bluuebunny/crossref_metadata_2025_split huggingface dataset:
The prevalence of rheumatoid arthritis in Spain
Authors: Silva-Fernández Lucía , Macía-Villa Cristina , Seoane-Mato Daniel , Cortés-Verdú Raúl , Romero-Pérez Antonio , Quevedo-Vila Víctor , Fábregas-Canales Dolores , Antón-Pagés Fred , Añez Gustavo , Brandy Anahy , Martínez-Dubois Cristina , Rubio-Muñoz Paula , Sánchez-Piedra Carlos , Díaz-González Federico , Bustabad-Reyes Sagrario 
Published: December 2020

AbstractRheumatoid arthritis (RA) prevalence is believed to be around 1% worldwide, although it varies considerably among different populations. The aim of EPISER2016 study was to estimate the prevalence of RA in the general adult population in Spain. We designed a population-based cross-sectional study. A national survey was conducted between November 2016 and October 2017 involving a probabilistic sample from the general population aged 20 years or older. Subjects were randomly selected for phone screening using a computer-assisted telephone interviewer system. Positive RA screening results were evaluated by a rheumatologist. Cases fulfilled the 1987 ACR and/or the 2010 ACR/EULAR criteria; previous diagnosis established by a rheumatologist and clearly identified in medical records were also accepted regardless of the criteria used. Prevalence estimates with 95% CI were calculated taking into account the design of the sample (weighting based on age, sex, and geographic origin using as a reference the distribution of the population in Spain). 4916 subjects participated in the study and 39 RA cases were confirmed. RA estimated prevalence was 0.82% (95% CI 0.59–1.15). Mean age of RA cases was 60.48 (14.85) years, they were more frequently women (61.5%), from urban areas (74.4%), non-smokers (43.6%), and with a high body mass index (53.8% with overweight). Extrapolating to the population in Spain (approximately 37 million are ≥ 20 years old), it was estimated that there were between 220,000 and 430,000 people aged 20 years or older with RA. No undiagnosed cases were detected, which could be related to the establishment of early arthritis clinics around the country, increasing the rates of diagnosis during early phases of RA.
The hydraulic resistance paradox in rapid narrow pipe waterflow
Authors: Dvorský Richard , Svoboda Ladislav , Bednář Jiří 
Published: December 2020

AbstractIn this work we present experimental results of cross-sectional speed of water flow in narrow cylindrical metal tubes at high pressure gradients up to 1.1 GPa$$\cdot$$
·
m−1. The measurement draws attention to the paradoxical behaviour of flowing water in internal diameters less than 250 $$\upmu$$
μ
m. At constant pressure gradient, its cross-section speed decreases with decreasing diameter in accordance with the classical hydrodynamic prediction for turbulent flow in rough cylindrical tube. However for very low diameters below 250 $$\upmu$$
μ
m, the cross-section speed rises again and reaches almost the maximum theoretical value of the outflow speed for the appropriate pressure without energy loss caused by contraction or hydraulic friction. Our contribution describes mainly experimental character of the new phenomenon and its motivation is to promptly provide the material for further study to the professional public.
Whole brain proton irradiation in adult Sprague Dawley rats produces dose dependent and non-dependent cognitive, behavioral, and dopaminergic effects
Authors: Williams Michael T. , Sugimoto Chiho , Regan Samantha L. , Pitzer Emily M. , Fritz Adam L. , Mascia Anthony E. , Sertorio Mathieu , Vatner Ralph E. , Perentesis John P. , Vorhees Charles V. 
Published: December 2020

AbstractProton radiotherapy causes less off-target effects than X-rays but is not without effect. To reduce adverse effects of proton radiotherapy, a model of cognitive deficits from conventional proton exposure is needed. We developed a model emphasizing multiple cognitive outcomes. Adult male rats (10/group) received a single dose of 0, 11, 14, 17, or 20 Gy irradiation (the 20 Gy group was not used because 50% died). Rats were tested once/week for 5 weeks post-irradiation for activity, coordination, and startle. Cognitive assessment began 6-weeks post-irradiation with novel object recognition (NOR), egocentric learning, allocentric learning, reference memory, and proximal cue learning. Proton exposure had the largest effect on activity and prepulse inhibition of startle 1-week post-irradiation that dissipated each week. 6-weeks post-irradiation, there were no effects on NOR, however proton exposure impaired egocentric (Cincinnati water maze) and allocentric learning and caused reference memory deficits (Morris water maze), but did not affect proximal cue learning or swimming performance. Proton groups also had reduced striatal levels of the dopamine transporter, tyrosine hydroxylase, and the dopamine receptor D1, effects consistent with egocentric learning deficits. This new model will facilitate investigations of different proton dose rates and drugs to ameliorate the cognitive sequelae of proton radiotherapy.
Gene expression data support the hypothesis that Isoetes rootlets are true roots and not modified leaves
Authors: Hetherington Alexander J. , Emms David M. , Kelly Steven , Dolan Liam 
Published: December 2020

AbstractRhizomorphic lycopsids are the land plant group that includes the first giant trees to grow on Earth and extant species in the genusIsoetes. Two mutually exclusive hypotheses account for the evolution of terminal rooting axes called rootlets among the rhizomorphic lycopsids. One hypothesis states that rootlets are true roots, like roots in other lycopsids. The other states that rootlets are modified leaves. Here we test predictions of each hypothesis by investigating gene expression in the leaves and rootlets ofIsoetes echinospora. We assembled the de novo transcriptome of axenically culturedI. echinospora. Gene expression signatures ofI. echinosporarootlets and leaves were different. Furthermore, gene expression signatures ofI. echinosporarootlets were similar to gene expression signatures of true roots ofSelaginella moellendorffiiandArabidopsis thaliana. RSL genes which positively regulate cell differentiation in roots were either exclusively or preferentially expressed in theI. echinosporarootlets, S.moellendorffiiroots andA. thalianaroots compared to the leaves of each respective species. Taken together, gene expression data from thede-novotranscriptome ofI. echinosporaare consistent with the hypothesis thatIsoetesrootlets are true roots and not modified leaves.
Multidimensional machine learning algorithms to learn liquid velocity inside a cylindrical bubble column reactor
Authors: Babanezhad Meisam , Marjani Azam , Shirazian Saeed 
Published: December 2020

AbstractFor understanding the complex behavior of fluids in a multiphase chemical bubble column reactor, a combination of the computational fluid dynamic (CFD) method and the adaptive network-based fuzzy inference system (ANFIS) method is used to predict bubble flow inside a reactor based on the function of column height. In this study, the Euler–Euler model is employed as a CFD method. In the Eulerian method, continuity and momentum governing equations are mathematically computed for each phase, while the equations are connected together by source terms. After calculating the flow pattern and turbulence flow in the reactor, all data sets are used to prepare a fully artificial method for further prediction. This algorithm contains different learning dimensions such as learning in different directions of reactor or large amount of input parameters and data set representing “big data”. The ANFIS method was evaluated in three steps by using one, two, and three inputs in each one to predict the liquid velocity in the x-direction (Ux). The x, y, and z coordinates of the location of the node of the liquid were considered as the inputs. Different percentages of data and various iterations and membership functions were used for training in the ANFIS method. The ANFIS method showed the best prediction using three inputs. This combination also shows the ability of computer science and computational methods in learning physical and chemical phenomena.
Large-scale resculpting of cortical circuits in children after surgical resection
Authors: Maallo Anne Margarette S. , Granovetter Michael C. , Freud Erez , Kastner Sabine , Pinsk Mark A. , Glen Daniel , Patterson Christina , Behrmann Marlene 
Published: December 2020

AbstractDespite the relative successes in the surgical treatment of pharmacoresistant epilepsy, there is rather little research on the neural (re)organization that potentially subserves behavioral compensation. Here, we examined the post-surgical functional connectivity (FC) in children and adolescents who have undergone unilateral cortical resection and, yet, display remarkably normal behavior. Conventionally, FC has been investigated in terms of the mean correlation of the BOLD time courses extracted from different brain regions. Here, we demonstrated the value of segregating the voxel-wise relationships into mutually exclusive populations that were either positively or negatively correlated. While, relative to controls, the positive correlations were largely normal, negative correlations among networks were increased. Together, our results point to reorganization in the contralesional hemisphere, possibly suggesting competition for cortical territory due to the demand for representation of function. Conceivably, the ubiquitous negative correlations enable the differentiation of function in the reduced cortical volume following a unilateral resection.
Rapid microbial identification and colistin resistance detection via MALDI-TOF MS using a novel on-target extraction of membrane lipids
Authors: Sorensen Matthew , Chandler Courtney E. , Gardner Francesca M. , Ramadan Salma , Khot Prasanna D. , Leung Lisa M. , Farrance Christine E. , Goodlett David R. , Ernst Robert K. , Nilsson Erik 
Published: December 2020

AbstractRapid infection diagnosis is critical to improving patient treatment and outcome. Recent studies have shown microbial lipids to be sensitive and selective biomarkers for identifying bacterial and fungal species and antimicrobial resistance. Practical procedures for microbial lipid biomarker analysis will therefore improve patient outcomes and antimicrobial stewardship. However, current lipid extraction methods require significant hands-on time and are thus not suited for direct adoption as a clinical assay for microbial identification. Here, we have developed a method for lipid extraction directly on the surface of stainless-steel matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) plates, termed fast lipid analysis technique or FLAT, which facilitates the identification of bacterial and fungal species using a sub-60-minute workflow. Additionally, our method detects lipid A modifications in Gram-negative bacteria that are associated with antimicrobial resistance, including to colistin.
Metabolic activation and toxicological evaluation of polychlorinated biphenyls in Drosophila melanogaster
Authors: Idda T. , Bonas C. , Hoffmann J. , Bertram J. , Quinete N. , Schettgen T. , Fietkau K. , Esser A. , Stope M. B. , Leijs M. M. , Baron J. M. , Kraus T. , Voigt A. , Ziegler P. 
Published: December 2020

AbstractDegradation of polychlorinated biphenyls (PCBs) is initiated by cytochrome P450 (CYP) enzymes and includes PCB oxidation to OH-metabolites, which often display a higher toxicity than their parental compounds. In search of an animal model reflecting PCB metabolism and toxicity, we tested Drosophila melanogaster, a well-known model system for genetics and human disease. Feeding Drosophila with lower chlorinated (LC) PCB congeners 28, 52 or 101 resulted in the detection of a human-like pattern of respective OH-metabolites in fly lysates. Feeding flies high PCB 28 concentrations caused lethality. Thus we silenced selected CYPs via RNA interference and analyzed the effect on PCB 28-derived metabolite formation by assaying 3-OH-2′,4,4′-trichlorobiphenyl (3-OHCB 28) and 3′-OH-4′,4,6′-trichlorobiphenyl (3′-OHCB 28) in fly lysates. We identified several drosophila CYPs (dCYPs) whose knockdown reduced PCB 28-derived OH-metabolites and suppressed PCB 28 induced lethality including dCYP1A2. Following in vitro analysis using a liver-like CYP-cocktail, containing human orthologues of dCYP1A2, we confirm human CYP1A2 as a PCB 28 metabolizing enzyme. PCB 28-induced mortality in flies was accompanied by locomotor impairment, a common phenotype of neurodegenerative disorders. Along this line, we show PCB 28-initiated caspase activation in differentiated fly neurons. This suggested the loss of neurons through apoptosis. Our findings in flies are congruent with observation in human exposed to high PCB levels. In plasma samples of PCB exposed humans, levels of the neurofilament light chain increase after LC-PCB exposure, indicating neuronal damage. In summary our findings demonstrate parallels between Drosophila and the human systems with respect to CYP mediated metabolism and PCB mediated neurotoxicity.
Memory guidance of value-based decision making at an abstract level of representation
Authors: Liashenko Anna , Dizaji Aslan S. , Melloni Lucia , Schwiedrzik Caspar M. 
Published: December 2020

AbstractValue-based decisions about alternatives we have never experienced can be guided by associations between current choice options and memories of prior reward. A critical question is how similar memories need to be to the current situation to effectively guide decisions. We address this question in the context of associative learning of faces using a sensory preconditioning paradigm. We find that memories of reward spread along established associations between faces to guide decision making. While memory guidance is specific for associated facial identities, it does not only occur for the specific images that were originally encountered. Instead, memory guidance generalizes across different images of the associated identities. This suggests that memory guidance does not rely on a pictorial format of representation but on a higher, view-invariant level of abstraction. Thus, memory guidance operates on a level of representation that neither over- nor underspecifies associative relationships in the context of obtaining reward.
Metabolomics analysis of plasma and adipose tissue samples from mice orally administered with polydextrose and correlations with cecal microbiota
Authors: Saarinen Markku Tapani , Kärkkäinen Olli , Hanhineva Kati , Tiihonen Kirsti , Hibberd Ashley , Mäkelä Kari Antero , Raza Ghulam Shere , Herzig Karl-Heinz , Anglenius Heli 
Published: December 2020

AbstractPolydextrose (PDX) is a branched glucose polymer, utilized as a soluble dietary fiber. Recently, PDX was found to have hypolipidemic effects and effects on the gut microbiota. To investigate these findings more closely, a non-targeted metabolomics approach, was exploited to determine metabolic alterations in blood and epididymal adipose tissue samples that were collected from C57BL/6 mice fed with a Western diet, with or without oral administration of PDX. Metabolomic analyses revealed significant differences between PDX- and control mice, which could be due to differences in diet or due to altered microbial metabolism in the gut. Some metabolites were found in both plasma and adipose tissue, such as the bile acid derivative deoxycholic acid and the microbiome-derived tryptophan metabolite indoxyl sulfate, both of which increased by PDX. Additionally, PDX increased the levels of glycine betaine and l-carnitine in plasma samples, which correlated negatively with plasma TG and positively correlated with bacterial genera enriched in PDX mice. The results demonstrated that PDX caused differential metabolite patterns in blood and adipose tissues and that one-carbon metabolism, associated with glycine betaine and l-carnitine, and bile acid and tryptophan metabolism are associated with the hypolipidemic effects observed in mice that were given PDX.
Biomarkers of cardiometabolic complications in survivors of childhood acute lymphoblastic leukemia
Authors: Morel Sophia , Léveillé Pauline , Samoilenko Mariia , Franco Anita , England Jade , Malaquin Nicolas , Tu Véronique , Cardin Guillaume B. , Drouin Simon , Rodier Francis , Lippé Sarah , Krajinovic Maja , Laverdière Caroline , Sinnett Daniel , Lefebvre Geneviève , Levy Emile , Marcil Valérie 
Published: December 2020

AbstractSurvivors of childhood acute lymphoblastic leukemia (cALL) are at higher risk of developing cardiometabolic complications. We aimed at exploring the associations between biomarkers of inflammation, oxidative stress, endothelial function, endotoxemia and cardiometabolic risk factors. We conducted a cross-sectional analysis in 246 cALL survivors (mean age, 22.1 ± 6.3 years; mean time since diagnosis, 15.5 ± 5.2 years) and evaluated the associations using a series of logistic regressions. Using structural equation models, we also tested if the relationship between endotoxemia and cardiometabolic complications was mediated by the latent (unobserved) variable inflammation inferred from the observed biomarkers CRP, TNF-α and IL-6. High leptin-adiponectin ratio was associated with obesity [adjusted OR = 15.7; 95% CI (6.2–39.7)], insulin resistance [20.6 (5.2–82.1)] and the metabolic syndrome [11.2 (2.6–48.7)]. Higher levels of plasminogen activator inhibitor-1 and tumor necrosis factor-α were associated with obesity [3.37 (1.6–7.1) and 2.34 (1.3–4.2), respectively] whereas high C-reactive protein levels were associated with insulin resistance [3.3 (1.6–6.8)], dyslipidemia [2.6 (1.4–4.9)] and MetS [6.5 (2.4–17.9)]. Our analyses provided evidence for a directional relationship between lipopolysaccharide binding protein, related to metabolic endotoxemia, inflammation and cardiometabolic outcomes. Identification of biomarkers and biological mechanisms could open new avenues for prevention strategies to minimize the long-term sequelae, improve follow-up and optimize the quality of life of this high-risk population.
A comparison of AAV-vector production methods for gene therapy and preclinical assessment
Authors: Davidsson Marcus , Negrini Matilde , Hauser Swantje , Svanbergsson Alexander , Lockowandt Marcus , Tomasello Giuseppe , Manfredsson Fredric P. , Heuer Andreas 
Published: December 2020

AbstractAdeno Associated Virus (AAV)-mediated gene expression in the brain is widely applied in the preclinical setting to investigate the therapeutic potential of specific molecular targets, characterize various cellular functions, and model central nervous system (CNS) diseases. In therapeutic applications in the clinical setting, gene therapy offers several advantages over traditional pharmacological based therapies, including the ability to directly manipulate disease mechanisms, selectively target disease-afflicted regions, and achieve long-term therapeutic protein expression in the absence of repeated administration of pharmacological agents. Next to the gold-standard iodixanol-based AAV vector production, we recently published a protocol for AAV production based on chloroform-precipitation, which allows for fast in-house production of small quantities of AAV vector without the need for specialized equipment. To validate our recent protocol, we present here a direct side-by-side comparison between vectors produced with either method in a series of in vitro and in vivo assays with a focus on transgene expression, cell loss, and neuroinflammatory responses in the brain. We do not find differences in transduction efficiency nor in any other parameter in our in vivo and in vitro panel of assessment. These results suggest that our novel protocol enables most standardly equipped laboratories to produce small batches of high quality and high titer AAV vectors for their experimental needs.
Rapid reduction of nitroarenes photocatalyzed by an innovative Mn3O4/α-Ag2WO4 nanoparticles
Authors: Mohamed Mohamed Mokhtar , El-Farsy Hassan 
Published: December 2020

AbstractA novel photocatalyst based on the design of P-N heterojunction between hollow spherical Mn3O4 and nanorods shape of α-Ag2WO4 is synthesized using a sonication-deposition–precipitation route. The nanocomposite Mn3O4/α-Ag2WO4(60%) exhibits a great potential towards nitroarenes (including 4-nitrophenol, 4-nitro-aniline and 4-Nitro-acetanilide) reduction under visible light irradiation exceeding that of Mn3O4/α-Ag2WO4(40%) as well as their individual counterparts (3–5%). The Mn3O4/α-Ag2WO4(60%) catalyst exhibited an excellent photo-reduction activity comprised of 0.067 s−1 towards 4-nitrophenol (0.001 M) in only 60 s reaction time using NaBH4 (0.2 M). This was due to the successful formation of the Mn3O4/α-Ag2WO4 composite as validated by XRD, TEM-SAED, XPS, FTIR, UV–Vis diffuse reflectance and PL techniques. Decreasing the Eg value into 2.7 eV, the existence of a new (151) plane in the composite beside enhancement of the composite electrical conductivity (1.66 × 10–7 Ω−1 cm−1) helps the facile nitroarenes adsorption and hydrogenation. Transient photocurrent response and linear sweep voltammetry results prove the facilitation of photogenerated charge carriers separation and transport via improving electron lifetime and lessening recombination rate. The composite photocatalyst produced higher amounts of H2 production, when inserted in a typical reaction medium containing NaBH4, comprised of 470 µ mole/g exceeding those of the counterparts (35 µ mole/g). This photocatalyst is strikingly hydrogenated 4-nitrophenol under mild conditions (25 °C and 0.35 MPa pressure of H2) with magnificent rate constant equal 34.9 × 10−3 min−1 with 100% selectivity towards 4-aminophenol.
Dysgraphia detection through machine learning
Authors: Drotár Peter , Dobeš Marek 
Published: December 2020

AbstractDysgraphia, a disorder affecting the written expression of symbols and words, negatively impacts the academic results of pupils as well as their overall well-being. The use of automated procedures can make dysgraphia testing available to larger populations, thereby facilitating early intervention for those who need it. In this paper, we employed a machine learning approach to identify handwriting deteriorated by dysgraphia. To achieve this goal, we collected a new handwriting dataset consisting of several handwriting tasks and extracted a broad range of features to capture different aspects of handwriting. These were fed to a machine learning algorithm to predict whether handwriting is affected by dysgraphia. We compared several machine learning algorithms and discovered that the best results were achieved by the adaptive boosting (AdaBoost) algorithm. The results show that machine learning can be used to detect dysgraphia with almost 80% accuracy, even when dealing with a heterogeneous set of subjects differing in age, sex and handedness.