bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cusp-artifacts in high order Superresolution Optical Fluctuation Imaging
Authors: Yi Xiyu , Weiss Shimon 
Published: February 2019

AbstractSuperresolution Optical Fluctuation Imaging (SOFI) offers a simple and affordable alternative to the more sophisticated (and expensive) super-resolution imaging techniques such as STED, PALM, STORM, structured illumination, and other derivative methods. In SOFI, the calculation of high order cumulants provides higher resolution but drastically expands the dynamic range of the resulting image. In this study, we have identified another type of artifact for high order SOFI cumulants, dubbed as ‘cusp artifacts.’ A series of realistic simulations are performed to study the cusp artifacts under the influences of various factors, including the blinking statistics, the spatial distribution of photophysical properties of the sample, the total number of frames processed per dataset, photobleaching, and noise. Experiments, simulations, and theory all show that high order cumulants and odd-order moments could suffer from cusp artifacts. These cusp artifacts also degrade the fidelity of bSOFI that has been proposed to solve the dynamic range expansion of image pixel intensities. Alternatively, cusp-artifacts could be altogether eliminated by utilizing even-order moments constructed directly or from cumulants for image reconstruction. Together with dynamic range compression, these approaches yield improved SOFI images. Our study provides new insight into the nature of high order SOFI images, outlines guidelines for developing and screening SOFI-optimized fluorescence probes, and suggests improved strategies for SOFI data acquisition.
Hippocampal Activity Dynamics During Contextual Reward Association in Virtual Reality Place Conditioning
Authors: Williams Sidney B. , Arriaga Moises , Post William W. , Korgaonkar Akshata A. , Morón Jose A. , Han Edward B. 
Published: February 2019

ABSTRACTExposure to environmental contexts associated with drug use can induce cravings that promote continued use and/or relapse. Opioid abuse is marked by high relapse rates, suggesting that contextual memories formed during opioid use may be particularly strong. While it is known that reward-seeking behavior is controlled by the mesolimbic reward circuit, little is understood about how contextual memories are altered by drug use. The dorsal hippocampus (dHPC) is necessary for multiple types of contextual learning and the place-specific activity of CA1 place cells map out space in a given environment. Here we examined the neuronal representation of context as animals developed morphine-paired environmental associations using a conditioned place preference (CPP) paradigm. To investigate changes in the hippocampal encoding before, during, and after drug-pairing, we developed a virtual reality (VR) morphine CPP (Mor-CPP) paradigm and used in vivo two-photon calcium imaging to record the activity of CA1 pyramidal neurons. We found increased activity in rewarded contexts following real-time operant conditioning with water rewards, but not after Mor-CPP training, suggesting different neural encoding mechanisms for natural reinforcers and morphine.
In Silico Genetics: Identification of pathogenic nsSNPs in human STAT3 gene associated with Job’s syndrome
Authors: Mustafa Mujahed I. , Abdelmoneim Abdelrahman H. , Elfadol Nafisa M. , Mahmoud Thwayba A. , Hassan Mohamed A. 
Published: February 2019

AbstractBackgroundAutosomal dominant hyper-IgE syndrome (AD-HIES) or Job’s syndrome is a rare immunodeficiesncy disease that classically presents in early childhood, characterized by eczematoid dermatitis, characteristic facies, pneumatoceles, hyperextensibility of joints, multiple bone fractures, scoliosis, atopic dermatitis and elevated levels of serum IgE (>2000 IU/ml). The term Autosomal dominant hyper-IgE syndrome has primarily been associated with mutations in STAT3 gene, Located in human chromosome 17q21.MethodsThe human STAT3 gene was investigated in dbSNP/NCBI, 962 SNPs were Homo sapiens; of which 255 were missense SNPs. This selected for in silico analysis by multiple in silico tools to investigate the effect of SNPs on STAT3 protein’s structure and function.ResultEleven novel mutations out of 255 nsSNPs that are found to be deleterious effect on the STAT3 structure and function.ConclusionA total of eleven novel nsSNPs were predicted to be responsible for the structural and functional modifications of STAT3 protein. The newly recognized genetic cause of the hyper-IgE syndrome affects complex, compartmentalized somatic and immune regulation. This study will opens new doors to facilitate the development of novel diagnostic markers for associated diseases.
Optimal use of statistical methods to validate reference gene stability in longitudinal studies
Authors: Sundaram Venkat Krishnan , Sampathkumar Nirmal Kumar , Massaad Charbel , Grenier Julien 
Published: February 2019

AbstractMultiple statistical approaches have been proposed to validate reference genes in qPCR assays. However, conflicting results from these statistical methods pose a major hurdle in the choice of the best reference genes. Indeed, as their respective approaches to calculating reference gene stability is different, their suitability has to be tested for a given experimental setting. In this study, the stability of 10 candidate reference genes (Actb, Gapdh, Tbp, Sdha, Pgk1, Ppia, Rpl13a, Hsp60, Mrpl10, Rps26) was assessed using four common statistical approaches (GeNorm, NormFinder, Coefficient of Variation analysis and Pairwise ΔCt method) in a longitudinal setting. We used the development of the cerebellum and the spinal cord of mice as a model to assess the suitability of these statistical methods for reference gene validation. GeNorm and the Pairwise ΔCt were found to be ill suited due to a fundamental assumption in their stability calculations. Whereas, NormFinder and Coefficient of Variation analysis fare better provided they are used complementarily. We therefore devised a workflow combining these two methods for validating reference genes in developmental studies. This workflow proves to be more robust than any of the methods used individually.
Screening for genes that accelerate the epigenetic ageing clock in humans reveals a role for the H3K36 methyltransferase NSD1
Authors: Martin-Herranz Daniel E. , Aref-Eshghi Erfan , Bonder Marc Jan , Stubbs Thomas M. , Stegle Oliver , Sadikovic Bekim , Reik Wolf , Thornton Janet M. 
Published: February 2019

ABSTRACTBackgroundEpigenetic clocks are mathematical models that predict the biological age of an individual using DNA methylation data, and which have emerged in the last few years as the most accurate biomarkers of the ageing process. However, little is known about the molecular mechanisms that control the rate of such clocks. Here, we have examined the human epigenetic clock in patients with a variety of developmental disorders, harbouring mutations in proteins of the epigenetic machinery.ResultsUsing the Horvath epigenetic clock, we performed an unbiased screen for epigenetic age acceleration (EAA) in the blood of these patients. We demonstrate that loss-of-function mutations in the H3K36 histone methyltransferase NSD1, which cause Sotos syndrome, substantially accelerate epigenetic ageing. Furthermore, we show that the normal ageing process and Sotos syndrome share methylation changes and the genomic context in which they occur. Finally, we found that the Horvath clock CpG sites are characterised by a higher Shannon methylation entropy when compared with the rest of the genome, which is dramatically decreased in Sotos syndrome patients.ConclusionsThese results suggest that the H3K36 methylation machinery is a key component of theepigenetic maintenance systemin humans, which controls the rate of epigenetic ageing, and this role seems to be conserved in model organisms. Our observations provide novel insights into the mechanisms behind the epigenetic ageing clock and we expect will shed light on the different processes that erode the human epigenetic landscape during ageing.
Probabilistic associative learning suffices for learning the temporal structure of multiple sequences
Authors: Martinez Ramon H. , Lansner Anders , Herman Pawel 
Published: February 2019

AbstractMany brain phenomena both at the cognitive and behavior level exhibit remarkable sequential characteristics. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-scale, in this work we attempt to characterize to what degree some of this properties can be explained as a consequence of simple associative learning. To this end, we employ a parsimonious firing-rate attractor network equipped with the Hebbian-like Bayesian Confidence Propagating Neural Network (BCPNN) learning rule relying on synaptic traces with asymmetric temporal characteristics. The proposed network model is able to encode and reproduce temporal aspects of the input, and offers internal control of the recall dynamics by gain modulation. We provide an analytical characterisation of the relationship between the structure of the weight matrix, the dynamical network parameters and the temporal aspects of sequence recall. We also present a computational study of the performance of the system under the effects of noise for an extensive region of the parameter space. Finally, we show how the inclusion of modularity in our network structure facilitates the learning and recall of multiple overlapping sequences even in a noisy regime.
THINGS: A database of 1,854 object concepts and more than 26,000 naturalistic object images
Authors: Hebart Martin N. , Dickter Adam H. , Kidder Alexis , Kwok Wan Y. , Corriveau Anna , Van Wicklin Caitlin , Baker Chris I. 
Published: February 2019

AbstractIn recent years, the use of a large number of object concepts and naturalistic object images has been growing enormously in cognitive neuroscience research. Classical databases of object concepts are based mostly on a manually-curated set of concepts. Further, databases of naturalistic object images typically consist of single images of objects cropped from their background, or a large number of uncontrolled naturalistic images of varying quality, requiring elaborate manual image curation. Here we provide a set of 1,854 diverse object concepts sampled systematically from concrete picturable and nameable nouns in the American English language. Using these object concepts, we conducted a large-scale web image search to compile a database of 26,107 high-quality naturalistic images of those objects, with 12 or more object images per concept and all images cropped to square size. Using crowdsourcing, we provide higher-level category membership for the 27 most common categories and validate them by relating them to representations in a semantic embedding derived from large text corpora. Finally, by feeding images through a deep convolutional neural network, we demonstrate that they exhibit high selectivity for different object concepts, while at the same time preserving variability of different object images within each concept. Together, the THINGS database provides a rich resource of object concepts and object images and offers a tool for both systematic and large-scale naturalistic research in the fields of psychology, neuroscience, and computer science.
Adapting in larger numbers can increase the vulnerability ofEscherichia colipopulations to environmental changes
Authors: Chavhan Yashraj , Karve Shraddha , Dey Sutirth 
Published: February 2019

AbstractLarger populations generally adapt faster to their existing environment. However, it is unknown if the population size experienced during evolution influences the ability to face sudden environmental changes. To investigate this issue, we subjected replicateEscherichia colipopulations of different sizes to experimental evolution in an environment containing a cocktail of three antibiotics. In this environment, the ability to actively efflux molecules outside the cell is expected to be a major fitness-affecting trait. We found that all the populations eventually reached similar fitness in the antibiotic cocktail despite adapting at different speeds, with the larger populations adapting faster. Surprisingly, whereas efflux activity enhanced in the smaller populations, it decayed in the larger ones. The evolution of efflux activity was largely shaped by pleiotropic responses to selection and not by drift. This demonstrates that quantitative differences in population size can lead to qualitative differences (decay/enhancement) in the fate of a character during adaptation to identical environments. Furthermore, the larger populations showed inferior fitness upon sudden exposure to several alternative stressful environments. These observations provide a novel link between population size and vulnerability to environmental changes. Counter-intuitively, adapting in larger numbers can render bacterial populations more vulnerable to abrupt environmental changes.
Measuring individual identity information in animal signals: Overview and performance of available identity metrics
Authors: Linhart Pavel , Osiejuk Tomasz , Budka Michal , Šálek Martin , Špinka Marek , Policht Richard , Syrová Michaela , Blumstein Daniel T. 
Published: February 2019

AbstractIdentity signals have been studied for over 50 years but there is no consensus as to how to quantify individuality. While there are a variety of different metrics to quantify individual identity, or individuality, these methods remain un-validated and the relationships between them unclear.We contrasted three univariate and four multivariate metrics (and their different computational variants) and evaluated their performance on simulated and empirical datasets.Of the metrics examined, Beecher’s information statistic (HS) was the best one and could easily and reliably be converted into the commonly used discrimination score (and vice versa) after accounting for the number of individuals and calls per individual in a given dataset. Although Beecher’s information statistic is not entirely independent of sampling parameters, this problem can be removed by reducing the number of parameters or by increasing the number of individuals.Because it is easily calculated, has superior performance, can be used to describe single variables or signal as a whole, and because it tells us the maximum number of individuals that can be discriminated given a set of measurements, we recommend that individuality should be quantified using Beecher’s information statistic.
Comprehensive circular RNA expression profiles in intermuscular fat from lean and obese pigs
Authors: Miao Zhiguo , Zhang Jinzhou , Wang Shan , Wei Paneng 
Published: February 2019

AbstractCircular RNA (circRNA) plays an important regulatory role in development and differentiation. Intermuscular fat in pork affects the tenderness and juiciness of the meat. In this study, we investigated the performances of Landrace (lean) and Jinhua (obese) pigs at the fattening period and explored the expression profile of circRNAs in intermuscular fat from the two breeds by Illumina high-throughput sequencing. we identified 5 548 circRNAs, specifically 2 651 (47.78%) in the Jinhua pigs, and 2 897 (52.22%) in the Landrace pigs. A totale of 809 differentially expressed circRNAs were observed between the the Jinhua and Landrace pigs, but only 29 of these circRNAs showed significant difference (19 upregulated and 10 downregulated). All 1 306 unigenes and 27 differentially expressed unigenesinvolved in lipid transport and metabolism; replication, recombination and repair; and signaling pathway were annotated. A total of 550 target miRNAs were perfect seed matches and 20 522 target genes were foundBy RNAhybrid and miRanda software prediction. Results from real-time quantitative PCR also confirmed the differential expression of 13 mRNAs between the two pig breeds. This study provides comprehensive expression profiles of circRNAs in Sus scrofa adipose metabolism and development, which can be used to clarify their functions.Summary statementThe paper explored the expression profile of circRNAs in intermuscular fat from Landrace and Jinhua pigs at the fattening period, to provide insights into circRNAregulation in animal adipose metabolism.
Transcriptome Analysis of juvenile Pacific White Shrimp (Litopenaeus vannamei) with symptom of stunted growth
Authors: Fang Huaiyi , Song Jingjing , Gong Bin , Pang Tingcai , Peng Chunyan 
Published: February 2019

AbstractIn search for viruses associated with Litopenaeus vannamei with symptom of stunted growth, we have undertaken a comparative transcriptome analysis of total RNA sequences using Illumina based high-throughput sequencing (HTS). We obtain 89000242 and 95126160 high-quality clean reads from cDNA libraries of L.vannamei with stunted growth symptom (sick group) and health shrimp (health group control), respectively. Totally, 108221 unigenes with an average length of 716 bp were obtained from RNA-seq data. The unigenes were annotated against NR, NT, KO, KOG, SwissProt, PFAM and GO databases. 3975 (3.67%) showed significant matches in all the above databases and 39812 (36.78%) unigenes were annotated in at least one database. Comparative transcriptomic analysis revealed that 807 significantly differentially expressed unigenes were identified, including 282 down-regulated genes and 525 up-regulated genes. Thirteen up-regulated virus-related genes were only discovered in the sick shrimp groups, but not in health ones. Five of them were closely related to virus family Picornaviridae. From phylogenetic tree, we could find five viral genes were closely related to genus Ampvirus, Falcovirus, Aquamavirus (Seal picornavirus). Some up-regulated genes in the Sick groups mainly included genes involved in virus infecting processes concerning antigen processing and presenting, apoptosis, lysosome, phagosome and inflammation. While, many down-regulated genes in the Sick groups mainly involved in the process of starch and sucrose metabolism, and protein digestion and absorption. Our research provided some useful information about pathogenic factor and mechanism on the stunted growth symptom of L.vannamei, and was significant for the control and prevention of this disease.
Forest fragmentation and impacts of intensive agriculture: responses from functional groups of the tree community
Authors: Tenius Ribeiro Juliana C. , Nunes-Freitas André Felippe , Uzêda Mariella Camardelli 
Published: February 2019

AbstractAgricultural landscapes are seen as areas of extreme importance for studying and developing strategies that integrate biodiversity conservation and ecosystem services with food production. The main strategies for intensifying agriculture are based on conventional practices of frequently using agricultural inputs for fertilization and correction of soil pH. Some studies show that these practices generate impacts on nearby forest fragments through soil contamination, causing an increase in nutrient content. The objective of this study was to identify the impacts on the functional groups of sciophilous and heliophilous species of a tree community of 14 forest fragments near agricultural areas under conventional practices, and raised the hypothesis that the higher the fertility of forest fragments adjacent to intensive agriculture modifies the floristic composition of the tree community. The floristic composition of fragments close to agricultural areas are more similar to each other and the General Linear Model (GLM) results show a clear influence of the intensive farming environment on the richness and abundance of the two functional groups in the forest fragments, directly benefiting the abundance of heliophilous species which are also benefited by the greater declivity and smaller fragment area, while the abundance of sciophytes is negatively correlated with these last two variables. The increase of calcium content is beneficial for the richness of heliophilous species, while the increase in phosphorus content influences a reduction in the richness of sciophyte species, which also respond strongly to the isolation between fragments. The results indicate a dominance trend of pioneer species in nutritionally enriched soils, evidencing that the intense adoption of inputs in cultivated areas causes concrete impacts on the diversity of the tree community of forest fragments, being more determinant for the species richness than the size of the fragments.
A generic cell surface ligand system for studying cell-cell recognition
Authors: Denham Eleanor M , Barton Michael I , Black Susannah M , Bridge Marcus J , Wet Ben de , Paterson Rachel L , der Merwe P. Anton van , Goyette Jesse 
Published: February 2019

AbstractDose-response experiments are a mainstay of receptor biology studies and can reveal valuable insights into receptor function. Such studies of receptors that bind cell surface ligands are currently limited by the difficulty in manipulating the surface density of ligands at a cell-cell interface. Here we describe a generic cell surface ligand system that allows precise manipulation of cell surface ligand densities over several orders of magnitude. We validate the system for a range of immunoreceptors, including the T cell receptor (TCR), and show that this generic ligand stimulates via the TCR at a similar surface density as its native ligand. This system allows the effect of surface density, valency, dimensions, and affinity of the ligand to be manipulated. It can be readily extended to other receptor-cell surface ligand interactions, and will facilitate investigation into the activation of, and signal integration between, cell surface receptors.