bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying regulatory and spatial genomic architectural elements using cell type independent machine and deep learning models
Authors: Martens Laura D. , Faust Oisín , Pirvan Liviu , Bihary Dóra , Samarajiwa Shamith A. 
Published: April 2020

AbstractChromosome conformation capture methods such as Hi-C enables mapping of genome-wide chromatin interactions and is a promising technology to understand the role of spatial chromatin organisation in gene regulation. However, the generation and analysis of these data sets at high resolutions remain technically challenging and costly. We developed a machine and deep learning approach to predict functionally important, highly interacting chromatin regions (HICR) and topologically associated domain (TAD) boundaries independent of Hi-C data in both normal physiological states and pathological conditions such as cancer. This approach utilises gradient boosted trees and convolutional neural networks trained on both Hi-C and histone modification epigenomic data from three different cell types. Given only epigenomic modification data these models are able to predict chromatin interactions and TAD boundaries with high accuracy. We demonstrate that our models are transferable across cell types, indicating that combinatorial histone mark signatures may be universal predictors for highly interacting chromatin regions and spatial chromatin architecture elements.
Enhancement of motor performance by a training method combining motor imagery and neurofeedback
Authors: Sha Chosei , Tamura Kaori , Okamoto Tsuyoshi 
Published: April 2020

AbstractMotor imagery and neurofeedback have been proposed as motor training approaches, but their effects on the enhancement of motor performance are still controversial. This study aimed to enhance motor performance using a training protocol combining motor imagery and neurofeedback. Seventeen participants were randomly assigned to the training or control group. The training group received real-time electroencephalography activity feedback relative to the motor imagery of the motor action. The control group reiterated the motor imagery of the intended motor action without feedback. The motor performance of the training group was enhanced significantly more than that of the control group. Subsequently, the proposed training protocol was tested in five elite male tennis players to investigate its applicability to sports activities. The motor performance was enhanced in three of these five professional tennis players. Using our training protocol, which combined motor imagery and neurofeedback training, we achieved enhanced motor performance. Furthermore, we could suggest the applicability to sports from the results with world-level tennis players.
The effect of Dicer knockout on RNA interference using various Dicer substrate interfering RNA structures
Authors: Song Min-Sun , Rossi John J 
Published: April 2020

AbstractDicer-substrate siRNA (DsiRNA) was a useful tool for sequence-specific gene silencing. DsiRNA was proposed to have increased efficacy via RNAi gene silencing, but the molecular mechanism underlying the increased efficacy is not precise. We designed the tetra-looped DsiRNA as the tetra-looped RNAs have been reported more stable structure and increased binding efficiency with RNA and protein. To gain a deeper understanding of the Dicer function of DsiRNA, we knocked out Dicer in the HCT116 cell line and analyzed the efficacy of various Dicer substrates on RNAi gene silencing activity. Tetra-looped DsiRNA demonstrated increased efficacy of gene silencing Dicer expressing cells with activity favoring the guide strand. The gene silencing activity of all DsiRNAs was reduced in Dicer knockout cells. Thus, this study allows us to understand the Dicer function of key RNAi silencing and provides valuable resources for RNAi research and applications.
Global analysis of protein stability by temperature and chemical denaturation
Authors: Hamborg Louise , Horsted Emma Wenzel , Johansson Kristoffer Enøe , Willemoës Martin , Lindorff-Larsen Kresten , Teilum Kaare 
Published: April 2020

AbstractThe stability of a protein is a fundamental property that determines under which conditions, the protein is functional. Equilibrium unfolding with denaturants requires preparation of several samples and only provides the free energy of folding when performed at a single temperature. The typical sample requirement is around 0.5 – 1 mg of protein. If the stability of many proteins or protein variants needs to be determined, substantial protein production may be needed. Here we have determined the stability of acyl-coenzyme A binding protein at pH 5.3 and chymotrypsin inhibitor 2 at pH 3 and pH 6.25 by combined temperature and denaturant unfolding. We used a setup where tryptophan fluorescence is measured in quartz capillaries where only 10 μl is needed. Temperature unfolding of a series of 15 samples at increasing denaturant concentrations provided accurate and precise thermodynamic parameters. We find that the number of samples may be further reduced and less than 10 μg of protein in total are needed for reliable stability measurements. For assessment of stability of protein purified in small scale e.g. in micro plate format, our method will be highly applicable. The routine for fitting the experimental data is made available as a python notebook.
Virtual EEG-electrodes: Convolutional neural networks as a method for upsampling or restoring channels
Authors: Svantesson Mats , Olausson Håkan , Eklund Anders , Thordstein Magnus 
Published: April 2020

ABSTRACTBackgroundIn clinical practice, EEGs are assessed visually. For practical reasons, recordings often need to be performed with a reduced number of electrodes and artifacts make assessment difficult. To circumvent these obstacles, different interpolation techniques can be utilized. These techniques usually perform better for higher electrode densities and values interpolated at areas far from electrodes can be unreliable. Using a method that learns the statistical distribution of the cortical electrical fields and predicts values may yield better results.New MethodGenerative networks based on convolutional layers were trained to upsample from 4 or 14 channels or to dynamically restore single missing channels to recreate 21 channel EEGs. 5,144 hours of data from 1,385 subjects of the Temple University Hospital EEG database were used for training and evaluating the networks.Comparison with Existing MethodThe results were compared to spherical spline interpolation. Several statistical measures were used as well as a visual evaluation by board certified clinical neurophysiologists. Overall, the generative networks performed significantly better. There was no difference between real and network generated data in the number of examples assessed as artificial by experienced EEG interpreters whereas for data generated by interpolation, the number was significantly higher. In addition, network performance improved with increasing number of included subjects, with the greatest effect seen in the range 5 – 100 subjects.ConclusionsUsing neural networks to restore or upsample EEG signals is a viable alternative to interpolation methods.
Tmed2regulates Smoothened trafficking and Hedgehog signalling
Authors: Di Minin Giulio , Dumeau Charles E. , Grison Alice , Chan Wesley , Monfort Asun , Jerome-Majewska Loydie A. , Wutz Anton 
Published: April 2020

AbstractHedgehog (HH) signalling plays a key role in embryonic pattering and stem cell differentiation. Compounds that selectively bind Smoothened (SMO) can induce cell death in mouse embryonic stem cells (ESCs). Here we perform a genetic screen in haploid ESCs and discover that SMO inhibits a cell death pathway that resembles dissociation induced death of human ESCs and Anoikis. In mouse ESCs, SMO acts through a G-protein coupled mechanism that is independent of GLI activation. Our screen also identifies the Golgi proteins Tmed2 and Tmed10. We show that TMED2 binds SMO and controls its abundance at the plasma membrane. In neural differentiation and neural tube pattering Tmed2 acts as a repressor of HH signalling strength. We demonstrate that the interaction between SMO and TMED2 is regulated by HH signalling suggesting SMO release form the ER-Golgi is critical for controlling G-protein and GLI mediated functions of mammalian HH signalling.
A comprehensive toolkit for quick and easy visualization of marker proteins, protein-protein interactions and cell morphology inMarchantia polymorpha
Authors: Westermann Jens , Koebke Eva , Lentz Roswitha , Hülskamp Martin , Boisson-Dernier Aurélien 
Published: April 2020

AbstractEven though stable genomic transformation of sporelings and thalli ofMarchantia polymorphais comparatively straightforward and efficient, numerous problems can arise during critical phases of the process such as efficient spore production, poor selection capacity of antibiotics or low transformation efficiency. It is therefore also desirable to establish quick methods not relying on stable transgenics to analyze the localization, interactions and functions of proteins of interest. The introduction of foreign DNA into living cells via biolistic mechanisms has been first reported roughly 30 years ago and has been commonly exploited in established plant model species such asArabidopsis thalianaorNicotiana benthamiana. Here we report the fast and reliable transient biolistic transformation of Marchantia thallus epidermal cells using fluorescent protein fusions. We present a catalogue of fluorescent markers which can be readily used for tagging of a variety of subcellular compartments. Moreover, we report the functionality of the bimolecular fluorescence complementation (BiFC) inM. polymorphawith the example of the p-body markers MpDCP1/2. Finally, we provide standard staining procedures for live cell imaging inM. polymorpha, applicable to visualize cell boundaries or cellular structures, to complement or support protein localizations and to understand how results gained by transient transformations can be embedded in cell architecture and dynamics. Taken together, we offer a set of easy and quick tools for experiments that aim at understanding subcellular localization, protein-protein interactions and thus functions of proteins of interest in the emerging early diverging land plant modelM. polymorpha.
One-shot analysis of translated mammalian lncRNAs with AHARIBO
Authors: Minati Luca , Firrito Claudia , Piano Alessia Del , Peretti Alberto , Sidoli Simone , Peroni Daniele , Belli Romina , Gandolfi Francesco , Romanel Alessandro , Bernabò Paola , Zasso Jacopo , Quattrone Alessandro , Guella Graziano , Lauria Fabio , Viero Gabriella , Clamer Massimiliano 
Published: April 2020

SUMMARYA vast portion of the mammalian genome is transcribed as long non-coding RNAs (lncRNAs) acting in the cytoplasm with largely unknown functions. Surprisingly, lncRNAs have been shown to interact with ribosomes, encode uncharacterized proteins, or act as ribosome sponges. These functions still remain mostly undetected and understudied owing to the lack of efficient tools for genome-wide simultaneous identification of ribosome-associated lncRNAs and peptide-producing lncRNAs.Here we present AHARIBO, a method for the detection of lncRNAs either untranslated, but associated with ribosomes, or encoding small peptides. Using AHARIBO in mouse embryonic stem cells during neuronal differentiation, we isolated ribosome-protected RNA fragments, translated RNAs and correspondingde novosynthesized polypeptides. Besides identifying mRNAs under active translation and associated ribosomes, we found and distinguished lncRNAs acting as ribosome sponges or encoding micropeptides, laying the ground for a better functional understanding of hundreds lncRNAs.
Deregulation of the histone H3K9 di-methylation landscape suppresses canonical Wnt signaling in embryonal rhabdomyosarcoma
Authors: Pal Ananya , Leung Jia Yu , Ang Gareth Chin Khye , Rao Vinay Kumar , Pignata Luca , Lim Huey Jin , Hebrard Maxime , Chang Kenneth T , Lee Victor KM , Guccione Ernesto , Taneja Reshma 
Published: April 2020

AbstractThe Wnt signaling pathway is down-regulated in embryonal rhabdomyosarcoma (ERMS) and contributes to the block of myogenic differentiation. Epigenetic mechanisms leading to its suppression are unknown and could pave the way towards novel therapeutic modalities. In this study, we demonstrate that the H3K9 lysine methyltransferase G9a suppresses canonical Wnt signaling by activating expression of the Wnt antagonistDKK1. Inhibition of G9a expression or activity reducedDKK1expression and elevated canonical Wnt signaling resulting in myogenic differentiationin vitroandin vivo. Mechanistically, G9a impacted Sp1 and p300 enrichment at theDKK1promoter in a methylation-dependent manner. The reduced tumor growth upon G9a deficiency was reversed by recombinant DKK1 or LGK974, which also inhibits Wnt signaling. Consistently, among thirteen drugs targeting chromatin modifiers, G9a inhibitors were highly effective in reducing ERMS cell viability. Together, our study demonstrates that ERMS cells are vulnerable to G9a inhibitors and suggest that targeting the G9a-DKK1-β-catenin node holds promise for differentiation therapy.
Contrasting stripes are a widespread feature of group living in birds, mammals and fishes
Authors: Negro Juan J. , Doña Jorge , Blázquez M. del Carmen , Rodríguez Airam , Herbert-Read James E. , Brooke M. de L. 
Published: April 2020

AbstractGrouping is a widespread form of predator defense, with individuals in groups often performing evasive collective movements in response to predators’ attacks. Individuals in these groups use behavioral rules to coordinate their movements, with visual cues about neighbors’ positions and orientations informing movement decisions. Although the exact visual cues individuals use to coordinate their movements with neighbors have not yet been decoded, some studies have suggested that stripes, lines or other body patterns may act as conspicuous conveyors of movement information that could promote coordinated group movement, or promote dazzle camouflage, thereby confusing predators. We used phylogenetic logistic regressions to test whether the contrasting achromatic stripes present in four different taxa vulnerable to predation, including species within two orders of birds (Anseriformes and Charadriiformes), a suborder of Artiodactyla (the ruminants) and several orders of marine fish (predominantly Perciformes) were associated with group living. Contrasting patterns were significantly more prevalent in social species, and tended to be absent in solitary species or species less vulnerable to predation. We suggest that stripes taking the form of light-colored lines on dark backgrounds, orvice versa, provide a widespread mechanism across taxa that serves either to inform conspecifics of neighbors’ directional movement, or to confuse predators, when moving in groups. Detection and processing of patterns and of motion in the visual channel is essentially colourblind. That diverse animal taxa with widely different vision systems (including di-, tri- and tetrachromats) appear to have converged on a similar use of achromatic patterns is therefore expected given signal-detection theory. This hypothesis would explain the convergent evolution of conspicuous achromatic patterns as an antipredator mechanism in numerous vertebrate species.
Learned SPARCOM: Unfolded Deep Super-Resolution Microscopy
Authors: Dardikman-Yoffe Gili , Eldar Yonina C. 
Published: April 2020

AbstractThe use of photo-activated fluorescent molecules to create long sequences of low emitter-density diffraction-limited images enables high-precision emitter localization. However, this is achieved at the cost of lengthy imaging times, limiting temporal resolution. In recent years, a variety of approaches have been suggested to reduce imaging times, ranging from classical optimization and statistical algorithms to deep learning methods. Classical methods often rely on prior knowledge of the optical system and require heuristic adjustment of parameters or do not lead to good enough performance. Deep learning methods proposed to date tend to suffer from poor generalization ability outside the specific distribution they were trained on, and require learning of many parameters. They also tend to lead to black-box solutions that are hard to interpret. In this paper, we suggest combining a recent high-performing classical method, SPARCOM, with model-based deep learning, using the algorithm unfolding approach which relies on an iterative algorithm to design a compact neural network considering domain knowledge. We show that the resulting network, Learned SPARCOM (LSPARCOM), requires far fewer layers and parameters, and can be trained on a single field of view. Nonetheless it yields comparable or superior results to those obtained by SPARCOM with no heuristic parameter determination or explicit knowledge of the point spread function, and is able to generalize better than standard deep learning techniques. It even allows producing a high-quality reconstruction from as few as 25 frames. This is due to a significantly smaller network, which also contributes to fast performance - 5× improvement in execution time relative to SPARCOM, and a full order of magnitudes improvement relative to a leading competing deep learning method (Deep-STORM) when implemented serially. Our results show that we can obtain super-resolution imaging from a small number of high emitter density frames without knowledge of the optical system and across different test sets. Thus, we believe LSPARCOM will find broad use in single molecule localization microscopy of biological structures, and pave the way to interpretable, efficient live-cell imaging in a broad range of settings.
Multiple paths to cold tolerance: the role of environmental cues, morphological traits and the circadian clock genevrille
Authors: Poikela Noora , Tyukmaeva Venera , Hoikkala Anneli , Kankare Maaria 
Published: April 2020

AbstractBackgroundTracing the association between insect cold tolerance and latitudinally and locally varying environmental conditions, as well as key morphological traits and molecular mechanisms, is essential for understanding the processes involved in adaptation. We explored these issues in two closely-related species,Drosophila montanaandDrosophila flavomontana, originating from diverse climatic locations across several latitudes on the coastal and mountainous regions of North America. We also investigated the association between sequence variation in one of the key circadian clock genes,vrille, and cold tolerance in both species. Finally, we studied the impact ofvrilleon fly cold tolerance and cold acclimation ability by silencing it with RNA interference inD. montana.ResultsWe performed a principal component analysis (PCA) on variables representing bioclimatic conditions on the study sites and used latitude as a proxy of photoperiod. PC1 separated the mountainous continental sites from the coastal ones based on temperature variability and precipitation, while PC2 arranged the sites based on summer and annual mean temperatures. Cold tolerance tests showedD. montanato be more cold-tolerant thanD. flavomontanaand chill coma resistance (CTmin) of this species showed an association with PC2. Chill coma recovery time (CCRT) of both species improved towards northern latitudes, and inD. flavomontanathis trait was also associated with PC1.D. flavomontanaflies were darkest in the coast and in the northern mountainous populations, but coloration showed no linkage with cold tolerance. Body size decreased towards cold environments in both species, but only withinD. montanapopulations largest flies showed fastest recovery from cold. Finally, both the sequence analysis and RNAi study onvrillesuggested this gene to play an essential role inD. montanacold resistance and acclimation, but not in recovery time.ConclusionsOur study demonstrates the complexity of insect cold tolerance and emphasizes the need to trace its association with multiple environmental variables and morphological traits to identify potential agents of natural selection. It also shows that a circadian clock genevrilleis essential both for short- and long-term cold acclimation, potentially elucidating the connection between circadian clock system and cold tolerance.
An open-sourced bioinformatic pipeline for the processing of Next-Generation Sequencing derived nucleotide reads: Identification and authentication of ancient metagenomic DNA
Authors: Collin Thomas C. , Drosou Konstantina , O’Riordan Jeremiah Daniel , Meshveliani Tengiz , Pinhasi Ron , Feeney Robin N. M. 
Published: April 2020

AbstractBioinformatic pipelines optimised for the processing and assessment of metagenomic ancient DNA (aDNA) are needed for studies that do not make use of high yielding DNA capture techniques. These bioinformatic pipelines are traditionally optimised for broad aDNA purposes, are contingent on selection biases and are associated with high costs. Here we present a bioinformatic pipeline optimised for the identification and assessment of ancient metagenomic DNA without the use of expensive DNA capture techniques. Our pipeline actively conserves aDNA reads, allowing the application of a bioinformatic approach by identifying the shortest reads possible for analysis (22-28bp). The time required for processing is drastically reduced through the use of a 10% segmented non-redundant sequence file (229 hours to 53). Processing speed is improved through the optimisation of BLAST parameters (53 hours to 48). Additionally, the use of multi-alignment authentication in the identification of taxa increases overall confidence of metagenomic results. DNA yields are further increased through the use of an optimal MAPQ setting (MAPQ 25) and the optimisation of the duplicate removal process using multiple sequence identifiers (a 4.35-6.88% better retention). Moreover, characteristic aDNA damage patterns are used to bioinformatically assess ancient vs. modern DNA origin throughout pipeline development. Of additional value, this pipeline uses open-source technologies, which increases its accessibility to the scientific community.
Endophilin A2 regulates B cell protein trafficking and humoral responses
Authors: Malinova Dessislava , Wasim Laabiah , Engels Niklas , Tolar Pavel 
Published: April 2020

ABSTRACTAntigen-specific B cell responses require endosomal trafficking to regulate antigen uptake and presentation to helper T cells, and to control expression and signaling of immune receptors. However, the molecular composition of B cell endosomal trafficking pathways and their specific roles in B cell responses have not been systematically investigated. Here we report high-throughput identification of genes regulating B cell receptor (BCR)-mediated antigen internalization using genome-wide functional screens. We show that antigen internalization depends both on clathrin-coated pits and on clathrin-independent endocytosis mediated by endophilin A2. Although endophilin A2 is dispensable for presentation of the endocytosed antigen, it is required for metabolic support of germinal center (GC) B cell proliferation, in part through regulation of iron uptake. Consequently, endophilin A2 deficient mice show selective defects in GC B cell responses and production of high-affinity IgG. The requirement for endophilin A2 highlights a unique importance of clathrin-independent intracellular trafficking in GC B cell clonal expansion and antibody responses.HIGHLIGHTSGenome-wide CRISPR screens comprehensively identify genes regulating antigen uptake in B cellsB cell receptor-mediated antigen internalization is mediated by both epsin1- dependent clathrin-coated pits and a novel fast endophilin A2-mediated endocytosis.Endophilin A2 is required for peripheral B cell development, antigen-specific germinal center responses and high-affinity IgG production.Endophilin A2 is broadly essential for B cell intracellular trafficking pathways providing metabolic support of germinal center B cell proliferation, in part through regulation of iron uptake.