bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional Connectivity Evoked by Orofacial Tactile Perception of Velocity
Authors: Wang Yingying , Sibaii Fatima , Custead Rebecca , Oh Hyuntaek , Barlow Steven M. 
Published: November 2019

AbstractThe cortical representation of orofacial pneumotactile stimulation involves a complex network, which is still unknown. This study aims to identify the characteristics of functional connectivity (FC) elicited by different saltatory velocities over the perioral and buccal surface of the lower face using functional magnetic resonance imaging (fMRI) in twenty neurotypical adults. Our results showed 25 cm/s evoked more functional coupling in the right hemisphere, suggesting 25 cm/s might be optimal velocity if bilateral brain damages occur. The decreased FC between the right secondary somatosensory cortex and right posterior parietal cortex for 5 cm/s versus All-on showed that the relatively slow velocity evoked less coupling in the ipsilateral hemisphere, which suggesting functional coupling in the contralateral hemisphere is in charge of orofacial tactile perception of velocity. The increased FC between the right thalamus and bilateral secondary somatosensory cortex for 65 cm/s versus All-on indicated that the neural encoding of relatively fast tactile velocity is more coupling between the right thalamus and bilateral secondary somatosensory cortex. Our results have shown different characteristics of FC for each seed at various velocity contrasts (5 > 25 cm/s, 5 > 65 cm/s, and 25 > 65 cm/s), suggesting the neuronal networks encoding the orofacial tactile perception of velocity. The difference of functional connectivity among three velocities may indicate the optimal stimulation setting for better therapeutic effects on stroke recovery.
Functional connectome analyses reveal a highly optimized human olfactory network
Authors: Arnold T. Campbell , You Yuqi , Ding Mingzhou , Zuo Xi-Nian , de Araujo Ivan , Li Wen 
Published: November 2019

AbstractThe olfactory system is uniquely heterogeneous, performing multifaceted functions (beyond basic sensory processing) across diverse, widely distributed neural substrates. While knowledge of human olfaction continues to grow, it remains unclear how the olfactory network is organized to serve this unique set of functions. Leveraging a large and high-quality resting-state functional magnetic resonance imaging (rs-fMRI) dataset of nearly 900 participants from the Human Connectome Project (HCP), we identified a human olfactory network encompassing cortical and subcortical regions across the temporal and frontal lobes. Highlighting its reliability and generalizability, the connectivity matrix of this olfactory network mapped closely onto that extracted from an independent rs-fMRI dataset. Graph theoretical analysis further explicated the organizational principles of the network. The olfactory network exhibits a functionally advantageous modular composition of three (i.e., thesensory,limbic, andfrontal) subnetworks and demonstrates strong small-world properties, high in both global integration and local segregation (i.e., circuit specialization). This network organization thus ensures the segregation of local circuits, which are nonetheless integrated via connecting hubs (i.e., amygdala and anterior insula), thereby enabling the specialized, yet integrative, functions of olfaction. In particular, the degree of local segregation positively predicted olfactory discrimination performance in the independent sample. In sum, an olfactory functional network has been identified through the large HCP dataset, affording a representative template of the human olfactory functional neuroanatomy. Importantly, the topological analysis of the olfactory network provides network-level insights into the remarkable functional specialization and spatial segregation of the olfactory system.Significance StatementOlfaction is an intriguing multifunctional system, playing key roles in regulating emotions, autonomic tone, and feeding, beyond basic sensory perception. However, it is unclear how the neuroanatomy of olfaction is organized in humans to subserve these functions. Functional connectivity analysis of the HCP dataset combined with graph theoretical analysis revealed an optimized large-scale network consisting of three subnetworks—the sensory, limbic, and frontal subnetworks. Distributed across frontal and temporal lobes in well segregated fashion, these olfactory structures are also highly integrated, linked through hub nodes of the amygdala and anterior insula. Our independent dataset replicated the HCP-derived olfactory network and, importantly, highlighted a direct association between the degree of network segregation and olfactory perception.
Effects of technical noise on bulk RNA-seq differential gene expression inference
Authors: Sheerin Dylan , O’Connor Daniel , Pollard Andrew J , Mohorianu Irina 
Published: November 2019

AbstractMotivationInconsistent, analytical noise introduced either by the sequencing technology or by the choice of read-processing tools can bias bulk RNA-seq analyses by shifting the focus to the variation in expression of low-abundance transcripts; as a consequence these highly-variable genes are often included the differential expression (DE) call and impact the interpretation of results.ResultsTo illustrate the effects of “noise”, we present simulated datasets following closely the characteristics of aH.sapiensand aM.musculusdataset, respectively, highlighting the extent of technical-noise in both a high inter-individual variability (H. sapiens) and reduced variability (M. Musculus) setup. The sequencing-induced noise is assessed using correlations of distributions of expression across transcripts; analytical noise is evaluated through side-by-side comparisons of several standard choices. The proportion of genes in the noise-range differs for each tool combi-nation. Data-driven, sample-specific noise-thresholds were applied to reduce the impact of low-level variation. Noise-adjustment reduced the number of significantly DE genes and gave rise to convergent calls across tool combinations.AvailabilityThe code for determining the sequence-derived noise is available for download from:https://github.com/yry/noiseAnalysis/tree/master/noiseDetection_mRNA; the code for running the analysis is available for download from:https://github.com/sheerind/noise_detection.
Muscle synergies are associated with intermuscular coherence in an isometric upper limb task
Authors: Ortega-Auriol Pablo , Byblow Winston D , McMorland Angus JC 
Published: November 2019

AbstractTo elucidate the underlying physiological mechanism of muscle synergies, we investigated the functional corticomuscular and intermuscular binding during an isometric upper limb task in 14 healthy participants. Cortical activity was recorded using 32-channel encephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorization (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy preferred directions. A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Functional connectivity was estimated using corticomuscular coherence (CMC) and intermuscular coherence (IMC). Overall, we were able to extract four different synergies from the multidirectional task. A significant alpha band IMC was present consistently in all extracted synergies. Moreover, alpha band IMC was higher between muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. In addition, there is a relationship between a synergy muscle weight and the level of IMC. Our findings suggest the existence of a consistent shared input between muscles of each synergy. Finally, the existence of a shared input onto synergistic muscles within a synergy supports the idea of neurally-derived muscle synergies that build human movement.
Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database
Authors: Jones Briony A. , Goodall Tim , George Paul B.L. , Gweon Soon , Puissant Jeremy , Read Daniel , Emmett Bridget A. , Robinson David A. , Jones Davey L. , Griffiths Robert I. 
Published: November 2019

AbstractHigh-throughput sequencing 16S rRNA gene surveys have enabled new insights into the diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances across landscapes. However, current analytical approaches are of limited use in formalising syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are typically unique to individual studies and sequence identification databases only characterise taxonomy. To address this, we used sequences obtained from a large nationwide soil survey (GB Countryside Survey, henceforth “CS”) to create a comprehensive soil specific 16S reference database, with coupled ecological information derived from the survey metadata. Specifically, we modelled taxon responses to soil pH at the OTU level using hierarchical logistic regression (HOF) models, to provide information on putative landscape scale pH-abundance responses. We identify that most of the soil OTUs examined exhibit predictable abundance responses across soil pH gradients, though with the exception of known acidophilic lineages, the pH optima of OTU relative abundance was variable and could not be generalised by broad taxonomy. This highlights the need for tools and databases to predict ecological traits at finer taxonomic resolution. We further demonstrate the utility of the database by testing against geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and accuracy in predicting pH responses of query sequences from a separate large soil survey. We found that the CS database provided good coverage of dominant taxa; and that the taxa indicating soil pH in a query dataset corresponded with the pH classifications of top matches in the CS database. Furthermore we were able to predict query dataset community structure, using predicted abundances of dominant taxa based on query soil pH data and the HOF models of matched CS database taxa. The database with associated HOF model outputs is released as an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-TaxER), and as a DADA2 database for use in bioinformatics pipelines. The further development of advanced informatics infrastructures incorporating modelled ecological attributes along with new functional genomic information will likely facilitate large scale exploration and prediction of soil microbial functional biodiversity under current and future environmental change scenarios.
A precision medicine approach uncovers a unique signature of neutrophils in patients with brushite kidney stones
Authors: Makki Mohammad Shahidul , Winfree Seth , Lingeman James E. , Witzmann Frank , Worcester Elaine M. , Krambeck Amy , Coe Fred , Evan Andrew P. , Bledsoe Sharon , Bergsland Kristin , Khochare Suraj , Barwinska Daria , Williams James C. , El-Achkar Tarek M. 
Published: November 2019

AbstractBackgroundWe have previously found that papillary histopathology differs greatly between calcium oxalate and brushite stone formers (SF); the latter have much more papillary mineral deposition, tubular cell injury and tissue fibrosis.MethodsIn this study, we applied unbiased orthogonal “omics” approaches on biopsied renal papillae and extracted stones from patients with brushite or calcium oxalate (CaOx) stones. Our goal was to discover stone type-specific molecular signatures to advance our understanding of the underlying pathogenesis.ResultsBrushite SF did not differ from CaOx SF with respect to metabolic risk factors for stones, but did exhibit increased tubule plugging in their papillae. Brushite SF had upregulation of inflammatory pathways in papillary tissue, and increased neutrophil markers in stone matrix compared to those with CaOx stones. Large-scale 3D tissue cytometry on renal papillary biopsies showed an increase in the number and density of neutrophils in the papillae of brushite vs. CaOx patients, thereby linking the observed inflammatory signatures to the neutrophils in the tissue. To explain how neutrophil proteins appear in the stone matrix, we measured neutrophil extracellular trap (NET) formation, NETosis, and found it significantly increased in the papillae of brushite compared to CaOx patients.ConclusionsWe show that increased neutrophil infiltration and NETosis is an unrecognized factor that differentiates brushite and CaOx SF, and may explain the markedly increased scarring and inflammation seen in the papillae of brushite patients. Given the increasing prevalence of brushite stones, the role of neutrophil activation in brushite stone formation requires further study.
A scalable random walk with restart on heterogeneous networks with Apache Spark for ranking disease-causing genes using type-2 fuzzy data fusion
Authors: Joodaki Mehdi , Ghadiri Nasser , Maleki Zeinab , Shahreza Maryam Lotfi 
Published: November 2019

AbstractPrediction and discovery of disease-causing genes are among the main missions of biology and medicine. In recent years, researchers have developed several methods based on gene/protein networks for the detection of causative genes. However, because of the presence of false positives in these networks, the results of these methods often lack accuracy and reliability. This problem can be solved by using multiple genomic sources to reduce noise in data. However, network integration can also affect the quality of the integrated network. In this paper, we present a method named RWRHN (random walk with restart on a heterogeneous network) with fuzzy fusion or RWRHN-FF. In this method, first, four gene-gene similarity networks are constructed based on different genomic sources and then integrated using the type-II fuzzy voter scheme. The resulting gene-gene network is then linked to a disease-disease similarity network, which itself is constructed by the integration of four sources, through a two-part disease-gene network. The product of this process is a reliable heterogeneous network, which is analyzed by the RWRHN algorithm. The results of the analysis with the leave-one-out cross-validation method show that RWRHN-FF outperforms both RWRHN and RWRH. The proposed method is used to predict new genes for prostate, breast, gastric and colon cancers. To reduce the algorithm run time, Apache Spark is used as a platform for parallel execution of the RWRHN algorithm on heterogeneous networks. In the test conducted on heterogeneous networks of different sizes, this solution results in faster convergence than other non-distributed modes of implementations.
A complete time-calibrated multi-gene phylogeny of the European butterflies
Authors: Wiemers Martin , Chazot Nicolas , Wheat Christopher W. , Schweiger Oliver , Wahlberg Niklas 
Published: November 2019

AbstractWith the aim of supporting ecological analyses in butterflies, the third most species-rich superfamily of Lepidoptera, this paper presents the first time-calibrated phylogeny of all 496 extant butterfly species in Europe, including 18 very localized endemics for which no public DNA sequences had been available previously. It is based on a concatenated alignment of the mitochondrial gene COI and up to 11 nuclear gene fragments, using Bayesian inference of phylogeny. To avoid analytical biases that could result from our region-focus sampling, our European tree was grafted upon a global genuslevel backbone butterfly phylogeny for analyses. In addition to a consensus tree, we provide the posterior distribution of trees and the fully-concatenated alignment for future analyses.
A representational asymmetry for composition in the human left-middle temporal gyrus
Authors: Frankland Steven M. , Greene Joshua D. 
Published: November 2019

AbstractNatural language is notable amongst representational systems for the rich internal structure of phrase and sentence-level expressions. Here, we provide evidence from two fMRI studies that a region of the left Middle Temporal Gyrus (MTG) exhibits a surprising representational asymmetry: verbs and patients (to whom was it done?) are bound to form a representation, but verbs and agents (who did it?) are not. Within MTG, BOLD signal to novel combinations of familiar components can be modeled by combining learned verb-patient conjunctive representations with more general agent representations, but not by the converse (verb-agent + patient). This asymmetry is not predicted by an abstract propositional representation of the event (e.g., chased(dog,cat), nor by a theory which derives conjunctions from the experienced statistical co-occurences between verbs and nouns. However, this asymmetry is predicted by various linguistic accounts of the internal structure of event descriptions (e.g., Williams, 1981; Marantz,1984; Grimshaw, 1990; Kratzer, 1996). These results provide evidence for the time-varying instantiation of re-usable representations of structure in MTG, consistent with the principle of compositionality, as well as accounts of verb-argument structure.
Enhancers predominantly regulate gene expression in vivo via transcription initiation
Authors: Larke Martin S. C. , Nojima Takayuki , Telenius Jelena , Sharpe Jacqueline A. , Sloane-Stanley Jacqueline A. , Butler Sue , Beagrie Robert A. , Downes Damien J. , Schwessinger Ron , Marieke Oudelaar A. , Truch Julia , Crompton Bryony , Bender M. A. , Proudfoot Nicholas J. , Higgs Douglas R. , Hughes Jim R. 
Published: November 2019

ABSTRACTGene transcription occurs via a cycle of linked events including initiation, promoter proximal pausing and elongation of RNA polymerase II (Pol II). A key question is how do transcriptional enhancers influence these events to control gene expression? Here we have used a new approach to quantify transcriptional initiation and pausing in vivo, while simultaneously identifying transcription start sites (TSSs) and pause-sites (TPSs) from single RNA molecules. When analyzed in parallel with nascent RNA-seq, these data show that differential gene expression is achieved predominantly via changes in transcription initiation rather than Pol II pausing. Using genetically engineered mouse models deleted for specific enhancers we show that these elements control gene expression via Pol II recruitment and/or initiation rather than via promoter proximal pause release. Together, our data show that enhancers, in general, control gene expression predominantly by Pol II recruitment and initiation rather than via pausing.
ESI mutagenesis: A one-step method for introducing point mutations into bacterial artificial chromosome transgenes
Authors: Rondelet Arnaud , Pozniakovsky Andrei , Leuschner Marit , Poser Ina , Ssykor Andrea , Berlitz Julian , Schmidt Nadine , Hyman Anthony A , Bird Alexander W 
Published: November 2019

AbstractBacterial artificial chromosome (BAC)-based transgenes have emerged as a powerful tool for controlled and conditional interrogation of protein function in higher eukaryotes. While homologous recombination-based recombineering methods have streamlined the efficient integration of protein tags onto BAC transgenes, generating precise point mutations has remained less efficient and time-consuming. Here we present a simplified method for inserting point mutations into BAC transgenes requiring a single recombineering step followed by antibiotic selection. This technique, which we call ESI (Exogenous/Synthetic Intronization) mutagenesis, relies on co-integration of a mutation of interest along with a selectable marker gene, the latter of which is harboured in an artificial intron adjacent to the mutation site. Cell lines generated from ESI-mutated BACs express the transgenes equivalently to the endogenous gene, and all cells efficiently splice out the synthetic intron. Thus, ESI-mutagenesis provides a robust and effective single-step method with high precision and high efficiency for mutating BAC transgenes.
Neural dysfunction correlates with heat coma and CTmax in Drosophila but does not set the boundaries for heat stress survival
Authors: Jørgensen Lisa B. , Meldrum Robertson R. , Overgaard Johannes 
Published: November 2019

AbstractWhen heated, insects loose coordinated movement followed by the onset of heat coma (CTmax). These phenotypes are popular measures to quantify inter- and intraspecific differences in insect heat tolerance, and CTmax correlate well with current species distributions. Here we examined the function of the central nervous system (CNS) in five species of Drosophila with different heat tolerances, while they were exposed to either constant high temperature or a gradual increasing temperature (ramp). Tolerant species were able to preserve CNS function at higher temperatures and for longer durations than sensitive species and similar differences were found for the behavioral indices (loss of coordination and onset of heat coma). Furthermore, the timing and temperature (constant and ramp exposure, respectively) for loss of coordination or complete coma coincided with the occurrence of spreading depolarisation (SD) events in the CNS. These SD events disrupt neurological function and silence the CNS suggesting that CNS failure is the primary cause of impaired coordination and heat coma. Heat mortality occurs soon after heat coma in insects and to examine if CNS failure could also be the proximal cause of heat death, we used selective heating of the head (CNS) and abdomen (visceral tissues). When comparing the temperature causing 50% mortality (LT50) of each body part to that of the whole animal, we found that the head was not particularly heat sensitive compared to the abdomen. Accordingly, it is unlikely that nervous failure is the principal/proximate cause of heat mortality in Drosophila.Summary statementHyperthermic failure of the Drosophila central nervous system causes heat coma, a phenotype varying in temperature between drosophilids, but neural failure is likely not the primary cause of heat mortality.