bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interleukin-19 alleviates experimental autoimmune encephalomyelitis by attenuating antigen-presenting cell activation
Authors: Horiuchi Hiroshi , Parajuli Bijay , Komiya Hiroyasu , Ogawa Yuki , Jin Shijie , Takahashi Keita , Azuma Yasu-Taka , Tanaka Fumiaki , Suzumura Akio , Takeuchi Hideyuki 
Published: July 2020

AbstractInterleukin-19 (IL-19) acts as an anti-inflammatory cytokine in various inflammatory diseases. Multiple sclerosis (MS) is a major neuroinflammatory disease in the central nervous system, but it remains uncertain how IL-19 contributes to MS pathogenesis. Here, we demonstrate that IL-19 deficiency aggravates experimental autoimmune encephalomyelitis (EAE), a mouse model of MS, by promoting IL-17–producing helper T cell (Th17 cell) infiltration into the central nervous system. In addition, IL-19–deficient splenic macrophages expressed elevated levels of major histocompatibility complex class II, co-stimulatory molecules, and Th17 cell differentiation–associated cytokines such as IL-1β, IL-6, IL-23, TGF-β1, and TNF-α. These observations indicated that IL-19 plays a critical role in suppression of MS pathogenesis by inhibiting macrophage antigen presentation, Th17 cell expansion, and subsequent inflammatory responses. Furthermore, treatment with IL-19 significantly abrogated EAE. Our data suggest that IL-19 could provide significant therapeutic benefits in patients with MS.
Genomic prediction in the wild: A case study in Soay sheep
Authors: Ashraf B , Hunter DC , Bérénos C , Ellis PA , Johnston SE , Pilkington JG , Pemberton JM , Slate J 
Published: July 2020

AbstractGenomic prediction, the technique whereby an individual’s genetic component of their phenotype is estimated from its genome, has revolutionised animal and plant breeding and medical genetics. However, despite being first introduced nearly two decades ago, it has hardly been adopted by the evolutionary genetics community studying wild organisms. Here, genomic prediction is performed on eight traits in a wild population of Soay sheep. The population has been the focus of a >30 year evolutionary ecology study and there is already considerable understanding of the genetic architecture of the focal Mendelian and quantitative traits. We show that the accuracy of genomic prediction is high for all traits, but especially those with loci of large effect segregating. Five different methods are compared, and the two methods that can accommodate zero-effect and large-effect loci in the same model tend to perform best. If the accuracy of genomic prediction is similar in other wild populations, then there is a real opportunity for pedigree-free molecular quantitative genetics research to be enabled in many more wild populations; currently the literature is dominated by studies that have required decades of field data collection to generate sufficiently deep pedigrees. Finally, some of the potential applications of genomic prediction in wild populations are discussed.
Sense the Moment: a highly sensitive antimicrobial activity predictor based on hydrophobic moment
Authors: Porto William F. , Ferreira Karla C. V. , Ribeiro Suzana M. , Franco Octavio L. 
Published: July 2020

AbstractBackgroundComputer-aided identification and design tools are indispensable for developing antimicrobial agents for controlling antibiotic-resistant bacteria. Antimicrobial peptides (AMPs) have aroused intense interest, since they have a broad spectrum of activity, and therefore, several systems for predicting antimicrobial peptides have been developed, using scalar physicochemical properties; however, regardless of the machine learning algorithm, these systems often fail in discriminating AMPs from their shuffled versions, leading to the need for new training methods to overcome this bias. Aiming to solve this bias, here we present “Sense the Moment”, a prediction system capable of discriminating AMPs and shuffled versions.MethodsThe system was trained using 776 entries: 388 from known AMPs and another 388 based on shuffled versions of known AMPs. Each entry contained the geometric average of three hydrophobic moments measured with different scales.ResultsThe model showed good accuracy (>80 %) and excellent sensitivity (>90 %) for AMP prediction, exceeding deep-learning-based methods.ConclusionOur results demonstrate the system’s applicability, aiding in identifying and discarding non-AMPs, since the number of false negatives is lower than false positives. General Significance: The application of this model in virtual screening protocols for identifying and/or creating antimicrobial agents could aid in the identification of potential drugs to control pathogenic microorganisms and in solving the antibiotic resistance crisis.AvailabilityThe system was implemented as a web application, available at <http://portoreports.com/stm/>.
Multiscale label-free volumetric holographic histopathology of thick-tissue slides with subcellular resolution
Authors: Hugonnet Herve , Kim Yeon Wook , Lee Moosung , Shin Seungwoo , Hruban Ralph H. , Hong Seung-Mo , Park YongKeun 
Published: July 2020

ABSTRACTHistopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artefacts and distort tissues. Here, we demonstrate label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple 3D tomograms and for reducing scattering-induced image distortion. We demonstrate demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm × 1.75 mm × 0.2 mm with a spatial resolution of 170 nm × 170 nm × 1200 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was approximately 20 Giga voxels. We have also demonstrated that different tumour types, and a variety of precursor lesions and pathologies can be visualized with the present method.Abstract Figure
Development ofArabidopsis thalianatransformants showing the self-recognition activity ofBrassica rapa
Authors: Yamamoto Masaya , Kitashiba Hiroyasu , Nishio Takeshi 
Published: July 2020

ABSTRACTSelf-incompatibility in the Brassicaceae family is governed by two-linked highly polymorphic genes located at theSlocus,SRKandSCR. Previously, theSRKandSCRgenes ofArabidopsis lyratawere introduced intoArabidopsis thalianatransformants to generate self-incompatible lines. However, it has not been reported that theSRKandSCRgenes ofBrassicaspecies confer self-incompatibility inA. thaliana. In this study, we attempted to construct self-incompatibleA. thalianatransformants expressing the self-recognition activity ofBrassica rapaby introducing theBrSCRgene along with a chimericBrSRKgene (BrSRK chimera, in which the kinase domain ofBrSRKwas replaced with that ofAlSKRb). We found thatBrSRK chimeraandBrSCRofB. rapa S-9andS-46haplotypes, but not those ofS-29,S-44, andS-60haplotypes, conferred self-recognition activity inA. thaliana. We also investigated the importance of amino acid residues involved in the BrSRK9–BrSCR9 interaction usingA. thalianatransformants expressing mutant variants ofBrSRK-9 chimeraandBrSCR-9. The results showed that some of the amino acid residues are essential for self-recognition. The method developed in this study for the construction of self-incompatibleA. thalianatransformants showingB. rapaself-recognition activity will be useful for analysis of self-recognition mechanisms in Brassicaceae.
Tau in the brain interstitial fluid is fragmented and seeding-competent
Authors: Barini Erica , Plotzky Gudrun , Mordashova Yulia , Hoppe Jonas , Rodriguez-Correa Esther , Julier Sonja , LePrieult Florie , Mairhofer Ina , Mezler Mario , Biesinger Sandra , Cik Miroslav , Meinhardt Marcus W , Ercan-Herbst Ebru , Ehrnhoefer Dagmar E. , Striebinger Andreas , Bodie Karen , Klein Corinna , Gasparini Laura , Schlegel Kerstin 
Published: July 2020

AbstractIn Alzheimer disease, Tau pathology is thought to propagate from cell to cell throughout interconnected brain areas. However, the forms of Tau released into the brain interstitial fluid (ISF) in vivo during the development of Tauopathy and their pathological relevance remain unclear. Combining in vivo microdialysis and biochemical analysis, we find that in Tau transgenic mice, human Tau (hTau) present in brain ISF is truncated and comprises at least 10 distinct fragments spanning the entire Tau protein. The fragmentation pattern is similar across different Tau transgenic models, pathological stages and brain areas. ISF hTau concentration decreases during Tauopathy progression, while its phosphorylation increases. ISF from mice with established Tauopathy induces Tau aggregation in HEK293-Tau biosensor cells. Notably, immunodepletion of ISF phosphorylated Tau, but not Tau fragments, significantly reduces its ability to seed Tau aggregation and only a fraction of Tau, separated by ultracentrifugation, is seeding competent. These results indicate that ISF seeding competence is driven by a small subset of Tau, which potentially contribute to the propagation of Tau pathology.HighlightsIn interstitial fluid (ISF) of transgenic mice, Tau comprises >10 distinct fragmentsISF Tau decreases with Tauopathy progression, while its phosphorylation increasesOnly ISF from mice with established Tauopathy is seeding competent in vitroRemoval of phospho-Tau reduces ISF seeding competenceISF seeding competence is driven by less soluble, aggregated and phosphorylated TauGraphical abstract
Rapid Establishment of Tracheal Stenosis in Pigs Using Endotracheal Tube Cuff Overpressure and Electrocautery
Authors: Kim Jin Hyoung , Ahn Jong Joon , Jegal Yangjin , Seo Kwang Won , Ra Seung Won , Kang Byung Ju , Bae Soohyun , Park Soon Eun , Jung Moon Sik , Park Ju Ik , Cha Hee Jeong , Lee Yongjik , Lee Taehoon 
Published: July 2020

ABSTRACTBackgroundCentral airway obstruction can be caused by cancer, tracheal intubation, or tuberculosis, among others. If surgery is contraindicated, bronchoscopic therapy may be performed. Bronchoscopic treatment for airway obstruction is continuously evolving. In particular, attempts to overcome the current shortcomings of airway stents (stent migration, mucostasis, and granulation tissue formation) are currently ongoing. To apply a new airway stent to humans, preclinical studies in an appropriate animal model is needed. Canine and porcine tracheas have been used as animal airway stenosis models. However, existing models take a long time to develop (3–8 weeks) and have a disadvantage that the mechanism of stenosis is different from that in humans.PurposeTo establish a new and fast tracheal stenosis model in pigs using a combination of cuff overpressure intubation and electrocautery.MethodsFourteen pigs were divided into three groups: tracheal cautery (TC) group (n = 3), cuff overpressure intubation (COI) group (n = 3), and COI-TC combination group (n = 8). Cuff overpressure (200/400/500 mmHg) was applied using a 9-mm internal diameter endotracheal tube. Tracheal cautery (40/60 watts) was performed using a rigid bronchoscopic electrocoagulator. After intervention, the pigs were observed for 3 weeks and bronchoscopy was performed every 7 days. When the cross-sectional area decreased by > 50%, it was judged that tracheal stenosis was established.ResultsThe time for tracheal stenosis was 14 days in the TC group and 7 days in the COI-TC combination group. In the COI group, no stenosis occurred. In the COI-TC group, electrocautery (40 watts) immediately after intubation for > 1 hour with a cuff pressure of 200 mmHg or more resulted in sufficient tracheal stenosis within 7 days. Moreover, the degree of tracheal stenosis increased in proportion to the cuff pressure and tracheal intubation time.ConclusionsThe combined use of cuff overpressure and electrocautery helped to establish tracheal stenosis in pigs rapidly. This animal model was technically simple and reproducible, and used a mechanism similar to that in human tracheal stenosis. It is expected to help develop new treatments for airway stenosis
The global impact of the first Coronavirus Disease 2019 (COVID-19) pandemic wave on vascular services
Authors:   The VERN COVER study collaborative, Benson Ruth A , Nandhra Sandip 
Published: July 2020

AbstractBackgroundThe Coronavirus Disease 2019 (COVID-19) pandemic is having an unprecedented impact on healthcare delivery. This international qualitative study captured the global impact on vascular patient care during the first pandemic ‘wave’.MethodsAn online structured survey was used to collect regular unit-level data regarding the modification to a wide range of vascular services and treatment pathways on a global scale.ResultsThe survey commenced on 23rd March 2020 worldwide. Over six weeks, 249 vascular units took part in 53 countries (465 individual responses). Overall, 65% of units stopped carotid surgery for anyone except patients with crescendo symptoms or offered surgery on a case-by-case basis, 25% only intervened for symptomatic aortic aneurysms cancelling all ‘elective’ repairs. For patients with symptomatic peripheral arterial disease 60% of units moved to an endovascular-first strategy. For patients who had previously undergone endovascular aortic aneurysm repair, 31.8% of units stopped all postoperative surveillance. Of those units regularly engaging in multidisciplinary team meetings, 59.5% of units stopped regular meetings and 39.1% had not replaced them. Further, 20% of units did not have formal personal protective equipment (PPE) guidelines in place and 25% reported insufficient PPE availability.ConclusionsThe COVID-19 pandemic has had a major impact on vascular services worldwide. There will be a significant vascular disease burden awaiting screening and intervention after the pandemic.
Triage-driven diagnosis for early detection of esophageal cancer using deep learning
Authors: Gehrung Marcel , Crispin-Ortuzar Mireia , Berman Adam G. , O’Donovan Maria , Fitzgerald Rebecca C. , Markowetz Florian 
Published: July 2020

AbstractDeep learning methods have been shown to achieve excellent performance on diagnostic tasks, but it is still an open challenge how to optimally combine them with expert knowledge and existing clinical decision pathways. This question is particularly important for the early detection of cancer, where high volume workflows might potentially benefit substantially from automated analysis. Here, we present a deep learning framework to analyse samples of the Cytosponge®-TFF3 test, a minimally invasive alternative to endoscopy, for detecting Barrett’s Esophagus, the main precursor of esophageal cancer. We trained and independently validated the framework on data from two clinical trials, analysing a combined total of 4,662 pathology slides from 2,331 patients. Our approach exploits screening patterns of expert gastrointestinal pathologists and established decision pathways to define eight triage classes of varying priority for manual expert review. By substituting manual review with automated review in low-priority classes, we can reduce pathologist workload by up to 66% while matching the diagnostic performance of expert pathologists. These results lay the foundation for tailored, semi-automated decision support systems embedded in clinical workflows.
Fertility Transition in Currently Married Reproductive Age Women in India: 1985-2017
Authors: Chaurasia Aalok Ranjan 
Published: July 2020

AbstractThis paper analyses fertility transition in currently married women in India and states during 1985 through 2017 on the basis of average annual number of live births per currently married woman of reproductive age available through the sample registration system. The analysis reveals that in recent years there has been an increase in the average annual number of live births per currently married woman of reproductive age in India and in its most of the states. The analysis also reveals that there has been an increasing concentration of average annual number of live births per currently married woman of reproductive age in the younger ages of the reproductive period which has implications for population growth as more and more growth in the coming years will be due to the momentum for growth built in the age structure of the population. It is argued that in order to mitigate the impact of the observed transition in the average annual number of live births per currently married woman of reproductive age, fertility regulation efforts in India should be directed towards the ‘practice’ of family planning rather than ‘treatment’ of high fertility.
BaseQTL: a Bayesian method to detect eQTLs from RNA-seq data with or without genotypes
Authors: Vigorito Elena , Lin Wei-Yu , Starr Colin , Kirk Paul DW , White Simon R , Wallace Chris 
Published: July 2020

AbstractAvailable methods to detect molecular quantitative trait loci (QTL) require study individuals to be genotyped. Here, we describe BaseQTL, a Bayesian method that exploits allele-specific expression to map molecular QTL from sequencing reads even when no genotypes are available. When used with genotypes, BaseQTL has lower error rates and increased power compared with existing QTL mapping methods. Running without genotypes limits how many tests can be performed, but due to the proximity of QTL variants to gene bodies, the 2.8% of variants within a 100kB-window that could be tested, contained 26% of QTL variants detectable with genotypes. eQTL effect estimates were invariably consistent between analyses performed with and without genotypes. Often, sequencing data may be generated in absence of genotypes on patients and controls in differential expression studies, and we identified an apparent psoriasis-specific effect forGSTP1in one such dataset, providing new insights into disease-dependent gene regulation.
Gene regulation of the avian malaria parasitePlasmodium relictum, during the different stages within the mosquito vector
Authors: Sekar V. , Rivero A. , Pigeault R. , Gandon S. , Drews A. , Ahren Dag , Hellgren O. 
Published: July 2020

AbstractThe malaria parasitePlasmodium relictumis one of the most widespread species of avian malaria. As is the case in its human counterparts, birdPlasmodiumundergoes a complex life cycle infecting two hosts: the arthropod vector and the vertebrate host. In this study, we examine the transcriptome ofP. relictum(SGS1) during crucial timepoints within its natural vector,Culex pipiens quinquefasciatus. Differential gene-expression analyses identified genes linked to the parasites life-stages at: i) a few minutes after the blood meal is ingested, ii) during peak oocyst production phase, iii) during peak sporozoite phase and iv) during the late-stages of the infection. A large amount of genes coding for functions linked to host-immune invasion and multifunctional genes was active throughout the infection cycle. One gene associated with a conservedPlasmodiummembrane protein with unknown function was upregulated throughout the parasite development in the vector, suggesting an important role in the successful completion of the sporogonic cycle. Transcript annotation further revealed novel genes, which were significantly differentially expressed during the infection in the vector as well as upregulation of reticulocyte-binding proteins, which raises the possibility of the multifunctionality of these RBPs. We establish the existence of highly stage-specific pathways being overexpressed during the infection. This first study of gene-expression of a non-human Plasmodium species in its natural vector provides a comprehensive insight into the molecular mechanisms of the common avian malaria parasiteP. relictumand provides essential information on the evolutionary diversity in gene regulation of the Plasmodium’s vector stages.
Growth of the Radiotrophic FungusCladosporium sphaerospermumaboard the International Space Station and Effects of Ionizing Radiation
Authors: Shunk Graham K. , Gomez Xavier R. , Kern Christoph , Averesch Nils J. H. 
Published: July 2020

AbstractThe greatest hazard for humans on deep-space exploration missions is radiation. To protect astronauts venturing out beyond Earth’s protective magnetosphere, advanced passive radiation protection is highly sought after. In search of innovative radiation-shields, biotechnology appeals with suitability forin-situresource utilization (ISRU), self-regeneration, and adaptability.Certain fungi thrive in high-radiation environments on Earth, such as the contamination radius of the Chernobyl Nuclear Power Plant. Analogous to photosynthesis, these organisms appear to perform radiosynthesis, utilizing ionizing radiation to generate chemical energy. It has been postulated that the absorption of radiation is attributable to the pigment melanin. It is further hypothesized that this phenomenon translates to radiation-shielding properties.Here, growth ofCladosporium sphaerospermumand its capability to attenuate ionizing radiation, was studied aboard the International Space Station (ISS) over a period of 26 days, as an analog to habitation on the surface of Mars. At full maturity, radiation beneath a ≈ 1.7 mm thick lawn of the dematiaceous radiotrophic fungus was approx. 0.84% lower as compared to the negative-control. In addition, a growth advantage in Space of ∼ 21% was observed, substantiating the thesis that the fungus’ radiotropism is extendable to Space radiation.
Near-infrared spectroscopy outperforms genomics for predicting sugarcane feedstock quality traits
Authors: Vital Gonçalves Mateus Teles , Morota Gota , de Almeida Costa Paulo Mafra , Pereira Vidigal Pedro Marcus , Pereira Barbosa Marcio Henrique , Peternelli Luiz Alexandre 
Published: July 2020

AbstractThe main objectives of this study were to evaluate the prediction performance of genomic and near-infrared spectroscopy (NIR) data and whether the integration of genomic and NIR predictor variables can increase the prediction accuracy of two feedstock quality traits (fiber and sucrose content) in a sugarcane population (Saccharumspp.). The following three modeling strategies were compared: M1 (genome-based prediction), M2 (NIR-based prediction), and M3 (integration of genomics s and NIR wavenumbers). Data were collected from a commercial population comprised of three hundred and eighty-five individuals, genotyped for single nucleotide polymorphisms (SNPs) and screened using NIR spectroscopy. We compared partial least squares (PLS) and BayesB regression methods to estimate marker and wavenumber effects. In order to assess model performance, we employed random sub-sampling cross-validation to calculate the mean Pearson correlation coefficient between observed and predicted genotypic values. Our results showed that models fitted using BayesB were most predictive than PLS models. We found that NIR (M2) provided the highest prediction accuracy, whereas genomics (M1) presented the lowest predictive ability, regardless of the measured traits and regression methods used. The integration of predictors derived from NIR spectroscopy and genomics into a single model (M3) did not significantly improve the prediction accuracy for the two traits evaluated. These findings suggest that NIR-based prediction can be an effective strategy for predicting the genotypic value of sugarcane clones.