bluuebunny/crossref_metadata_2025_split huggingface dataset:
A brief report: de novo copy number variants in children with attention deficit hyperactivity disorder
Authors: Martin Joanna , Hosking Grace , Wadon Megan , Agha Sharifah Shameem , Langley Kate , Rees Elliott , Owen Michael J. , O’Donovan Michael , Kirov George , Thapar Anita 
Published: May 2020

AbstractRecent case–control genetic studies of attention deficit hyperactivity disorder (ADHD) have implicated common and rare genetic risk alleles, highlighting the polygenic and complex aetiology of this neurodevelopmental disorder. Studies of other neurodevelopmental disorders, such as autism spectrum disorder (ASD), Tourette disorder, developmental delay/intellectual disability and schizophrenia indicate that identification of specific risk alleles and additional insights into disorder biology can be gained by studying non-inherited de novo variation. In this study, we aimed to identify large de novo copy number variants (CNVs) in children with ADHD. Children with a confirmed diagnosis of ADHD and their parents were genotyped and included in this sample. We used PennCNV to call large (>200 kb) CNVs and identified those calls that were present in the proband and absent in both biological parents. In 305 parent–offspring trios, we detected 14 de novo CNVs in 13 probands, giving a mutation rate of 4.6% and a per individual rate of 4.3%. This rate is higher than published reports in controls and similar to those observed for ASD, schizophrenia and Tourette disorder. We also identified de novo mutations at four genomic loci (15q13.1–13.2 duplication, 16p13.11 duplication, 16p12.2 deletion and 22q11.21 duplication) that have previously been implicated in other neurodevelopmental disorders, two of which (16p13.11 and 22q11.21) have also been implicated in case–control ADHD studies. Our study complements ADHD case–control genomic analyses and demonstrates the need for larger parent–offspring trio genetic studies to gain further insights into the complex aetiology of ADHD.
Association of early-onset Alzheimer’s disease with germline-generated high affinity self-antigen load
Authors: Huang Poyin , Yang Yuan-Han , Chang Ya-Hsuan , Chang Shu-Ling , Chou Mei-Chuan , Lai Chiou-Lian , Liu Ching-Kuan , Chen Hsuan-Yu 
Published: May 2020

AbstractSelf-antigen presentation outside the central nervous system has crucial role regarding self-proteins tolerance and autoimmunity, leading to neuroinflammation. Self-antigen with strong-binding affinity is considered to be pathogenic. We aim to investigate whether strong-binding affinity self-antigen load is associated with early/late-onset Alzheimer’s disease (AD). A total of 54 AD samples (22 early-onset, 32 late-onset) underwent next-generation sequencing (NGS) for whole-exome sequencing. Genotypes of HLA class I genes and germline mutations were obtained for estimation of the binding affinity and number of self-antigens. For each patient, self-antigen load was estimated by adding up the number of self-antigens with strong-binding affinity. Self-antigen load of early-onset AD was significantly higher than late-onset AD (mean ± SD: 6115 ± 2430 vs 4373 ± 2492;p = 0.011). An appropriate cutoff value 2503 for dichotomizing self-antigen load was obtained by receiver operating characteristic (ROC) curve analysis. Patients were then dichotomized into high or low self-antigen load groups in the binary multivariate logistic regression analysis. Adjusted odds ratio of the high self-antigen load (>2503) was 14.22 (95% CI, 1.22–165.70;p = 0.034) after controlling other covariates including gender, education, ApoE status, and baseline CDR score. This is the first study using NGS to investigate germline mutations generated self-antigen load in AD. As strong-binding affinity self-antigen is considered to be pathogenic in neuroinflammation, our finding indicated that self-antigen load did have a role in the pathogenesis of AD owing to its association with neuroinflammation. This finding may also contribute to further research regarding disease mechanism and development of novel biomarkers or treatment.
Characteristics of gray matter alterations in never-treated and treated chronic schizophrenia patients
Authors: Liu Nian , Xiao Yuan , Zhang Wenjing , Tang Biqiu , Zeng Jiaxin , Hu Na , Chandan Shah , Gong Qiyong , Lui Su 
Published: May 2020

AbstractThough gray matter deficits have been consistently revealed in chronic treated schizophrenia, it is still not clear whether there are different brain alterations between chronic never treated and treated patients. To explore the different patterns of gray matter alterations among chronic never treated patients and those treated with monotherapy, we recruited 35 never-treated chronic schizophrenia patients with illness durations ranging from 5 to 48 years, 20 illness duration-matched risperidone monotherapy and 20 clozapine monotherapy patients, and 55 healthy controls. GM (surface area, cortical thickness, and cortical volume) measures were extracted and compared using ANCOVA across the four groups followed by post hoc tests. Relative to controls, both treated and never-treated chronic schizophrenia patients showed reduced GM mainly involving the bilateral medial and rostral middle frontal, left banks superior temporal sulcus, left fusiform, and left pericalcarine cortex and increased in the left cuneus. Compared with the untreated patient group, the two treated groups showed reductions mainly in the bilateral prefrontal, temporal, and left inferior parietal lobules. The clozapine monotherapy patients demonstrated more severe decreases in the bilateral prefrontal cortex and left cuneus and less severe decreases in the left ventral temporal lobe than risperidone monotherapy patients. These findings provide new insights into the long-term effects of antipsychotic treatment on gray matter alterations in schizophrenia patients. Furthermore, the characteristic findings of reductions in the inferior parietal lobule might be specific for long-term antipsychotic treatment, which could be a possible target for medication development in the future.
Fermionic neural-network states for ab-initio electronic structure
Authors: Choo Kenny , Mezzacapo Antonio , Carleo Giuseppe 
Published: May 2020

AbstractNeural-network quantum states have been successfully used to study a variety of lattice and continuous-space problems. Despite a great deal of general methodological developments, representing fermionic matter is however still early research activity. Here we present an extension of neural-network quantum states to model interacting fermionic problems. Borrowing techniques from quantum simulation, we directly map fermionic degrees of freedom to spin ones, and then use neural-network quantum states to perform electronic structure calculations. For several diatomic molecules in a minimal basis set, we benchmark our approach against widely used coupled cluster methods, as well as many-body variational states. On some test molecules, we systematically improve upon coupled cluster methods and Jastrow wave functions, reaching chemical accuracy or better. Finally, we discuss routes for future developments and improvements of the methods presented.
Dissociable neural correlates of uncertainty underlie different exploration strategies
Authors: Tomov Momchil S. , Truong Van Q. , Hundia Rohan A. , Gershman Samuel J. 
Published: May 2020

AbstractMost real-world decisions involve a delicate balance between exploring unfamiliar alternatives and committing to the best known option. Previous work has shown that humans rely on different forms of uncertainty to negotiate this "explore-exploit” trade-off, yet the neural basis of the underlying computations remains unclear. Using fMRI (n = 31), we find that relative uncertainty is represented in right rostrolateral prefrontal cortex and drives directed exploration, while total uncertainty is represented in right dorsolateral prefrontal cortex and drives random exploration. The decision value signal combining relative and total uncertainty to compute choice is reflected in motor cortex activity. The variance of this signal scales with total uncertainty, consistent with a sampling mechanism for random exploration. Overall, these results are consistent with a hybrid computational architecture in which different uncertainty computations are performed separately and then combined by downstream decision circuits to compute choice.
Microplastics affect sedimentary microbial communities and nitrogen cycling
Authors: Seeley Meredith E. , Song Bongkeun , Passie Renia , Hale Robert C. 
Published: May 2020

AbstractMicroplastics are ubiquitous in estuarine, coastal, and deep sea sediments. The impacts of microplastics on sedimentary microbial ecosystems and biogeochemical carbon and nitrogen cycles, however, have not been well reported. To evaluate if microplastics influence the composition and function of sedimentary microbial communities, we conducted a microcosm experiment using salt marsh sediment amended with polyethylene (PE), polyvinyl chloride (PVC), polyurethane foam (PUF) or polylactic acid (PLA) microplastics. We report that the presence of microplastics alters sediment microbial community composition and nitrogen cycling processes. Compared to control sediments without microplastic, PUF- and PLA-amended sediments promote nitrification and denitrification, while PVC amendment inhibits both processes. These results indicate that nitrogen cycling processes in sediments can be significantly affected by different microplastics, which may serve as organic carbon substrates for microbial communities. Considering this evidence and increasing microplastic pollution, the impact of plastics on global ecosystems and biogeochemical cycling merits critical investigation.
Context-dependent regulation of endothelial cell metabolism: differential effects of the PPARβ/δ agonist GW0742 and VEGF-A
Authors: Faulkner Ashton , Lynam Eleanor , Purcell Robert , Jones Coleen , Lopez Colleen , Board Mary , Wagner Kay-Dietrich , Wagner Nicole , Carr Carolyn , Wheeler-Jones Caroline 
Published: May 2020

AbstractPeroxisome proliferator activated receptor β/δ (PPARβ/δ) has pro-angiogenic functions, but whether PPARβ/δ modulates endothelial cell metabolism to support the dynamic phenotype remains to be established. This study characterised the metabolic response of HUVEC to the PPARβ/δ agonist, GW0742, and compared these effects with those induced by VEGF-A. In HUVEC monolayers, flux analysis revealed that VEGF-A promoted glycolysis at the expense of fatty acid oxidation (FAO), whereas GW0742 reduced both glycolysis and FAO. Only VEGF-A stimulated HUVEC migration and proliferation whereas both GW0742 and VEGF-A promoted tubulogenesis. Studies using inhibitors of PPARβ/δ or sirtuin-1 showed that the tubulogenic effect of GW0742, but not VEGF-A, was PPARβ/δ- and sirtuin-1-dependent. HUVEC were reliant on glycolysis and FAO, and inhibition of either pathway disrupted cell growth and proliferation. VEGF-A was a potent inducer of glycolysis in tubulogenic HUVEC, while FAO was maintained. In contrast, GW0742-induced tubulogenesis was associated with enhanced FAO and a modest increase in glycolysis. These novel data reveal a context-dependent regulation of endothelial metabolism by GW0742, where metabolic activity is reduced in monolayers but enhanced during tubulogenesis. These findings expand our understanding of PPARβ/δ in the endothelium and support the targeting of PPARβ/δ in regulating EC behaviour and boosting tissue maintenance and repair.
Arid1b haploinsufficiency in parvalbumin- or somatostatin-expressing interneurons leads to distinct ASD-like and ID-like behavior
Authors: Smith Amanda L. , Jung Eui-Man , Jeon Byeong Tak , Kim Woo-Yang 
Published: May 2020

AbstractInhibitory interneurons are essential for proper brain development and function. Dysfunction of interneurons is implicated in several neurodevelopmental disorders, including autism spectrum disorder (ASD) and intellectual disability (ID). We have previously shown that Arid1b haploinsufficiency interferes with interneuron development and leads to social, cognitive, and emotional impairments consistent with ASD and ID. It is unclear, however, whether interneurons play a major role for the behavioral deficits in Arid1b haploinsufficiency. Furthermore, it is critical to determine which interneuron subtypes contribute to distinct behavioral phenotypes. In the present study, we generated Arid1b haploinsufficient mice in which a copy of the Arid1b gene is deleted in either parvalbumin (PV) or somatostatin (SST) interneurons, and examined their ASD- and ID-like behaviors. We found that Arid1b haploinsufficiency in PV or SST interneurons resulted in distinct features that do not overlap with one another. Arid1b haploinsufficiency in PV neurons contributed to social and emotional impairments, while the gene deletion in the SST population caused stereotypies as well as learning and memory dysfunction. These findings demonstrate a critical role of interneurons in Arid1b haploinsufficient pathology and suggest that PV and SST interneurons may have distinct roles in modulating neurological phenotypes in Arid1b haploinsufficiency-induced ASD and ID.
Platform independent protein-based cell-of-origin subtyping of diffuse large B-cell lymphoma in formalin-fixed paraffin-embedded tissue
Authors: Reinders Jörg , Altenbuchinger Michael , Limm Katharina , Schwarzfischer Philipp , Scheidt Tamara , Strasser Lisa , Richter Julia , Szczepanowski Monika , Huber Christian G. , Klapper Wolfram , Spang Rainer , Oefner Peter J. 
Published: May 2020

AbstractDiffuse large B-cell lymphoma (DLBCL) is commonly classified by gene expression profiling according to its cell of origin (COO) into activated B-cell (ABC)-like and germinal center B-cell (GCB)-like subgroups. Here we report the application of label-free nano-liquid chromatography - Sequential Window Acquisition of all THeoretical fragment-ion spectra – mass spectrometry (nanoLC-SWATH-MS) to the COO classification of DLBCL in formalin-fixed paraffin-embedded (FFPE) tissue. To generate a protein signature capable of predicting Affymetrix-based GCB scores, the summed log2-transformed fragment ion intensities of 780 proteins quantified in a training set of 42 DLBCL cases were used as independent variables in a penalized zero-sum elastic net regression model with variable selection. The eight-protein signature obtained showed an excellent correlation (r = 0.873) between predicted and true GCB scores and yielded only 9 (21.4%) minor discrepancies between the three classifications: ABC, GCB, and unclassified. The robustness of the model was validated successfully in two independent cohorts of 42 and 31 DLBCL cases, the latter cohort comprising only patients aged >75 years, with Pearson correlation coefficients of 0.846 and 0.815, respectively, between predicted and NanoString nCounter based GCB scores. We further show that the 8-protein signature is directly transferable to both a triple quadrupole and a Q Exactive quadrupole-Orbitrap mass spectrometer, thus obviating the need for proprietary instrumentation and reagents. This method may therefore be used for robust and competitive classification of DLBCLs on the protein level.
Identifying task-relevant spectral signatures of perceptual categorization in the human cortex
Authors: Kuzovkin Ilya , Vidal Juan R. , Perrone-Bertolotti Marcela , Kahane Philippe , Rheims Sylvain , Aru Jaan , Lachaux Jean-Philippe , Vicente Raul 
Published: May 2020

AbstractHuman brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks’ selectivity for categorical information processing is still unknown. In this work we train Random Forest classification models to decode eight perceptual categories from broad spectrum of human intracranial signals (4–150 Hz, 100 subjects) obtained during a visual perception task. We then analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding and gain the insights into which parts of the recorded activity are actually characteristic of the visual categorization process in the human brain. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4–50 Hz) and high (50–150 Hz) frequency bands. By focusing on task-relevant neural activity and separating it into dissociated anatomical and spectrotemporal groups we uncover spectral signatures that characterize neural mechanisms of visual category perception in human brain that have not yet been reported in the literature.
Effects of synchronised engine sound and vibration presentation on visually induced motion sickness
Authors: Sawada Yuki , Itaguchi Yoshihiro , Hayashi Masami , Aigo Kosuke , Miyagi Takuya , Miki Masayuki , Kimura Tetsuya , Miyazaki Makoto 
Published: May 2020

AbstractDriving simulator usage is often accompanied by motion sickness, and techniques for its prevention are not yet established. To reduce visually induced motion sickness (VIMS), we investigated the effects of synchronised presentation of engine sounds and motorcycle vibration on VIMS. A total of 80 participants experienced a driving scene with a head-mounted display for 5 minutes with or without synchronised presentation of engine sound and vibration. The results showed that VIMS scores, as measured by the Fast Motion Sickness scale, were significantly lower in participants who experienced the driving scene with sounds and vibration than in those who experienced the scene with sounds only, vibration only, or neither. Multiple regression analyses revealed that susceptibility to VIMS consistently explained the severity of VIMS to some extent but not with perceived realism of the virtual reality (VR) scene, sex, and experiences about VR devices and vehicles. This study demonstrated that simultaneous presentation of engine sounds and vibration, which were synchronous to each other and tightly coupled with the visual flow speed, effectively reduces VIMS while experiencing motorcycling simulators. The findings not only improve practical knowledge for reducing VIMS in driving simulators but also provide evidence for understanding the mechanisms of VIMS.
Anomalous Decay of Quantum Resistance Oscillations of 2D Helical Electrons in Magnetic Field
Authors: Abedi S. , Vitkalov S. A. , Mikhailov N. N. , Kvon Z. D. 
Published: May 2020

AbstractShubnikov de Haas resistance oscillations of highly mobile two dimensional helical electrons propagating on a conducting surface of strained HgTe 3D topological insulator are studied in magnetic fields B tilted by angle θ from the normal to the conducting layer. Strong decrease of oscillation amplitude A is observed with the tilt: $${\boldsymbol{A}}\sim {\boldsymbol{e}}{\boldsymbol{x}}{\boldsymbol{p}}(\,-\,{\boldsymbol{\xi }}/{\boldsymbol{c}}{\boldsymbol{o}}{\boldsymbol{s}}({\boldsymbol{\theta }}))$$A∼exp(−ξ/cos(θ)), where ξ is a constant. Evolution of the oscillations with temperature T shows that the parameter $${\boldsymbol{\xi }}$$ξ contains two terms: $${\boldsymbol{\xi }}={{\boldsymbol{\xi }}}_{1}+{{\boldsymbol{\xi }}}_{2}{\boldsymbol{T}}$$ξ=ξ1+ξ2T. The temperature independent term, $${{\boldsymbol{\xi }}}_{{\bf{1}}}$$ξ1, signals possible reduction of electron mean free path $${l}_{q}$$lq and/or enhancement of in-homogeneous broadening of the oscillations in magnetic field B. The temperature dependent term, $${{\boldsymbol{\xi }}}_{{\bf{2}}}{\boldsymbol{T}}$$ξ2T, indicates increase of the reciprocal velocity of 2D helical electrons: $$\delta ({v}_{F}^{-1})\sim B$$δ(vF−1)∼B suggesting modification of the electron spectrum in magnetic fields. Results are found in good agreement with proposed phenomenological model.
Methotrexate elicits pro-respiratory and anti-growth effects by promoting AMPK signaling
Authors: Papadopoli David J. , Ma Eric H. , Roy Dominic , Russo Mariana , Bridon Gaëlle , Avizonis Daina , Jones Russell G. , St-Pierre Julie 
Published: May 2020

AbstractOne-carbon metabolism fuels the high demand of cancer cells for nucleotides and other building blocks needed for increased proliferation. Although inhibitors of this pathway are widely used to treat many cancers, their global impact on anabolic and catabolic processes remains unclear. Using a combination of real-time bioenergetics assays and metabolomics approaches, we investigated the global effects of methotrexate on cellular metabolism. We show that methotrexate treatment increases the intracellular concentration of the metabolite AICAR, resulting in AMPK activation. Methotrexate-induced AMPK activation leads to decreased one-carbon metabolism gene expression and cellular proliferation as well as increased global bioenergetic capacity. The anti-proliferative and pro-respiratory effects of methotrexate are AMPK-dependent, as cells with reduced AMPK activity are less affected by methotrexate treatment. Conversely, the combination of methotrexate with the AMPK activator, phenformin, potentiates its anti-proliferative activity in cancer cells. These data highlight a reciprocal effect of methotrexate on anabolic and catabolic processes and implicate AMPK activation as a metabolic determinant of methotrexate response.
Interaction Between Apolipoprotein M Gene Single-Nucleotide Polymorphisms and Obesity and its Effect on Type 2 Diabetes Mellitus Susceptibility
Authors: Liu Dan , Pan Jian-Min , Pei Xiang , Li Jun-Sen 
Published: May 2020

AbstractThis study investigated the correlation of four single nucleotide polymorphisms (SNPs) in Apolipoprotein M (ApoM) with the risk of type 2 diabetes mellitus (T2DM) and effects of the interactions of this gene and obesity. The effects of SNP and obesity interaction on T2DM was examined by generalized multifactor dimensionality reduction (GMDR) combined with the logistic regression model. T2DM patient-control haplotype was analyzed in silico using the haplotype analysis algorithm SHEsis. The rs805296-C allele or 724-del allele indicted high risk of T2DM. The incidence of T2DM in individuals with rs805296-C allele polymorphism (TC + CC) was higher than those without (TT), adjusted OR (95%CI) = 1.29 (1.10–1.66) (p < 0.001). Moreover, the individuals with 724-delallele have a higher risk of T2DM compared to those with 724-ins variants, adjusted OR (95%CI) = 1.66 (1.40–2.06), p < 0.001. GMDR analysis suggested that the interaction model composed of the two factors, rs805296 and obesity, was the best model with statistical significance (P value from sign test [Psign]=0.0107). The T2DM risk in obese individuals having TC or CC genotype was higher than non-obese individuals with TT genotype (OR = 2.38, 95% CI = 1.58–3.53). Haplotype analysis suggests that rs805297-C and rs9404941-C alleles haplotype indicate high risk of T2DM, OR (95%CI) = 1.62 (1.29–2.16), p < 0.001. Our results suggested that rs805296 and 724-del minor allele of ApoM gene, interaction of rs805296 and obesity, rs805297-C and rs9404941-C alleles haplotype were indicators of high T2DM risk.