bluuebunny/crossref_metadata_2025_split huggingface dataset:
The role of cultural norms in shaping attitudes towards amphibians in Cape Town, South Africa
Authors: Brom Peta , Anderson Pippin , Channing Alan , Underhill Leslie G. 
Published: June 2019

AbstractUrban ecosystems are increasingly viewed as an important component within strategies for wildlife conservation but are shaped as much by natural systems as they are by social and political processes. At the garden scale, attitudes and preferences govern design and maintenance choices including the decision to encourage or discourage specific faunal presence. At the global scale, charismatic taxa that are well-liked attract more conservation funding and volunteer stewardship. Amphibians are a class of animals that are both loved and loathed making them a suitable subject for comparing and unpacking the drivers of preference and attitudes towards animals. We conducted a mixed methods survey of 192 participants in three adjacent neighbourhoods in Cape Town, South Africa. The survey included both quantitative and qualitative questions which were analysed thematically and used to explain the quantitative results. The results revealed that attitudes formed during childhood tended to be retained into adulthood, were shaped by cultural norms, childhood experiences and the attitudes of primary care-givers. The findings are significant for environmental education programmes aimed at building connectedness to nature and biophilic values.
Damage-related changes in the cerebellum of juvenileOncorhynchus masou: reactivation of neurogenic niches and astrocytic response
Authors: Pushchina Eugenyia V. , Stukaneva Maryia E. , Varaksin Anatoly A. 
Published: June 2019

ABSTRACTIn the cerebellum of juvenileOncorhynchus masou, proliferating BrdU+ and HuCD+ cells and constitutive neurogenic niches were detected in different zones; the largest number of labeled cells were found in the dorsal part of the molecular layer and the dorsal matrix zone (DMZ). Cells labeled with glutamine synthetase (GS) and radial glia were also present in the intactO. masoucerebellum. The most intensive proliferation was detected in the rostral part of cerebellum. This part is assumed to contain active zones of constitutive neurogenesis. After an injury inflicted to the cerebellum, the number of BrdU+ and HuCD+ cells increased significantly. The number of BrdU+ cells after this type of injury was much greater than after a telencephalon trauma. A quantitative analysis revealed that after the cerebellum injury the proliferative activity in the caudal part of CCb is increased compared to that in the control. A reactivation of neurogenic and neuroepithelial niches and their transformation into reactive neurogenic domains, with an increased distribution density of intensely labeled HuCD+ cells of different types, were observed. The increase in the number of HuCD+ differentiated cells in the basal area suggests that the processes of neuronal differentiation are intensified in the cerebellum of juvenileO. masouafter injury. The number of GS positive cells (GS+) and fibers increased in all the zones of cerebellum. The most intensive astrocytic response was noted in the dorsal part of cerebellum. The data of the enzyme immunoassay confirm the multiple variations in the level of GS after a traumatic injury to cerebellum inO. masou.
The efficacy and safety ofMomordica charantiaL. in animal models of type 2 diabetes mellitus; A systematic review and meta-analysis
Authors: Peter Emanuel L. , Nagendrappa Prakash B. , Kaligirwa Anita , Ogwang Patrick Engeu , Sesaazi Crispin Duncan 
Published: June 2019

AbstractBackgroundMomordica charantiaL. (Cucurbitaceae) has been used to control hyperglycemia in people with type 2 diabetes mellitus in Asia, South America, and Africa for decades. However, a meta-analysis of clinical trials confirmed very low-quality evidence of its efficacy. To potentially increase the certainty of evidence, we evaluated the effect ofM. charantiaL. in comparison with vehicle on glycemic control in animal models of type 2 diabetes mellitus.MethodsReview authors searched in MEDLINE, Web of Science, Scopus, and CINAHL databases without language restriction through April 2019. Two authors independently evaluated full texts, assessed the risk of bias, and extracted data. We analyzed the influence of study design and evidence of publication bias.ResultsThe review included 66 studies involving 1861 animals. They had a follow up between 7 and 90 days. Majority 29 (43.9%) used Wistar albino rats, and 37 (56.1%) used male animals. Thirty-two (48%) used an aqueous extract of fresh fruits.M. charantiaL. reduced fasting plasma glucose (FPG) and glycosylated hemoglobin A1c in comparison to vehicle control (42 studies, 815 animals; SMD, −6.86 [95% CI; −7.95, −5.77], 3 studies, 59 animals; SMD; −7.76 [95%CI; −12.50, −3.01]) respectively. Magnitude of FPG was large in Wistar albino rat subgroup; SMD; −10.29, [95%CI; −12.55, −8.03]. Publication bias changed FPG to non-significant −2.46 SMD, [95%CI; - 5.10, 0.17]. We downgraded the evidence to moderate quality due to poor methodological quality, high risk of bias, unexplained heterogeneity, suspected publication bias, and lack of standardized dose.ConclusionM. charantiaL. lowers elevated plasma glucose level in type 2 diabetes mellitus animal models. Publication bias and poor methodological quality call for future researches to focus on standardizing dose with chemical markers and provide measures to improve preclinical type 2 diabetes mellitus studies.Systematic review registration CRD42019119181
A wake-active locomotion circuit depolarizes a sleep-active neuron to switch on sleep
Authors: Maluck Elisabeth , Busack Inka , Besseling Judith , Masurat Florentin , Turek Michal , Busch Karl Emanuel , Bringmann Henrik 
Published: June 2019

AbstractSleep-active neurons depolarize during sleep to suppress wakefulness circuits. Wake-active wake-promoting neurons in turn shut down sleep-active neurons, thus forming a bipartite flip-flop switch. However, how sleep is switched on is unclear because it is not known how wakefulness is translated into sleep-active neuron depolarization when the system is set to sleep. Using optogenetics in C. elegans, we solved the presynaptic circuit for depolarization of the sleep-active RIS neuron during developmentally-regulated sleep, also known as lethargus. Surprisingly, we found that RIS activation requires neurons that have known roles in wakefulness and locomotion behavior. The RIM interneurons, which are active during and can induce reverse locomotion, play a complex role and can act as inhibitors of RIS when they are strongly depolarized and as activators of RIS when they are modestly depolarized. The PVC command interneurons, which are known to promote forward locomotion during wakefulness, act as major activators of RIS. The properties of these locomotion neurons are modulated during lethargus. The RIMs become less excitable. The PVCs become resistant to inhibition and have an increased capacity to activate RIS. Separate activation of neither the PVCs nor the RIMs appears to be sufficient for sleep induction; instead, our data suggests that they act in concert to activate RIS. Forward and reverse circuit activity is normally mutually exclusive. Our data suggest that RIS may be activated at the transition between forward and reverse locomotion states, perhaps when both reverse (including RIM) and forward (PVC) circuit activity overlaps. While RIS is not strongly activated outside of lethargus, altered activity of the locomotion interneurons during lethargus favors strong RIS activation and thus sleep. The control of sleep-active neurons by locomotion circuits suggests that sleep may have evolved from locomotion quiescence. The flip-flop sleep switch in C. elegans thus requires an additional component, wake-active sleep-promoting neurons that translate wakefulness into the depolarization of a sleep-active neuron when the worm is sleepy. Wake-active sleep-promoting circuits may also be required for sleep state switching in other animals including in mammals.
Decoding task-specific cognitive states with slow, directed functional networks in the human brain
Authors: Sridharan Devarajan , Ajmera Shagun , Jain Hritik , Sundaresan Mali 
Published: June 2019

AbstractFlexible functional interactions among brain regions mediate critical cognitive functions. Such interactions can be measured from functional magnetic resonance imaging (fMRI) data with either instantaneous (zero-lag) or lag-based (time-lagged) functional connectivity; only the latter approach permits inferring directed functional interactions. Yet, the fMRI hemodynamic response is slow, and sampled at a timescale (seconds) several orders of magnitude slower than the underlying neural dynamics (milliseconds). It is, therefore, widely held that lag-based fMRI functional connectivity, measured with approaches like as Granger-Geweke causality (GC), provides spurious and unreliable estimates of underlying neural interactions. Experimental verification of this claim has proven challenging because neural ground truth connectivity is often unavailable concurrently with fMRI recordings. We address this challenge by combining machine learning with GC functional connectivity estimation. We estimated instantaneous and lag-based GC functional connectivity networks using fMRI data from 1000 participants, drawn from the Human Connectome Project database. A linear classifier, trained on either instantaneous or lag-based GC, reliably discriminated among seven different task and resting brain states, with over 80% cross-validation accuracy. With network simulations, we demonstrate that instantaneous and lag-based GC exploited interactions at fast and slow timescales, respectively, to achieve robust classification. With human fMRI data, instantaneous and lag-based GC identified distinct, cognitive core networks. Finally, variations in GC connectivity explained inter-individual variations in a variety of cognitive scores. Our findings show that instantaneous and lag-based methods reveal complementary aspects of functional connectivity in the brain, and suggest that slow, directed functional interactions, estimated with fMRI, provide robust markers of behaviorally relevant cognitive states.Author SummaryFunctional MRI (fMRI) is a leading, non-invasive technique for mapping networks in the human brain. Yet, fMRI signals are noisy and sluggish, and fMRI scans are acquired at a timescale of seconds, considerably slower than the timescale of neural spiking (milliseconds). Can fMRI, then, be used to infer dynamic processes in the brain such as the direction of information flow among brain networks? We sought to answer this question by applying machine learning to fMRI scans acquired from 1000 participants in the Human Connectome Project (HCP) database. We show that directed brain networks, estimated with a technique known as Granger-Geweke Causality (GC), accurately predicts individual subjects’ task-specific cognitive states inside the scanner, and also explains variations in a variety of behavioral scores across individuals. We propose that directed functional connectivity, as estimated with fMRI-GC, is relevant for understanding human cognitive function.
Drosophila insulin-like peptide 2mediates dietary regulation of sleep intensity
Authors: Brown Elizabeth B. , Shah Kreesha D. , Faville Richard , Kottler Benjamin , Keene Alex C. 
Published: June 2019

AbstractSleep is a nearly universal behavior that is regulated by diverse environmental and physiological stimuli. A defining feature of sleep is a homeostatic rebound following deprivation, where animals compensate for lost sleep by increasing sleep duration and/or sleep depth. Fruit flies exhibit robust recovery sleep following deprivation and represent a powerful model to study neural circuits regulating sleep homeostasis. Numerous neuronal populations have been identified in modulating sleep homeostasis as well as depth, raising the possibility that recovery sleep is differentially regulated by environmental or physiological processes that induce sleep deprivation. Here, we find that unlike most pharmacological and environmental manipulations commonly used to restrict sleep, starvation potently induces sleep loss without a subsequent rebound in sleep duration or depth. We find that both starvation and a sucrose-only diet result in reduced metabolic rate and increased sleep depth, suggesting that dietary yeast protein is essential for normal sleep depth and homeostasis. Finally, we find thatDrosophila insulin like peptide2 (Dilp2) is required for starvation-induced changes in sleep depth without regulating the duration of sleep. Remarkably,Dilp2mutant flies require rebound sleep following sleep deprivation, suggestingDilp2underlies resilience to sleep loss. Together, these findings reveal innate resilience to starvation-induced sleep loss and identify distinct mechanisms that underlie starvation-induced changes in sleep duration and depth.Author SummarySleep is nearly universal throughout the animal kingdom and homeostatic regulation represents a defining feature of sleep, where animals compensate for lost sleep by increasing sleep over subsequent time periods. Despite the robustness of this feature, surprisingly little is known about how recovery-sleep is regulated in response to different types of sleep deprivation. Fruit flies provide a powerful model for investigating the genetic regulation of sleep, and like mammals, display robust recovery sleep following deprivation. Here, we find that unlike most stimuli that suppress sleep, sleep deprivation by starvation does not require a homeostatic rebound. These findings appear to be due to flies engaging in deeper sleep during the period of partial deprivation, suggesting a natural resilience to starvation-induced sleep loss. This unique resilience to starvation-induced sleep loss is dependent onDrosophila insulin-like peptide 2, suggesting a critical role for insulin signaling in regulating interactions between diet and sleep homeostasis.
Recently emerged and diverse lineages of Xanthomonas perforans have independently evolved through plasmid acquisition and homologous recombination originating from multiple Xanthomonas species
Authors: Newberry E. A. , Bhandari R. , Minsavage G.V. , Timilsina S. , Jibrin M. , Kemble J. , Sikora E. , Jones J.B. , Potnis N. 
Published: June 2019

AbstractXanthomonas perforans is the predominant pathogen responsible for bacterial leaf spot of tomato and X. euvesicatoria of pepper in the southeast United States. Previous studies have indicated significant changes in the X. perforans population collected from Florida tomato fields over the span of two decades including a shift in race, diversification into three genetic groups, and host range expansion to pepper. Recombination originating from X. euvesicatoria was identified as the primary factor driving the diversification of X. perforans in Florida. The aim of this study was to genetically characterize X. perforans strains that were isolated from tomato and pepper plants grown in Alabama and compare them to the previously published genomes available from GenBank. Surprisingly, a maximum likelihood phylogeny coupled with a Bayesian analysis of population structure revealed the presence of two novel genetic groups in Alabama, which each harbored a different transcription activation-like effector (TALE). While one TALE, avrHah1, was associated with adaptation of X. perforans to pepper, the other was identified as a new class within the avrBs3 family, designated here as pthXp1. Examination of patterns of homologous recombination between X. perforans and other closely related Xanthomonas spp. indicated that the lineages identified here emerged in part through recent recombination events originating from xanthomonads associated with diverse hosts of isolation. Our results also suggest that the evolution of pathogenicity to pepper has likely emerged independently within X. perforans and in one lineage, was associated with the recombination-mediated remodeling of the Xps type II secretion and TonB transduction systems.ImportanceThe emergence of novel pathogen lineages has important implications in the sustainability of genetic resistance as a disease management tool in agricultural ecosystems. In this study, we identified two novel lineages of X. perforans in Alabama. While one lineage was isolated from symptomatic pepper plants, confirming the host range expansion of X. perforans, the other lineage was isolated from tomato and acquired a novel transcription activation-like effector, pthXp1. Unlike AvrBs4, PthXp1overcomes Bs4-mediated resistance in tomato, indicating the evolution of this novel lineage towards fitness on this host. Our findings also show that different phylogenetic groups of the pathogen have experienced independent recombination events originating from multiple Xanthomonas species. This suggests a continuous gene flux between related xanthomonads associated with diverse plant hosts which results in the emergence of novel pathogen lineages and associated phenotypes, including host range expansion.
Deep Learning Interpretation of Echocardiograms
Authors: Ghorbani Amirata , Ouyang David , Abid Abubakar , He Bryan , Chen Jonathan H. , Harrington Robert A. , Liang David H. , Ashley Euan A. , Zou James Y. 
Published: June 2019

AbstractEchocardiography uses ultrasound technology to capture high temporal and spatial resolution images of the heart and surrounding structures and is the most common imaging modality in cardiovascular medicine. Using convolutional neural networks on a large new dataset, we show that deep learning applied to echocardiography can identify local cardiac structures, estimate cardiac function, and predict systemic phenotypes that modify cardiovascular risk but not readily identifiable to human interpretation. Our deep learning model, EchoNet, accurately identified the presence of pacemaker leads (AUC = 0.89), enlarged left atrium (AUC = 0.85), normal left ventricular wall thickness (AUC = 0.75), left ventricular end systolic and diastolic volumes(R2= 0.73 andR2= 0.68), and ejection fraction (R2= 0.48) as well as predicted systemic phenotypes of age (R2= 0.46), sex (AUC = 0.88), weight (R2= 0.56), and height (R2= 0.33). Interpretation analysis validates that EchoNet shows appropriate attention to key cardiac structures when performing human-explainable tasks and highlight hypothesis-generating regions of interest when predicting systemic phenotypes difficult for human interpretation. Machine learning on echocardiography images can streamline repetitive tasks in the clinical workflow, standardize interpretation in areas with insufficient qualified cardiologists, and more consistently produce echocardiographic measurements.
What is the test-retest reliability of common task-fMRI measures? New empirical evidence and a meta-analysis
Authors: Elliott Maxwell L. , Knodt Annchen R. , Ireland David , Morris Meriwether L. , Poulton Richie , Ramrakha Sandhya , Sison Maria L. , Moffitt Terrie E. , Caspi Avshalom , Hariri Ahmad R. 
Published: June 2019

AbstractIdentifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability to identify meaningful biomarkers is limited by measurement reliability; unreliable measures are unsuitable for predicting clinical outcomes. Measuring brain activity using task-fMRI is a major focus of biomarker development; however, the reliability of task-fMRI has not been systematically evaluated. We present converging evidence demonstrating poor reliability of task-fMRI measures. First, a meta-analysis of 90 experiments (N=1,008) revealed poor overall reliability (mean ICC=.397). Second, the test-retest reliabilities of activity in a priori regions of interest across 11 common fMRI tasks collected in the context of the Human Connectome Project (N=45) and the Dunedin Study (N=20) were poor (ICCs=.067-.485). Collectively, these findings demonstrate that common task-fMRI measures are not currently suitable for brain biomarker discovery or individual differences research. We review how this state of affairs came to be and highlight avenues for improving task-fMRI reliability.
Decoding of the other’s focus of attention by a temporal cortex module
Authors: Ramezanpour H. , Thier P. 
Published: June 2019

AbstractFaces attract the observer’s attention towards objects and locations of interest for the other, thereby allowing the two agents to establish joint attention. Previous work has delineated a network of cortical “patches” in the macaque cortex, processing faces, eventually also extracting information on the other’s gaze direction. Yet, the neural mechanism that links information on gaze direction, guiding the observer’s attention to the relevant object has remained elusive. Here we present electrophysiological evidence for the existence of a distinct “gaze-following patch (GFP)” with neurons that establish this linkage in a highly flexible manner. The other’s gaze and the object, singled out by the gaze, are linked only if this linkage is pertinent within the prevailing social context. The properties of these neurons establish the GFP as a key switch in controlling social interactions based on the other’s gaze.One Sentence SummaryNeurons in a “gaze-following patch” in the posterior temporal cortex orchestrate the flexible linkage between the other’s gaze and objects of interest to both, the other and the observer.