bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of α2,6-sialyltransferases for sialylation of therapeutic proteins
Authors: Janesch Bettina , Saxena Hirak , Sim Lyann , Wakarchuk Warren W 
Published: July 2019

AbstractThe development of therapeutic proteins for the treatment of numerous diseases is one of the fastest growing areas of biotechnology. Therapeutic efficacy and serum half-life are particularly important, and these properties rely heavily on the glycosylation state of the protein. Expression systems to produce authentically fully glycosylated therapeutic proteins with appropriate terminal sialic acids are not yet perfected. The in vitro modification of therapeutic proteins by recombinant sialyltransferases offers a promising and elegant strategy to overcome this problem. Thus, the detailed expression and characterization of sialyltransferases for completion of the glycan chains is of great interest to the community. We identified a novel α2,6-sialyltransferase from Helicobacter cetorum and compared it to the human ST6Gal1 and a Photobacterium sp. sialyltransferase using glycoprotein substrates in a 96-well microtiter-plate-based assay. We demonstrated that the recombinant α2,6-sialyltransferase from H. cetorum is an excellent catalyst for modification of N-linked glycans of different therapeutic proteins.
Eliminating Meningococcal Epidemics From the African Meningitis Belt: The Case for Advanced Prevention and Control Using Next-Generation Meningococcal Conjugate Vaccines
Authors: Alderson Mark R , LaForce F Marc , Sobanjo-ter Meulen Ajoke , Hwang Angela , Preziosi Marie-Pierre , Klugman Keith P 
Published: July 2019

AbstractThe introduction and rollout of a meningococcal serogroup A conjugate vaccine, MenAfriVac, in the African meningitis belt has eliminated serogroup A meningococcal infections for >300 million Africans. However, serogroup C, W, and X meningococci continue to circulate and have been responsible for focal epidemics in meningitis belt countries. Affordable multivalent meningococcal conjugate vaccines are being developed to prevent these non-A epidemics. This article describes the current epidemiologic situation and status of vaccine development and highlights questions to be addressed to most efficiently use these new vaccines.
Medical knowledge infused convolutional neural networks for cohort selection in clinical trials
Authors: Chen Chi-Jen , Warikoo Neha , Chang Yung-Chun , Chen Jin-Hua , Hsu Wen-Lian 
Published: July 2019

Abstract

Objective
In this era of digitized health records, there has been a marked interest in using de-identified patient records for conducting various health related surveys. To assist in this research effort, we developed a novel clinical data representation model entitled medical knowledge-infused convolutional neural network (MKCNN), which is used for learning the clinical trial criteria eligibility status of patients to participate in cohort studies.

Materials and Methods
In this study, we propose a clinical text representation infused with medical knowledge (MK). First, we isolate the noise from the relevant data using a medically relevant description extractor; then we utilize log-likelihood ratio based weights from selected sentences to highlight “met” and “not-met” knowledge-infused representations in bichannel setting for each instance. The combined medical knowledge-infused representation (MK) from these modules helps identify significant clinical criteria semantics, which in turn renders effective learning when used with a convolutional neural network architecture.

Results
MKCNN outperforms other Medical Knowledge (MK) relevant learning architectures by approximately 3%; notably SVM and XGBoost implementations developed in this study. MKCNN scored 86.1% on F1metric, a gain of 6% above the average performance assessed from the submissions for n2c2 task. Although pattern/rule-based methods show a higher average performance for the n2c2 clinical data set, MKCNN significantly improves performance of machine learning implementations for clinical datasets.

Conclusion
MKCNN scored 86.1% on the F1 score metric. In contrast to many of the rule-based systems introduced during the n2c2 challenge workshop, our system presents a model that heavily draws on machine-based learning. In addition, the MK representations add more value to clinical comprehension and interpretation of natural texts.
Gender and Embodied War Knowledge
Authors: Waldron Thea , Baines Erin 
Published: July 2019

AbstractUN Security Council Resolution 1325 (adopted in 2000) seeks to protect women’s bodily integrity in war and promote women’s rights to participate in decisions affecting them in the realm of peace and security. Its normative framework offers potential to transform how peace and security is framed in the UN Security Council. At the same time, critics charge that the Women, Peace and Security agenda reproduces problematic categories, including women as a static, homogeneous social group, binaries such as peace and war as clearly delineated events, and victims and perpetrators as gendered, oppositional groups. In this article, we strive to think critically about gender and human rights through the rubric of the Women, Peace and Security agenda and problematic categories that underpin its design. We do so by exploring gender and embodied knowledge in war.
Inter-alpha Inhibitor Proteins Modulate Neuroinflammatory Biomarkers After Hypoxia-Ischemia in Neonatal Rats
Authors: Barrios-Anderson Adriel , Chen Xiaodi , Nakada Sakura , Chen Ray , Lim Yow-Pin , Stonestreet Barbara S 
Published: July 2019

AbstractNeuroinflammation contributes to hypoxic-ischemic (HI) brain injury. Inter-alpha inhibitor proteins (IAIPs) have important immunomodulatory properties. Human (h) plasma-derived IAIPs reduce brain injury and improve neurobehavioral outcomes after HI. However, the effects of hIAIPs on neuroinflammatory biomarkers after HI have not been examined. We determined whether hIAIPs attenuated HI-related neuroinflammation. Postnatal day-7 rats exposed to sham-placebo, or right carotid ligation and 8% oxygen for 90 minutes with placebo, and hIAIP treatment were studied. hIAIPs (30 mg/kg) or PL was injected intraperitoneally immediately, 24, and 48 hours after HI. Rat complete blood counts and sex were determined. Brain tissue and peripheral blood were prepared for analysis 72 hours after HI. The effects of hIAIPs on HI-induced neuroinflammation were quantified by image analysis of positively stained astrocytic (glial fibrillary acid protein [GFAP]), microglial (ionized calcium binding adaptor molecule-1 [Iba-1]), neutrophilic (myeloperoxidase [MPO]), matrix metalloproteinase-9 (MMP9), and MMP9-MPO cellular markers in brain regions. hIAIPs reduced quantities of cortical GFAP, hippocampal Iba-1-positive microglia, corpus callosum MPO, and cortical MMP9-MPO cells and the percent of neutrophils in peripheral blood after HI in male, but not female rats. hIAIPs modulate neuroinflammatory biomarkers in the neonatal brain after HI and may exhibit sex-related differential effects.
Bias and robustness of eccentricity estimates from radial velocity data
Authors: Hara Nathan C , Boué G , Laskar J , Delisle J-B , Unger N 
Published: July 2019

ABSTRACTEccentricity is a parameter of particular interest as it is an informative indicator of the past of planetary systems. It is however not always clear whether the eccentricity fitted on radial velocity data is real or if it is an artefact of an inappropriate modelling. In this work, we address this question in two steps: we first assume that the model used for inference is correct and present interesting features of classical estimators. Secondly, we study whether the eccentricity estimates are to be trusted when the data contain incorrectly modelled signals, such as missed planetary companions, non-Gaussian noises, correlated noises with unknown covariance, etc. Our main conclusion is that data analysis via posterior distributions, with a model including a free error term gives reliable results provided two conditions. First, convergence of the numerical methods needs to be ascertained. Secondly, the noise power spectrum should not have a particularly strong peak at the semiperiod of the planet of interest. As a consequence, it is difficult to determine if the signal of an apparently eccentric planet might be due to another inner companion in 2:1 mean motion resonance. We study the use of Bayes factors to disentangle these cases. Finally, we suggest methods to check if there are hints of an incorrect model in the residuals. We show on simulated data the performance of our methods and comment on the eccentricities of Proxima b and 55 Cnc f.
Multiphase gas in the circumgalactic medium: relative role of tcool/tff and density fluctuations
Authors: Pal Choudhury Prakriti , Sharma Prateek , Quataert Eliot 
Published: July 2019

ABSTRACT
We perform a suite of simulations with realistic gravity and thermal balance in shells to quantify the role of the ratio of cooling time to the free-fall time (tcool/tff) and the amplitude of density perturbations (δρ/ρ) in the production of multiphase gas in the circumgalactic medium (CGM). Previous idealized simulations, focusing on small amplitude perturbations in the intracluster medium (ICM), found that cold gas can condense out of the hot ICM in global thermal balance when the background tcool/tff ≲ 10. Recent observations suggest the presence of cold gas even when the background profiles have somewhat large values of tcool/tff. This partly motivates a better understanding of additional factors such as large density perturbations that can enhance the propensity for cooling and condensation even when the background tcool/tff is high. Such large density contrasts can be seeded by galaxy wakes or dense cosmological filaments. From our simulations, we introduce a condensation curve in the (δρ/ρ) – min(tcool/tff) space, which defines the threshold for condensation of multiphase gas in the CGM. We show that this condensation curve corresponds to (tcool/tff)blob ≲ 10 applied to the overdense blob instead of the background for which tcool/tff can be higher. We also study the modification in the condensation curve by varying entropy stratification. Steeper (positive) entropy gradients shift the condensation curve to higher amplitudes of perturbations (i.e. make condensation difficult). A constant entropy core, applicable to the CGM in smaller haloes, shows condensation over a larger range of radii as compared to the steeper entropy profiles in the ICM.
Are the observed gaps in protoplanetary discs caused by growing planets?
Authors: Ndugu N , Bitsch B , Jurua E 
Published: July 2019

ABSTRACT
Recent detailed observations of protoplanetary discs revealed a lot of substructures that are mostly ring like. One interpretation is that these rings are caused by growing planets. These potential planets are not yet opening very deep gaps in their discs. These planets instead form small gaps in the discs to generate small pressure bumps exterior to their orbits that stop the inflow of the largest dust particles. In the pebble accretion paradigm, this planetary mass corresponds to the pebble isolation mass, where pebble accretion stops and efficient gas accretion starts. We perform planet population synthesis via pebble and gas accretion including type-I and type-II migration. In the first stage of our simulations, we investigate the conditions necessary for planets to reach the pebble isolation mass and compare their position to the observed gaps. We find that in order to match the gap structures 2000ME in pebbles is needed, which would be only available for the most metal-rich stars. We then follow the evolution of these planets for a few Myr to compare the resulting population with the observed exoplanet populations. Planet formation in discs with these large amounts of pebbles results in mostly forming gas giants and only very little super-Earths, contradicting observations. This leads to the conclusions that either (i) the observed discs are exceptions, (ii) not all gaps in observed discs are caused by planets, or (iii) that we miss some important ingredients in planet formation related to gas accretion and/or planet migration.
Optimizing sparse RFI prediction using deep learning
Authors: Kerrigan Joshua , Plante Paul La , Kohn Saul , Pober Jonathan C , Aguirre James , Abdurashidova Zara , Alexander Paul , Ali Zaki S , Balfour Yanga , Beardsley Adam P , Bernardi Gianni , Bowman Judd D , Bradley Richard F , Burba Jacob , Carilli Chris L , Cheng Carina , DeBoer David R , Dexter Matt , Acedo Eloy de Lera , Dillon Joshua S , Estrada Julia , Ewall-Wice Aaron , Fagnoni Nicolas , Fritz Randall , Furlanetto Steve R , Glendenning Brian , Greig Bradley , Grobbelaar Jasper , Gorthi Deepthi , Halday Ziyaad , Hazelton Bryna J , Hickish Jack , Jacobs Daniel C , Julius Austin , Kern Nicholas S , Kittiwisit Piyanat , Kolopanis Matthew , Lanman Adam , Lekalake Telalo , Liu Adrian , MacMahon David , Malan Lourence , Malgas Cresshim , Maree Matthys , Martinot Zachary E , Matsetela Eunice , Mesinger Andrei , Molewa Mathakane , Morales Miguel F , Mosiane Tshegofalang , Neben Abraham R , Parsons Aaron R , Patra Nipanjana , Pieterse Samantha , Razavi-Ghods Nima , Ringuette Jon , Robnett James , Rosie Kathryn , Sims Peter , Smith Craig , Syce Angelo , Thyagarajan Nithyanandan , Williams Peter K G , Zheng Haoxuan 
Published: July 2019

ABSTRACT
Radio frequency interference (RFI) is an ever-present limiting factor among radio telescopes even in the most remote observing locations. When looking to retain the maximum amount of sensitivity and reduce contamination for Epoch of Reionization studies, the identification and removal of RFI is especially important. In addition to improved RFI identification, we must also take into account computational efficiency of the RFI-Identification algorithm as radio interferometer arrays such as the Hydrogen Epoch of Reionization Array (HERA) grow larger in number of receivers. To address this, we present a deep fully convolutional neural network (DFCN) that is comprehensive in its use of interferometric data, where both amplitude and phase information are used jointly for identifying RFI. We train the network using simulated HERA visibilities containing mock RFI, yielding a known ‘ground truth’ data set for evaluating the accuracy of various RFI algorithms. Evaluation of the DFCN model is performed on observations from the 67 dish build-out, HERA-67, and achieves a data throughput of 1.6 × 105 HERA time-ordered 1024 channelled visibilities per hour per GPU. We determine that relative to an amplitude only network including visibility phase adds important adjacent time–frequency context which increases discrimination between RFI and non-RFI. The inclusion of phase when predicting achieves a recall of 0.81, precision of 0.58, and F2 score of 0.75 as applied to our HERA-67 observations.
Sunspot observations by Charles Malapert during the period 1618–1626: a key data set to understand solar activity before the Maunder minimum
Authors: Carrasco V M S , Gallego M C , Villalba Álvarez J , Vaquero J M 
Published: July 2019

ABSTRACT
A revision is presented of the sunspot observations made by Charles Malapert from 1618 to 1626, studying several documentary sources that include those observations. The revised accounting of the group numbers recorded by Malapert for that period shows new information unavailable in the current sunspot group data base. The average solar activity level calculated from these revised records of Malapert is by almost one-third greater than that calculated from his records included in the current group data base. Comparison of the sunspot observations made by Malapert and by other astronomers of that time with regard to the number of recorded groups and sunspot positions on the solar disc shows good agreement. Malapert reported that he only recorded one sunspot group in each sunspot drawing presented in Austriaca Sidera Heliocyclia (the documentary source that includes most of the sunspot records made by Malapert), although he sometimes observed several groups. Therefore, the sunspot counts obtained in this work on Malapert's sunspot observations represent the lower limit of the solar activity level corresponding to those records.
Ambipolar diffusion and the molecular abundances in pre-stellar cores
Authors: Priestley Felix D , Wurster James , Viti Serena 
Published: July 2019

ABSTRACT
We investigate differences in the molecular abundances between magnetically super- and subcritical pre-stellar cores, performing three-dimensional non-ideal magnetohydrodynamical (MHD) simulations with varying densities and magnetic field strengths, and post-processing the results with a time-dependent gas–grain chemical code. Most molecular species show significantly more central depletion in subcritical models, due to the longer duration of collapse. However, the directly observable quantities – the molecule to hydrogen column density ratios – are generally too similar for observational data to discriminate between models. The profiles of N2H+ and HCO+ show qualitative differences between supercritical and subcritical models on scales of $0.01 \, {\rm pc}$, which may allow the two cases to be distinguished. However, this requires knowledge of the hydrogen column density, which is not directly measureable, and predicted line intensity profiles from radiative transfer modelling are similar for these molecules. Other commonly observed species, such as HCN and CH3OH, have line intensity profiles that differ more strongly between models, and so are more promising as tracers of the mechanism of cloud collapse.
Envelopes of embedded super-Earths – II. Three-dimensional isothermal simulations
Authors: Béthune William , Rafikov Roman R 
Published: July 2019

ABSTRACT
Massive planetary cores embedded in protoplanetary discs are believed to accrete extended atmospheres, providing a pathway to forming gas giants and gas-rich super-Earths. The properties of these atmospheres strongly depend on the nature of the coupling between the atmosphere and the surrounding disc. We examine the formation of gaseous envelopes around massive planetary cores via three-dimensional inviscid and isothermal hydrodynamic simulations. We focus the changes in the envelope properties as the core mass varies from low (subthermal) to high (superthermal) values, a regime relevant to close-in super-Earths. We show that global envelope properties such as the amount of rotational support or turbulent mixing are mostly sensitive to the ratio of the Bondi radius of the core to its physical size. High-mass cores are fed by supersonic inflows arriving along the polar axis and shocking on the densest parts of the envelope, driving turbulence, and mass accretion. Gas flows out of the core’s Hill sphere in the equatorial plane, describing a global mass circulation through the envelope. The shell of shocked gas atop the core surface delimits regions of slow (inside) and fast (outside) material recycling by gas from the surrounding disc. While recycling hinders the runaway growth towards gas giants, the inner regions of protoplanetary atmospheres, more immune to mixing, may remain bound to the planet.
Dwarf spheroidal J-factor likelihoods for generalized NFW profiles
Authors: Chiappo A , Cohen-Tanugi J , Conrad J , Strigari L E 
Published: July 2019

ABSTRACT
Indirect detection strategies of particle dark matter (DM) in Dwarf spheroidal satellite galaxies (dSphs) typically entail searching for annihilation signals above the astrophysical background. To robustly compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data – which are generally frequentist – rely on estimating the abundance of DM by calculating the so-called J factor. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph using the Jeans equation, commonly by means of Bayesian techniques that entail the presence (and additional systematic uncertainty) of prior choice. Here, extending earlier work, we develop a scheme to derive the profile likelihood for J factors of dwarf spheroidals for models with five or more free parameters. We validate our method on a publicly available simulation suite, released by the Gaia Challenge, finding satisfactory statistical properties for bias and probability coverage. We present the profile likelihood function and maximum likelihood estimates for the J-factor of 10 dSphs. As an illustration, we apply these profile likelihoods to recently published analyses of γ-ray data with the Fermi Large Area Telescope to derive new, consistent upper limits on the DM annihilation cross-section. We do this for a subset of systems, generally referred to as classical dwarfs. The implications of these findings for DM searches are discussed, together with future improvements and extensions of this technique.
Thermodynamics of pure fast solar wind: radial evolution of the temperature–speed relationship in the inner heliosphere
Authors: Perrone Denise , Stansby D , Horbury T S , Matteini L 
Published: July 2019

ABSTRACT
A strong correlation between speed and proton temperature has been observed, across many years, on hourly averaged measurements in the solar wind. Here, we show that this relationship is also observed at a smaller scale on intervals of a few days, within a single stream. Following the radial evolution of a well-defined stream of coronal-hole plasma, we show that the temperature–speed (T–V) relationship evolves with distance, implying that the T–V relationship at 1 au cannot be used as a proxy for that near the Sun. We suggest that this behaviour could be a combination of the anticorrelation between speed and flux-tube expansion factor near the Sun and the effect of a continuous heating experienced by the plasma during the expansion. We also show that the cooling index for the radial evolution of the temperature is a function of the speed. In particular, T⊥ in faster wind, although higher close to the Sun, decreases more quickly with respect to slower wind, suggesting that it has less time to interact with the mechanism(s) able to heat the plasma. Finally, we predict the expected T–V relationship in fast streams closer to the Sun with respect to the Helios observations, which Parker Solar Probe will explore in the near future.
Conserved regions in long non-coding RNAs contain abundant translation and protein–RNA interaction signatures
Authors: Ruiz-Orera Jorge , Albà M Mar 
Published: July 2019

Abstract
The mammalian transcriptome includes thousands of transcripts that do not correspond to annotated protein-coding genes and that are known as long non-coding RNAs (lncRNAs). A handful of lncRNAs have well-characterized regulatory functions but the biological significance of the majority of them is not well understood. LncRNAs that are conserved between mice and humans are likely to be enriched in functional sequences. Here, we investigate the presence of different types of ribosome profiling signatures in lncRNAs and how they relate to sequence conservation. We find that lncRNA-conserved regions contain three times more ORFs with translation evidence than non-conserved ones, and identify nine cases that display significant sequence constraints at the amino acid sequence level. The study also reveals that conserved regions in intergenic lncRNAs are significantly enriched in protein–RNA interaction signatures when compared to non-conserved ones; this includes sites in well-characterized lncRNAs, such as Cyrano, Malat1, Neat1 and Meg3, as well as in tens of lncRNAs of unknown function. This work illustrates how the analysis of ribosome profiling data coupled with evolutionary analysis provides new opportunities to explore the lncRNA functional landscape.