bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of caecaloids to study host-pathogen interactions: new insights into immunoregulatory functions ofTrichuris murisextracellular vesicles in the caecum
Authors: Duque-Correa María A. , Schreiber Fernanda , Rodgers Faye H. , Goulding David , Forrest Sally , White Ruby , Buck Amy , Grencis Richard K. , Berriman Matthew 
Published: May 2020

ABSTRACTThe caecum, an intestinal appendage in the junction of the small and large intestines, displays a unique epithelium that serves as an exclusive niche for a range of pathogens including whipworms (Trichuris spp). While protocols to grow organoids from small intestine (enteroids) and colon (colonoids) exist, the conditions to culture organoids from the caecum have yet to be described. Here, we report methods to grow, differentiate and characterise mouse adult stem cell-derived caecal organoids, termed caecaloids. We compare the cellular composition of caecaloids to that of enteroids identifying differences in intestinal epithelial cell (IEC) populations that mimic those found in the caecum and small intestine. The remarkable similarity in the IECs composition and spatial conformation of caecaloids and their tissue of origin enables their use as anin vitromodel to study host interactions with important caecal pathogens. Thus, exploiting this system we investigated the responses of caecal IECs to extracellular vesicles (EVs) secreted/excreted by the intracellular helminthTrichuris muris.Our findings reveal novel immunoregulatory effects of whipworm EVs on the caecal epithelium, including the downregulation of responses to nucleic acid recognition and type-I interferon (IFN) signalling.
GABAA receptor mapping in human using non-invasive electrophysiology
Authors: Shaw Alexander D , Chandler Hannah L , Hamandi Khalid , Muthukumaraswamy Suresh D , Hammers Alexander , Singh Krish D 
Published: May 2020

AbstractThe non-invasive study of cortical oscillations provides a window onto neuronal processing. Temporal correlation of these oscillations between distinct anatomical regions is considered a marker of functional connectedness. As the most abundant inhibitory neurotransmitter in the mammalian brain, γ-aminobutyric acid (GABA) is thought to play a crucial role in shaping the frequency and amplitude of oscillations, which thereby suggests a role for GABA in shaping the topography of functional activity and connectivity. This study explored the effects of pharmacologically blocking the reuptake of GABA (increasing local concentrations) through oral administration of the GABA transporter 1 (GAT1) blocker tiagabine (15 mg). We show that the spatial distribution of tiagabine-induced activity changes, across the brain, corresponds to group-average flumazenil PET maps of GABAA receptor distribution.In a placebo-controlled crossover design, we collected resting magnetoencephalography (MEG) recordings from 15 healthy male individuals prior to, and at 1-, 3- and 5- hours post, administration of tiagabine and placebo pill. Using leakage-corrected amplitude envelope correlations (AECs), we quantified the functional connectivity in discrete frequency bands across the whole brain, using the 90-region Automatic Anatomical Labelling atlas (AAL90), as well as quantifying the average oscillatory activity across the brain.Analysis of variance in connectivity using a drug-by-session (2×4) design revealed interaction effects, accompanied by main effects of drug and session. Post-hoc permutation testing of each post-drug recording against the respective pre-drug baseline revealed consistent reductions of a bilateral occipital network spanning theta, alpha and beta frequencies, and across 1- 3- and 5- hour recordings following tiagabine, but not placebo.The same analysis applied to activity, across the brain, also revealed a significant interaction, with post-hoc permutation testing demonstrating significant increases in activity across frontal regions, coupled with reductions in activity in posterior regions, across the delta, theta, alpha and beta frequency bands.Crucially, we show that the spatial distribution of tiagabine-induced changes in oscillatory activity overlap significantly with group-averaged maps of the estimated distribution of GABAA receptors, derived from scaled flumazenil volume-of-distribution (FMZ-VT) PET, hence demonstrating a possible mechanistic link between GABA availability, GABAA receptor distribution, and low-frequency network oscillations. We therefore propose that electrophysiologically-derived maps of oscillatory connectivity and activity can be used as sensitive, time-resolved, and targeted receptor-mapping tools for pharmacological imaging at the group level, providing direct measures of target engagement and pharmacodynamics.
Predicting drug-target interactions using multi-label learning with community detection method (DTI-MLCD)
Authors: Chu Yanyi , Shan Xiaoqi , Salahub Dennis R. , Xiong Yi , Wei Dong-Qing 
Published: May 2020

AbstractIdentifying drug-target interactions (DTIs) is an important step for drug discovery and drug repositioning. To reduce heavily experiment cost, booming machine learning has been applied to this field and developed many computational methods, especially binary classification methods. However, there is still much room for improvement in the performance of current methods. Multi-label learning can reduce difficulties faced by binary classification learning with high predictive performance, and has not been explored extensively. The key challenge it faces is the exponential-sized output space, and considering label correlations can help it. Thus, we facilitate the multi-label classification by introducing community detection methods for DTIs prediction, named DTI-MLCD. On the other hand, we updated the gold standard data set proposed in 2008 and still in use today. The proposed DTI-MLCD is performed on the gold standard data set before and after the update, and shows the superiority than other classical machine learning methods and other benchmark proposed methods, which confirms the efficiency of it. The data and code for this study can be found athttps://github.com/a96123155/DTI-MLCD.
RippleNet: A Recurrent Neural Network for Sharp Wave Ripple (SPW-R) Detection
Authors: Hagen Espen , Chambers Anna R. , Einevoll Gaute T. , Pettersen Klas H. , Enger Rune , Stasik Alexander J. 
Published: May 2020

AbstractHippocampal sharp wave ripples (SPW-R) have been identified as key bio-markers of important brain functions such as memory consolidation and decision making. SPW-R detection typically relies on hand-crafted feature extraction, and laborious manual curation is often required. In this multidisciplinary study, we propose a novel, self-improving artificial intelligence (AI) method in the form of deep Recurrent Neural Networks (RNN) with Long Short-Term memory (LSTM) layers that can learn features of SPW-R events from raw, labeled input data. The algorithm is trained using supervised learning on hand-curated data sets with SPW-R events. The input to the algorithm is the local field potential (LFP), the low-frequency part of extracellularly recorded electric potentials from the CA1 region of the hippocampus. The output prediction can be interpreted as the time-varying probability of SPW-R events for the duration of the input. A simple thresholding applied to the output probabilities is found to identify times of events with high precision. The reference implementation of the algorithm, named ‘RippleNet’, is open source, freely available, and implemented using a common open-source framework for neural networks (tensorflow.keras) and can be easily incorporated into existing data analysis workflows for processing experimental data.
Hunting with catapults: the predatory strike of the dragonfly larva
Authors: Büsse Sebastian , Koehnsen Alexander , Rajabi Hamed , Gorb Stanislav N. 
Published: May 2020

AbstractDragonfly larvae capture their prey with a strongly modified -extensible- mouthpart using a biomechanically unique but not yet understood mechanism. The current opinion of hydraulic pressure being the driving force of the predatory strike can be refuted by our manipulation experiments and reinterpretation of former studies. On this fact, we present evidence for a synchronized dual-catapult system powered by two spring-loaded catapults. The power output of the system exceeds generally the maximum power achievable by musculature. Energy for the movement is stored by straining a resilin-containing structure at each joint and possibly the surrounding cuticle which is preloaded by muscle contraction. To achieve the precise timing required to catch fast-moving prey, accessory structures are used to lock and actively trigger the system, ensuring the synchronisation of both catapults. As a proof of concept, we developed a bio-inspired robotic arm resembling the morphology and functional principle of the extensible mouthpart. Our study elucidates the predatory strike of dragonfly larvae by proposing a novel mechanism, where two synchronized catapults power the ballistic movement of prey capturing in dragonfly larvae – a so-called synchronized dual-catapult system. Understanding this complex biomechanical system may further our understanding in related fields of bio inspired robotics and biomimetics.One Sentence SummaryThe synchronized dual-catapult, a biomechanically novel mechanism for the ballistic movement of prey capturing in dragonfly larvae
ctmmweb: A graphical user interface for autocorrelation-informed home range estimation
Authors: Calabrese Justin M. , Fleming Christen H. , Noonan Michael J. , Dong Xianghui 
Published: May 2020

ABSTRACTEstimating animal home ranges is a primary purpose of collecting tracking data. All conventional home range estimators in widespread usage, including minimum convex polygons and kernel density estimators, assume independently sampled data. In stark contrast, modern GPS animal tracking datasets are almost always strongly autocorrelated. This incongruence between estimator assumptions and empirical reality leads to systematically underestimated home ranges. Autocorrelated kernel density estimation (AKDE) resolves this conflict by modeling the observed autocorrelation structure of tracking data during home range estimation, and has been shown to perform accurately across a broad range of tracking datasets. However, compared to conventional estimators, AKDE requires additional modeling steps and has heretofore only been accessible via the command-linectmmR package. Here, we introducectmmweb, which provides a point-and-click graphical interface toctmm, and streamlines AKDE, its prerequisite autocorrelation modeling steps, and a number of additional movement analyses. We demonstratectmmweb’scapabilities, including AKDE home range estimation and subsequent home range overlap analysis, on a dataset of four jaguars from the Brazilian Pantanal. We intendctmmwebto open AKDE and related autocorrelation-explicit analyses to a wider audience of wildlife and conservation professionals.
Deubiquitinating Enzyme Amino Acid Profiling Reveals a Class of Ubiquitin Esterases
Authors: De Cesare Virginia , Lopez Daniel Carbajo , Mabbitt Peter D. , Antico Odetta , Wood Nicola T. , Virdee Satpal 
Published: May 2020

AbstractThe reversibility of ubiquitination by the action of deubiquitinating enzymes (DUBs) serves as an important regulatory layer within the ubiquitin system. Approximately 100 DUBs are encoded by the human genome and many have been implicated with pathologies including neurodegeneration and cancer. Non-lysine ubiquitination is chemically distinct and its physiological importance is emerging. Here we couple chemically and chemoenzymatically synthesized ubiquitinated lysine and threonine model substrates to a matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry-based DUB assay. Using this platform, we profile two-thirds of known catalytically active DUBs for threonine esterase and lysine isopeptidase activity and find that most DUBs demonstrate dual selectivity. However, with two anomalous exceptions, the ovarian tumor domain (OTU) DUB class demonstrate specific (iso)peptidase activity. Strikingly, we find the Machado Josephin Domain (MJD) class to be unappreciated non-lysine DUBs with highly specific ubiquitin esterase activity that rivals the efficiency of the most active isopeptidases. Esterase activity is dependent on the canonical catalytic triad but proximal hydrophobic residues appear to be general determinants of non-lysine activity. These findings suggest that non-lysine ubiquitination is an integral component of the ubiquitin system, with regulatory sophistication comparable to that of canonical ubiquitination.
Leaf shape and size variation in bur oaks: An empirical study and simulation of sampling strategies
Authors: Desmond Sara C. , Garner Mira , Flannery Seamus , Whittemore Alan T. , Hipp Andrew L. 
Published: May 2020

ABSTRACTPREMISELeaf shape and size figure strongly in trees’ adaptation to their environments. Oaks are notoriously variable in leaf morphology. Our study examines the degree to which within-tree, among-tree, and among-site variation contribute to latitudinal variation in leaf shape and size of bur oak (Quercus macrocarpa: Fagaceae), one of North America’s most geographically widespread oak species.METHODSSamples were collected from four sites each at northern, central, and southern latitudes of the bur oak range. Ten leaf size traits were measured, and variance in these traits and eight ratios based on these traits was partitioned into tree, population, and latitude components. We then parameterized a series of leaf collection simulations using empirical covariance among leaves on trees and trees at sites. We used the simulations to assess the efficiency of different collecting strategies for estimating among-population differences in leaf shape and size.KEY RESULTSLeaf size measurements were highly responsive to latitude. Site contributed more than tree to total variation in leaf morphology. Simulations suggest that power to detect among-site variance in leaf shape and size can be estimated most efficiently with increases in either leaves per tree (10-11 leaves from each of 5 trees) or trees per site (5 leaves from each of 10+ trees).CONCLUSIONSOur study demonstrates the utility of simulating sampling and controlling for variance in sampling for leaf morphology, whether the questions being addressed are ecological, evolutionary, or taxonomic. Simulation code is provided as an R package (traitsPopSim) to help researchers plan morphological sampling strategies.
Somatostatin, anIn VivoBinder to Aβ Oligomers, Binds to βPFOAβ(1-42)Tetramer
Authors: Puig Eduard , Tolchard James , Riera Antoni , Carulla Natàlia 
Published: May 2020

AbstractSomatostatin (SST14) is strongly related to Alzheimer’s disease (AD), as its levels decline during aging, it regulates the proteolytic degradation of the amyloid beta peptide (Aβ), and it binds to Aβ oligomersin vivo. Recently, the 3D structure of a membrane-associated β-sheet pore forming tetramer (βPFOAβ(1-42)tetramer) has been reported. Here we show that SST14 binds selectively to the βPFOAβ(1-42)tetramer without binding to monomeric Aβ(1-42). Specific NMR chemical shift perturbations, observed during titration of SST14, define a binding site in the βPFOAβ(1-42)tetramer and are in agreement with a 2:1 stoichiometry determined by both native MS and ITC. These results enabled us to perform driven docking and model the binding mode for the interaction. The present study provides additional evidence on the relation between SST14 and the amyloid cascade, as well as positions the βPFOAβ(1-42)tetramer as a relevant aggregation form of Aβ and as a potential target for AD.
Structural variants at theBRCA1/2loci are a common source of homologous repair deficiency in high grade serous ovarian carcinoma
Authors: Ewing Ailith , Meynert Alison , Churchman Michael , Grimes Graeme R. , Hollis Robert L. , Herrington C. Simon , Rye Tzyvia , Bartos Clare , Croy Ian , Ferguson Michelle , Lennie Mairi , McGoldrick Trevor , McPhail Neil , Siddiqui Nadeem , Dowson Suzanne , Glasspool Rosalind , Mackean Melanie , Nussey Fiona , McDade Brian ,   The Scottish Genomes Partnership, McMahon Lynn , Matakidou Athena , Dougherty Brian , March Ruth , Barrett J. Carl , McNeish Iain A. , Biankin Andrew V. , Roxburgh Patricia , Gourley Charlie , Semple Colin A. 
Published: May 2020

AbstractAround half of high grade serous ovarian carcinomas (HGSOC) show homologous recombination repair deficiency (HRD), often caused by germline or somatic single nucleotide variant (SNV) mutations or small indels disruptingBRCA1/2. We have uniformly processed the largest collection of whole genome sequencing (WGS) data from HGSOC samples to date (N=205), comprehensively characterising the somatic mutational landscape, and expression at theBRCA1/2loci. We discover that large structural variants (SV) are a frequent but unappreciated source ofBRCA1/2disruption in these tumours. Somatic structural variation at these loci is dominated by multi-megabase deletions that span the entirety ofBRCA1(median = 4.9Mb) orBRCA2(median = 6.2Mb), independently affecting a substantial proportion of patients (16%) in addition to those affected by damaging germline or somatic short variants, within theBRCA1/2coding sequences (24%). In common with previous studies, we show that the presence of damaging somatic SNVs or short indels inBRCA1(OR=10, 95% CI 1.8-103, p=0.002, adj p=0.027 andBRCA2(OR=17, 95% CI 2.1-816), p=0.002, adj.p=0.021) was found to influence HRD. For the first time we also study the compound effect of SV and SNV or short indel mutations at both loci, demonstrating that SVs often contribute to compound deficiencies involving SNVs or indels, with large somatic deletions contributing to these compound deficiencies in 15/205 (7%) of samples. Notably the strongest risk of HRD (OR=19 (2.4-896), p=6.6×10-3, adj P=8.5×10-3) is generated by combined large deletions atBRCA1andBRCA2in the absence of SNVs or indels, affecting 3% of patients. Overall, we show that HRD is a complex phenotype in HGSOC tumours, affected by the patterns of shorter variants such as SNVs and indels, SVs, methylation and expression seen at multiple loci, and we construct a successful (ROC AUC = 0.75) predictive model of HRD using such variables. In addition, HRD impacts patient survival when conferred by mechanisms other than through the well-understood short variants atBRCA1/2, currently exploited in the clinic. These results alter our understanding of the mutational landscape at theBRCA1/2loci in highly rearranged tumours, and increase the number of patients predicted to benefit from therapies exploiting HRD in tumours such as PARP inhibition.
Dopaminergic neurons establish a distinctive axonal arbor with a majority of non-synaptic terminals
Authors: Ducrot Charles , Bourque Marie-Josée , Delmas Constantin V. L. , Racine Anne-Sophie , Bello Dainelys Guadarrama , Delignat-Lavaud Benoît , Lycas Matthew Domenic , Fallon Aurélie , Michaud-Tardif Charlotte , Nanni Samuel Burke , Herborg Freja , Gether Ulrik , Nanci Antonio , Takahashi Hideto , Parent Martin , Trudeau Louis-Eric 
Published: May 2020

ABSTRACTChemical neurotransmission in the brain typically occurs through synapses, which are structurally and functionally defined as sites of close apposition between an axon terminal and a postsynaptic domain. Ultrastructural examinations of axon terminals established by monoamine neurons in the brain often failed to identify a similar tight pre- and postsynaptic coupling, giving rise to the concept of “diffuse” or “volume” transmission. Whether this results from intrinsic properties of such modulatory neurons remains undefined. Using an efficient co-culture model, we find that dopaminergic neurons establish an axonal arbor that is distinctive compared to glutamatergic or GABAergic neurons in both size and propensity of terminals to avoid direct contact with target neurons. Furthermore, while most dopaminergic varicosities express key proteins involved in exocytosis such as synaptotagmin 1, only ~20% of these are synaptic. The active zone protein bassoon was found to be enriched in a subset of dopaminergic terminals that are in proximity to a target cell. Irrespective of their structure, a majority of dopaminergic terminals were found to be active. Finally, we found that the presynaptic protein Nrxn-1αSS4-and the postsynaptic protein NL-1AB, two major components involved in excitatory synapse formation, play a critical role in the formation of synapses by dopamine neurons. Taken together, our findings support the idea that dopamine neurons in the brain are endowed with a distinctive developmental program that leads them to adopt a fundamentally different mode of connectivity, compared to glutamatergic and GABAergic neurons involved in fast point-to-point signaling.SIGNIFICANCE STATEMENTMidbrain dopamine (DA) neurons regulate circuits controlling movement, motivation, and learning. The axonal connectivity of DA neurons is intriguing due to its hyperdense nature, with a particularly large number of release sites, most of which not adopting a classical synaptic structure. In this study, we provide new evidence highlighting the unique ability of DA neurons to establish a large and heterogeneous axonal arbor with terminals that, in striking contrast with glutamate and GABA neurons, actively avoid contact with the target cells. The majority of synaptic and non-synaptic terminals express proteins for exocytosis and are active. Finally, our finding suggests that, NL-1A+Band Nrxn-1αSS4-, play a critical role in the formation of synapses by DA neurons.