bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep coverage microscopy exposes a pharmacological window for modifiers of neuronal network connectivity
Authors: Verschuuren Marlies , Verstraelen Peter , Garcia Gerardo , Cilissen Ines , Coninx Emma , Verslegers Mieke , Larsen Peter , Nuydens Rony , De Vos Winnok H. 
Published: February 2019

AbstractBackgroundTherapeutic developments for neurodegenerative disorders are redirecting their focus to the mechanisms that contribute to synaptic plasticity and the loss thereof. Identification of novel regulators requires a method to quantify neuronal network connectivity with high accuracy and throughput. To meet this demand, we have established a microscopy-based pipeline that integrates morphological and functional correlates of connectivity in primary neuronal culture.ResultsWe unveiled a connectivity signature that was specific to the cell type and culture age. We defined a score that accurately reports on the degree of neuronal connectivity and we validated this score by targeted perturbation of microtubule stability and selective depletion of anti-oxidants. With a focused compound screen, we discovered that inhibition of dual leucine zipper kinase activity increased neuronal connectivity in otherwise unperturbed cultures and exerted neuroprotective effects in cultures grown under sub-optimal or challenged conditions.ConclusionsOur results illustrate that profiling microscopy images with deep coverage enables sensitive interrogation of neuronal connectivity and allows exposing a dose and time window for pharmacological interventions. Therefore, the current approach holds promise for identifying pathways and compounds that preserve or rescue neuronal connectivity in neurodegenerative disorders.
Depth-dependent PSF calibration and aberration correction for 3D single-molecule localization
Authors: Li Yiming , Wu Yu-Le , Hoess Philipp , Mund Markus , Ries Jonas 
Published: February 2019

Abstract3D Single molecule localization microscopy relies on fitting of the individual molecules with a point spread function (PSF) model. The reconstructed images often show local squeezing or expansion in z. A common cause are depth-induced aberrations in conjunction with an imperfect PSF model calibrated from beads on a coverslip, resulting in a mismatch between measured PSF and real PSF. Here, we developed a strategy for accurate z-localization in which we use the imperfect PSF model for fitting, determine the fitting errors and correct for them in a post-processing step. We present an open-source software tool and a simple experimental calibration procedure that allow retrieving accurate z-positions in any PSF engineering approach or fitting modality, even at large imaging depths.
A novel human enteroid-anaerobe co-culture system to study microbial-host interaction under physiological hypoxia
Authors: Fofanova TY , Stewart CJ , Auchtung JM , Wilson RL , Britton RA , Grande-Allen KJ , Estes MK , Petrosino JF 
Published: February 2019

AbstractMechanistic investigations of host-microbe interactions in the human gut are limited by current co-culture model systems. The intestinal epithelium requires oxygen for viability, while gut bacteria are facultative or obligate anaerobes. The ability to model host-commensal interactions under dynamic oxygen conditions is critical to understanding host-pathogen interactions in the human gut. Here, we demonstrate a simple, cost-effective method for co-culturing obligate anaerobic bacteria with human intestinal enteroid monolayers under variable oxygen conditions. The Enteroid-Anaerobe Co-Culture (EACC) system is able to recapitulate the steep oxygen gradient seenin vivoand induce expression of hypoxia-associated phenotypes such as increased barrier integrity and expression of antimicrobial peptide genes. Using clinical strains of the commensal anaerobesBacteroides thetaiotaomicronandBlautiasp. on established patient-derived intestinal enteroid cell lines under physiological hypoxia, the EACC system can sustain host-anaerobe interactions for at least 24 hours. Following co-culture with anaerobic bacteria, we demonstrate patient-specific differences in epithelial response, reinforcing the potential to develop a personalized medicine approach to bacteriotherapy and host-microbe interaction investigations. Our innovative EACC system provides a robust model for investigating host-microbe interactions in complex, patient-derived intestinal tissues, that facilitates study of mechanisms underlying the role of the microbiome in health and disease.
Model-based integration of genomics and metabolomics reveals SNP functionality in Mycobacterium tuberculosis
Authors: Øyås Ove , Borrell Sonia , Trauner Andrej , Zimmermann Michael , Feldmann Julia , Gagneux Sebastien , Stelling Jörg , Sauer Uwe , Zampieri Mattia 
Published: February 2019

AbstractHuman tuberculosis is caused by members of the Mycobacterium tuberculosis complex (MTBC) and presents variable disease outcomes. The variation has primarily been attributed to host and environmental factors, but recent evidence indicates an additional role of genetic diversity among MTBC clinical strains. Here, we used metabolomics to unravel the potential role of genetic variations in conferring strain-specific adaptive capacity and vulnerability. To systematically identify functionality of single nucleotide polymorphisms (SNPs), we developed a constraint-based approach that integrates metabolomic and genomic data. Model-based predictions were systematically tested against independent metabolome data; they correctly classified SNP effects in pyruvate kinase and suggested a genetic basis for strain-specific sensitivity to the antibiotic para-aminosalicylic acid. Our method is broadly applicable to mutations in enzyme-encoding genes across microbial life, opening new possibilities for identifying strain-specific metabolic vulnerabilities that could lead to more selective treatment strategies.
A Recurrent Neural Network Model for Flexible and Adaptive Decision Making based on Sequence Learning
Authors: Zhang Zhewei , Cheng Huzi , Yang Tianming 
Published: February 2019

AbstractThe brain makes flexible and adaptive responses in the complicated and ever-changing environment for the organism’s survival. To achieve this, the brain needs to choose appropriate actions flexibly in response to sensory inputs. Moreover, the brain also has to understand how its actions affect future sensory inputs and what reward outcomes should be expected, and adapts its behavior based on the actual outcomes. A modeling approach that takes into account of the combined contingencies between sensory inputs, actions, and reward outcomes may be the key to understanding the underlying neural computation. Here, we train a recurrent neural network model based on sequence learning to predict future events based on the past event sequences that combine sensory, action, and reward events. We use four exemplary tasks that have been used in previous animal and human experiments to study different aspects of decision making and learning. We first show that the model reproduces the animals’ choice and reaction time pattern in a probabilistic reasoning task, and its units’ activities mimics the classical findings of the ramping pattern of the parietal neurons that reflects the evidence accumulation process during decision making. We further demonstrate that the model carries out Bayesian inference and may support meta-cognition such as confidence with additional tasks. Finally, we show how the network model achieves adaptive behavior with an approach distinct from reinforcement learning. Our work pieces together many experimental findings in decision making and reinforcement learning and provides a unified framework for the flexible and adaptive behavior of the brain.
Murburn concept explains the acutely lethal effect of cyanide
Authors: Manoj Kelath Murali , Ramasamy Surjith , Parashar Abhinav , Soman Vidhu , Pakshirajan Kannan 
Published: February 2019

AbstractCyanide (CN) toxicity is traditionally understood to result from its binding of hemeFe centers, thereby disrupting mitochondrial cytochrome oxidase function and oxygen utilization by other globin proteins. Recently, a diffusible reactive oxygen species (DROS) mediated reaction mechanism called murburn concept was proposed to explain mitochondrial ATP-synthesis and heat generation. Per this purview, it was theorized that CN ion-radical equilibrium dissipates the catalytically vital DROS into futile cycles, producing water. In the current study, a comparative quantitative assessment of the above two explanations is made for: (i) lethal dosage or concentrations of CN, (ii) thermodynamics and kinetics of the binding/reaction, and (iii) correlation of CN with the binding data and reaction chemistry of H2S/CO. The quantitative findings suggest that the hemeFe binding-based toxicity explanation is untenable. CN also inhibited the experimentalin vitroDROS-mediated coupling of inorganic phosphate with ADP. Further, pH-dependent inhibition profiles of heme enzyme catalyzed oxidation of a phenolic (wherein an -OH group reacts with DROS to form water, quite akin to the murburn model of ATP synthesis) indicated that- (i) multiple competitive reactions in milieu controlled outcomes and (ii) low concentrations of CN cannot disrupt activity via a coordination (binding) of cyanide at the distal hemeFe. Therefore, the μM-level IC50and the acutely lethal effect of CN on cellular respiration could be explained by the deleterious interaction of CN ion-radical equilibrium with DROS in matrix, disrupting mitochondrial ATP synthesis. This work supports the murburn explanation for cellular respiration.
TMS-EEG signatures of glutamatergic neurotransmission in human cortex
Authors: König Franca , Belardinelli Paolo , Liang Chen , Desideri Debora , Müller-Dahlhaus Florian , Gordon Pedro Caldana , Zipser Carl , Zrenner Christoph , Ziemann Ulf 
Published: February 2019

AbstractNeuronal activity in the brain is regulated by an excitation-inhibition balance. Glutamate is the main excitatory neurotransmitter. Transcranial magnetic stimulation (TMS) evoked electroencephalographic (EEG) potentials (TEPs) represent a novel way to quantify pharmacological effects on neuronal activity in the human cortex. Here we tested TEPs under the influence of a single oral dose of two anti-glutamatergic drugs, perampanel, an AMPA-receptor antagonist, and dextromethorphan, an NMDA-receptor antagonist, and nimodipine, an L-type voltage-gated calcium channel blocker in 16 healthy adults in a pseudorandomized, double-blinded, placebo-controlled, crossover design. Single-pulse TMS was delivered to the left motor cortex and TEPs were obtained pre-and post-drug intake. Dextromethorphan specifically increased the amplitude of the N45, a negative potential around 45 ms after the TMS pulse, while perampanel reduced the P70 amplitude in the non-stimulated hemisphere. Nimodipine and placebo had no effect on TEPs. These data extend previous pharmaco-TMS-EEG studies by demonstrating that the N45 is regulated by a balance of GABAAergic inhibition and NMDA-receptor-mediated glutamatergic excitation. In contrast, AMPA-receptor-mediated glutamatergic neurotransmission contributes to interhemispherically propagated activity reflected in the P70. These data are important to understand the physiology of TEPs as markers of excitability and propagated activity in the human cortex in health and disease.
Ancient whole genome duplications and the evolution of the gene duplication and loss rate
Authors: Zwaenepoel Arthur , Van de Peer Yves 
Published: February 2019

AbstractGene tree - species tree reconciliation methods have been employed for studying ancient whole genome duplication (WGD) events across the eukaryotic tree of life. Most approaches have relied on using maximum likelihood trees and the maximum parsimony reconciliation thereof to count duplication events on specific branches of interest in a reference species tree. Such approaches do not account for uncertainty in the gene tree and reconciliation, or do so only heuristically. The effects of these simplifications on the inference of ancient WGDs are unclear. In particular the effects of variation in gene duplication and loss rates across the species tree have not been considered. Here, we developed a full probabilistic approach for phylogenomic reconciliation based WGD inference, accounting for both gene tree and reconciliation uncertainty using a method based on the principle of amalgamated likelihood estimation. The model and methods are implemented in a maximum likelihood and Bayesian setting and account for variation of duplication and loss rate across the species tree, using methods inspired by phylogenetic divergence time estimation. We applied our newly developed framework to ancient WGDs in land plants and investigate the effects of duplication and loss rate variation on reconciliation and gene count based assessment of these earlier proposed WGDs.
Structural Insights into Hearing Loss Genetics from Polarizable Protein Repacking
Authors: Tollefson M. R. , Litman J. M. , Qi G. , Marini R. J. , O’Connell C. E. , Wipfler M. J. , Bernabe H. V. , Tollefson W. T. A. , Casavant T. L. , Braun T. A. , Smith R. J. H. , Schnieders M. J. 
Published: February 2019

AbstractHearing loss is associated with ~8100 mutations in 152 genes, and within the coding regions of these genes are over 60,000 missense variants. The majority of these variants are classified as ‘variants of uncertain significance’ to reflect our inability to ascribe a phenotypic effect to the observed amino acid change. A promising source of pathogenicity information are atomic resolution simulations, although input protein structures often contain defects due to limitations in experimental data and/or only distant homology to a template. Here we combine the polarizable AMOEBA force field, many-body optimization theory and GPU acceleration to repack all deafness-associated proteins and thereby improve average structure resolution from 2.2 Å to 1.0 Å based on assessment with MolProbity. We incorporate these data into the Deafness Variation Database to inform deafness pathogenicity prediction, and show that advanced polarizable force fields could now be used to repack the entire human proteome using the Force Field X software.
Estimating the abundance of duiker (Cephalophus spp.) populations in African rainforests: an overview of relevant methods
Authors: Entanga Elenga Gaius Bolumbu , Gaillard Jean-Michel , Musibono Dieudonné Eyul’Anki , Bibula Ifuta Séraphin Ndey , Bonenfant Christophe 
Published: February 2019

AbstractDuikers are among the most sought after antelope species for bush meat in central Africa. Estimates of population abundance of duikers based on reliable methods is therefore of prime importance for their sustainable management. Here we retrieved 31 studies from the literature and compared methods used to estimate the abundance of duiker populations in African rainforests. Implemented methods all derived from seven main combinations of sampling designs and population abundance estimators. We then evaluated the relevance of those seven methods by scoring them based on eight criteria selected according to their pros and cons reported in the litterature for large-scale population management of wildlife. For management purposes, methods derived from distance sampling offer the best compromise between the implementation costs and the biological information collected. In particular, both diurnal and nocturnal distance sampling can be recommended. Hunter calls and drive-netting are less reliable, but can be used in association with other measurements in the framework of indicators of ecological changes, a monitoring approach that has been successfully used in temperate ecosystems for managing large herbivores.Funding informationMinistère de l’Environnement et du Développement Durable de la République Démocratique du Congo, Campus France and Centre National de la Recherche Scientifique (CNRS).RésuméLes céphalophes sont parmi les espèces d’antilopes les plus recherchées pour la viande de brousse en Afrique centrale. L’estimation de l’abondance des populations de céphalophes revêt donc une importance primordiale pour leur gestion durable et adaptative. Nous avons extrait 31 études de la littérature et comparé les méthodes utilisées pour estimer l’abondance des populations de céphalophes dans les forêts tropicales africaines. Les méthodes employées dérivent de sept combinaisons principales de plans d’échantillonnage et d’estimateurs d’abondance. Nous avons évalué la pertinence de ces sept méthodes sur la base de critères sélectionnés en fonction de leurs avantages et inconvénients pour une gestion à grande échelle de la population. Les méthodes dérivées de l’échantillonnage par distance offrent le meilleur compromis entre les coûts de mise en œuvre et les informations biologiques collectées. Les méthodes d’échantillonnage diurne et nocturne se sont montrées les plus satisfaisantes. Les méthodes d’appel par les chasseurs et de battue au filet sont moins fiables, mais peuvent être utilisées en association avec d’autres mesures biologiques comme indicateurs de changements écologiques, une approche qui a été utilisée avec succès dans les écosystèmes tempérés pour la gestion des grands herbivores.Mots-clés:gestion durable, grands herbivores, indicateurs de changement écologique, méthode de recensement, viande de brousse
Orally consumed cannabinoids provide long-lasting relief of allodynia in a mouse model of chronic neuropathic pain
Authors: Leung Edward J.Y. , Abraham Antony D. , Wong Brenden A. , Kruse Lauren C. , Clark Jeremy J. , Land Benjamin B. 
Published: February 2019

AbstractChronic pain affects a significant percentage of the United States population, and available pain medications like opioids have drawbacks that make long-term use untenable. Cannabinoids show promise in the management of pain, but long-term treatment of pain with cannabinoids has been challenging to implement in preclinical models. We developed a voluntary, gelatin oral self-administration paradigm that allowed animals to consume Δ9-tetrahydrocannabinol, cannabidiol, or morphine ad libitum. Animals stably consumed these gelatins over 3 weeks, with detectable serum levels. We designed a real-time gelatin measurement system, and observed that mice consumed gelatin throughout the light and dark cycles, with THC-gelatin animals consuming less than the other groups. Consumption of all three gelatins reduced measures of allodynia in a chronic, neuropathic sciatic nerve injury model, but tolerance to morphine developed after one week while THC or CBD reduced allodynia over three weeks. Hyperalgesia took longer to develop after sciatic nerve injury, but by the last day of testing THC significantly reduced hyperalgesia responses, with a trend effect of CBD, and no effect of morphine. Mouse vocalizations were recorded throughout the experiment, and mice showed a large increase in ultrasonic, broadband clicks after sciatic nerve injury, which was reversed by both THC and CBD. This study demonstrates that mice will voluntarily consume both cannabinoids and opioids via gelatin, and that cannabinoids can provide long-term relief of chronic pain states. Additionally, ultrasonic clicks may objectively represent the pain status of a mouse and could be integrated into future pain models.
pyKNEEr: An image analysis workflow for open and reproducible research on femoral knee cartilage
Authors: Bonaretti Serena , Gold Garry E. , Beaupre Gary S. 
Published: February 2019

AbstractTransparent research in musculoskeletal imaging is fundamental to reliably investigate diseases such as knee osteoarthritis (OA), a chronic disease impairing femoral knee cartilage. To study cartilage degeneration, researchers have developed algorithms to segment femoral knee cartilage from magnetic resonance (MR) images and to measure cartilage morphology and relaxometry. The majority of these algorithms are not publicly available or require advanced programming skills to be compiled and run. However, to accelerate discoveries and findings, it is crucial to have open and reproducible workflows. We presentpyKNEEr, a framework for open and reproducible research on femoral knee cartilage from MR images.pyKNEEris written in python, uses Jupyter notebook as a user interface, and is available on GitHub with a GNU GPLv3 license. It is composed of three modules: 1) image preprocessing to standardize spatial and intensity characteristics, 2) femoral knee cartilage segmentation for intersubject, multimodal, and longitudinal acquisitions, and 3) analysis of cartilage morphology and relaxometry. Each module contains one or more Jupyter notebooks with narrative, code, visualizations, and dependencies to reproduce computational environments.pyKNEErfacilitates transparent image-based research of femoral knee cartilage because of its ease of installation and use, and its versatility for publication and sharing among researchers. Finally, due to its modular structure,pyKNEErfavors code extension and algorithm comparison. We tested our reproducible workflows with experiments that also constitute an example of transparent research withpyKNEEr. We provide links to executed notebooks and executable environments for immediate reproducibility of our findings.
Adult emergence order in a community of cavity-nesting bees and wasps, and their parasites
Authors: MacIvor J Scott 
Published: February 2019

AbstractEvaluating resource use and overlap through time and space among and within species having similar habitat requirements informs community-level conservation and coexistence, efforts to monitor species at-risk and biological invasions. Many species share common nesting requirements; one example are cavity-nest bees and wasps, which provision nests in dark and dry holes in wood, plant stems, or other plant-based materials that can be bundled together into ‘trap nests’. In this study, the adult emergence order of 47 species of solitary cavity-nesting bees and wasps, and their parasites (total N>8000 brood cells) were obtained from two hundred identical trap nests set up each year (over three years) to survey these populations across Toronto, Canada and the surrounding region. All brood cells collected were reared in a growth chamber under constant warming temperature and humidity to determine species identity, and adult emergence order. This order ranged from 0 to 38 days, with all mason bees (Osmiaspp.) emerging within the first two days, and the invasive resin bee species,Megachile sculpturalisSmith significantly later than all others. Late emerging species i) exhibited significantly greater intraspecific variation in mean emergence day and ii) were significantly larger in body size, compared to early emerging species. Detailing natural history information at the species- and community-level, such as the adult emergence order of coexisting cavity-nesting bees and wasps and their parasites, can inform the timing of deployment of trap nests to support and monitor target species, and refine experimental design to study these easily-surveyed and essential insect communities.