviridaefamily, has a 70-nm diameter icosahedral protein capsid that encapsulates a lipid membrane, dsDNA, and various internal proteins. An icosahedrally averaged CryoEM reconstruction of the wild-type virion and a localized reconstruction of the vertex region reveals the composition and the structure of the vertex complex along with new protein conformations that play a vital role in maintaining the capsid architecture of the virion. The overall resolution of the virion is 2.75 Å, while the resolution of the protein capsid is 2.3 Å. The conventional penta-symmetron formed by the capsomeres is replaced by a large vertex complex in the pseudo T=25 capsid. All the vertices contain the host-recognition protein, P5; two of these vertices show the presence of the receptor-binding protein, P2. The 3D structure of the vertex complex shows interactions with the viral membrane, indicating a possible mechanism for viral infection.
Weaker neural suppression in autism
Authors: Schallmo Michael-Paul , Kolodny Tamar , Kale Alexander M. , Millin Rachel , Flevaris Anastasia V. , Edden Richard A.E. , Gerdts Jennifer , Bernier Raphael A. , Murray Scott O. 
Published: May 2019

AbstractIncreased neural excitation resulting from weakened inhibition is a leading hypothesis for the pathophysiology of autism. However, experimental support in humans remains equivocal. Alternatively, modulatory processes that suppress neural responses but do not specifically rely on inhibition may be impacted in ASD. Leveraging well-characterized suppressive neural circuits in the visual system, we used behavioral and fMRI tasks to demonstrate a significant reduction in neural suppression in young adults with ASD compared to neurotypical controls. We further tested the mechanism of this suppression by measuring levels of the inhibitory neurotransmitter GABA, and found no differences in GABA between groups. We show how a computational model that incorporates divisive normalization, as well as narrower top-down gain (that could result, for example, from a narrower window of attention), can explain our observations and divergent previous findings. Thus, weaker neural suppression in ASD may be attributable to differences in top-down processing, but not to differences in GABA levels.
Personality and local brain structure: their shared genetic basis and reproducibility
Authors: Valk Sofie L. , Hoffstaedter Felix , Camilleri Julia A. , Kochunov Peter , Thomas Yeo B.T. , Eickhoff Simon B. 
Published: May 2019

AbstractLocal variation in cortical architecture is highly heritable and distinct genes are associated with specific cortical regions. Total surface area has been shown to be genetically correlated with complex cognitive capacities, suggesting cortical brain structure is a viable endophenotype linking genes to behavior. However, to what extend local brain structure has a genetic association with cognitive and emotional functioning is incompletely understood. Here, we study the genetic correlation between personality traits and local cortical structure in a large-scale twin sample (Human Connectome Project, n=1106, 22-37y). We found a genetic overlap between personality traits and local cortical structure in 10 of 17 observed phenotypic associations in predominantly frontal cortices. To evaluate the robustness of observed personality-brain associations we studied two independent age-matched samples (GSP: n=926, age=19-35y, eNKI: n=210, age: 19-39y). We observed anecdotal to moderate evidence for a successful replication of the negative association between surface area in medial prefrontal cortex and Neuroticism in both samples. Quantitative functional decoding indicated this region is implicated in emotional and socio-cognitive functional processes. In sum, our observations suggest that associations between local brain structure and personality are, in part, under genetic control. However, associations are weak and only the relation between frontal surface area and Neuroticism was consistently observed across three independent samples of young adults.
Intermittent theta burst stimulation at personalized targets reduces the functional connectivity of the default mode network in healthy subjects
Authors: Singh Aditya , Erwin-Grabner Tracy , Sutcliffe Grant , Paulus Walter , Dechent Peter , Antal Andrea , Goya-Maldonado Roberto 
Published: May 2019

AbstractUnderstanding the mechanisms by which transcranial magnetic stimulation protocols exert changes in the default mode network (DMN) is paramount to develop therapeutically more effective approaches in the future. A full session (3000 pulses) of 10 Hz repetitive transcranial magnetic stimulation (HF-rTMS) reduces the functional connectivity (FC) of the DMN and the subgenual anterior cingulate cortex but current understanding of the effects of a single session of intermittent theta burst stimulation (iTBS) on the DMN in healthy subjects is limited. To reduce the effects of inter-individual variability in functional architectures, we used a novel personalized target selection approach based on each subject’s resting state fMRI for an unprecedented investigation into the effects of a single session (1800 pulses) of iTBS over the DMN in healthy controls. 26 healthy subjects participated in a double-blind, crossover, sham-controlled study. After iTBS to the personalized left dorsolateral prefrontal cortex (DLPFC) targets, we investigated the time lapse of effects in the DMN and its relationship to the harm avoidance (HA) personality trait measure (Temperament and Character Inventory/TCI). Approx. 25-30 minutes after stimulation, we observed reduced FC between the DMN and the rostral anterior cingulate cortex (rACC). About 45 minutes after stimulation the FC of rACC strongly decreased further, as did the FC of right anterior insula (rAI) with the DMN. We also report a positive correlation between the FC decrease in the rACC and the HA domain of TCI. Our results show how iTBS at personalized left-DLPFC targets reduces the FC between DMN and the rACC and rAI, regions typically described as nodes of the salience network. We find that HA scores can potentially predict iTBS response, as has been observed for HF-rTMS.
Visual epidural field potentials possess high functional specificity in single trials
Authors: Fischer Benjamin , Schander Andreas , Kreiter Andreas K. , Lang Walter , Wegener Detlef 
Published: May 2019

AbstractRecordings of epidural field potentials (EFPs) allow to acquire neuronal activity over a large region of cortical tissue with minimal invasiveness. Because electrodes are placed on top of the dura and do not enter the neuronal tissue, EFPs offer intriguing options for both clinical and basic science research. On the other hand, EFPs represent the integrated activity of larger neuronal populations, possess a higher trial-by-trial variability, and a reduced signal-to-noise ratio due the additional barrier of the dura. It is thus unclear whether and to what extent EFPs have sufficient spatial selectivity to allow for conclusions about the underlying functional cortical architecture, and whether single EFP trials provide enough information on the short time scales relevant for many clinical and basic neuroscience purposes. We here use the high spatial resolution of primary visual cortex to address these issues and investigate the extent to which very short EFP traces allow reliable decoding of spatial information. We briefly presented different visual objects at one out of nine closely adjacent locations and recorded neuronal activity with a high-density, epidural multi-electrode array in three macaque monkeys. Using receiver-operating characteristics to identify most-informative data, machine-learning algorithms provided close-to-perfect classification rates for all 27 stimulus conditions. A binary classifier applying a simple max function on ROC-selected data further showed that single trials might be classified with 100% performance even without advanced offline classifiers. Thus, although highly variable, EFPs constitute an extremely valuable source of information and offer new perspectives for minimally invasive recording of large-scale networks.
Multiplex secretome engineering enhances recombinant protein production and purity
Authors: Kol Stefan , Ley Daniel , Wulff Tune , Decker Marianne , Arnsdorf Johnny , Gutierrez Jahir M. , Chiang Austin W.T. , Pedersen Lasse Ebdrup , Kildegaard Helene Faustrup , Lee Gyun Min , Lewis Nathan E. 
Published: May 2019

AbstractHost cell proteins (HCPs) are process-related impurities generated during biotherapeutic protein production. HCPs can be problematic if they pose a significant metabolic demand, degrade product quality, or contaminate the final product. Here, we present an effort to create a “clean” Chinese hamster ovary (CHO) cell by disrupting multiple genes to eliminate HCPs. Using a model of CHO cell protein secretion, we predicted the elimination of unnecessary HCPs could have a non-negligible impact on protein production. We analyzed the total HCP content of 6-protein, 11-protein, and 14-protein knockout clones and characterized their growth in shake flasks and bioreactors. These cell lines exhibited a substantial reduction in total HCP content (40%-70%). We also observed higher productivity and improved growth characteristics, in specific clones. With the reduced HCP content, protein A and ion exchange chromatography more efficiently purified a monoclonal antibody (mAb) produced in these cells during a three-step purification process. Thus, substantial improvements can be made in protein titer and purity through large-scale HCP deletion, providing an avenue to increased quality and affordability of high-value biopharmaceuticals.
Sensory Processing and Categorization in Cortical and Deep Neural Networks
Authors: Pinotsis Dimitris A. , Siegel Markus , Miller Earl K. 
Published: May 2019

AbstractMany recent advances in artificial intelligence (AI) are rooted in visual neuroscience. However, ideas from more complicated paradigms like decision-making are less used. Although automated decision-making systems are ubiquitous (driverless cars, pilot support systems, medical diagnosis algorithms etc.), achieving human-level performance in decision making tasks is still a challenge. At the same time, these tasks that are hard for AI are easy for humans. Thus, understanding human brain dynamics during these decision-making tasks and modeling them using deep neural networks could improve AI performance. Here we modelled some of the complex neural interactions during a sensorimotor decision making task. We investigated how brain dynamics flexibly represented and distinguished between sensory processing and categorization in two sensory domains: motion direction and color. We used two different approaches for understanding neural representations. We compared brain responses to 1) the geometry of a sensory or category domain (domain selectivity) and 2) predictions from deep neural networks (computation selectivity). Both approaches gave us similar results. This confirmed the validity of our analyses. Using the first approach, we found that neural representations changed depending on context. We then trained deep recurrent neural networks to perform the same tasks as the animals. Using the second approach, we found that computations in different brain areas also changed flexibly depending on context. Color computations appeared to rely more on sensory processing, while motion computations more on abstract categories. Overall, our results shed light to the biological basis of categorization and differences in selectivity and computations in different brain areas. They also suggest a way for studying sensory and categorical representations in the brain: compare brain responses to both a behavioral model and a deep neural network and test if they give similar results.
Genomics of clinal local adaptation inPinus sylvestrisunder continuous environmental and spatial genetic setting
Authors: Tyrmi Jaakko S. , Vuosku Jaana , Acosta Juan J. , Li Zhen , Sterck Lieven , Cervera Maria T. , Savolainen Outi , Pyhäjärvi Tanja 
Published: May 2019

AbstractUnderstanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic background often remains elusive. We examined the patterns of genetic diversity inPinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. MakingP. sylvestrisan even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we found that several coding loci contribute to local adaptation. We also discovered a very large (ca. 300 Mbp) putative inversion with a signal of local adaptation, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out to the need for more attention towards multi-locus analysis of polygenic adaptation.
Analysis of leaf microbiome composition of near-isogenic maize lines differing in broad-spectrum disease resistance
Authors: Wagner Maggie R. , Busby Posy E. , Balint-Kurti Peter 
Published: May 2019

SummaryPlant genotype strongly affects disease resistance, and also influences the composition of the leaf microbiome. However, these processes have not been studied and linked in the microevolutionary context of breeding for improved disease resistance. We hypothesized that broad-spectrum disease resistance alleles also affect colonization by non-pathogenic symbionts.Quantitative trait loci (QTL) conferring resistance to multiple fungal pathogens were introgressed into a disease-susceptible maize inbred line. Bacterial and fungal leaf microbiomes of the resulting near-isogenic lines were compared to the microbiome of the disease-susceptible parent line at two timepoints in multiple fields.Introgression of QTL from disease-resistant lines strongly shifted the relative abundance of diverse fungal and bacterial taxa in both 3-week-old and 7-week-old plants. Nevertheless, the effects on overall community structure and diversity were minor and varied among fields and years. Contrary to our expectations, host genotype effects were not any stronger in fields with high disease pressure than in uninfected fields, and microbiome succession over time was similar in heavily infected plants and uninfected plants.These results show that introgressed QTL can greatly improve broad-spectrum disease resistance while having only limited and inconsistent pleiotropic effects on the leaf microbiome in maize.
Optimal Recovery of Missing Values for Non-negative Matrix Factorization
Authors: Chen Rebecca , Varshney Lav R. 
Published: May 2019

AbstractWe extend the approximation-theoretic technique of optimal recovery to the setting of imputing missing values in clustered data, specifically for non-negative matrix factorization (NMF), and develop an implementable algorithm. Under certain geometric conditions, we prove tight upper bounds on NMF relative error, which is the first bound of this type for missing values. We also give probabilistic bounds for the same geometric assumptions. Experiments on image data and biological data show that this theoretically-grounded technique performs as well as or better than other imputation techniques that account for local structure.
Early Ictal Recruitment of Midline Thalamus in Mesial Temporal Lobe Epilepsy
Authors: Romeo Andrew , Issa Roach Alexandra T. , Toth Emilia , Chaitanya G. , Ilyas Adeel , Riley Kristen O. , Pati Sandipan 
Published: May 2019

AbstractThe causal role of midline thalamus in the initiation and early organization of mesial temporal lobe seizures is studied. Three patients undergoing stereoelectroencephalography were enrolled for the placement of an additional depth electrode targeting the midline thalamus. The midline thalamus was recruited in all three patients at varying points of seizure initiation (0-13 seconds) and early propagation (9-60 seconds). Stimulation of either thalamus or hippocampus induced similar habitual seizures. Seizure-induced in the hippocampus rapidly recruited the thalamus. Evoked potentials demonstrated stronger connectivity from the hippocampus to the thalamus than in the opposite direction. The midline thalamus can be within the seizure initiation and symptomatogenic circuits.