bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying “real-world” initiatives for knowledge translation tools: a case study of community-based physical activity programs for persons with physical disability in Canada
Authors: D’Urzo Katrina A , Man Kristiann E , Bassett-Gunter Rebecca L , Latimer-Cheung Amy E , Tomasone Jennifer R 
Published: September 2018

Abstract
“Real-world” initiatives represent an important source of information for evidence-based practice; however, accessing information about initiatives is often challenging. Casebooks are an innovative knowledge translation (KT) tool for researchers, practitioners, and end-users to address “research-to-implementation gaps” through sharing “real-world” experiences. Several casebooks have been published; yet, they remain inconsistent in their methodological approach for identifying “real-world” initiatives. The purpose of this project is to describe and apply systematic scoping study methods for the identification of “real-world” initiatives relevant for the development of KT tools. Specifically, systematic scoping study methods were developed to identify community-based physical activity (PA) programs for persons with physical disabilities across Canada. To identify PA programs, a search strategy was developed and included five distinct search approaches: (i) peer-reviewed literature databases, (ii) grey literature databases, (iii) customized Google search engines, (iv) targeted websites, and (v) consultation with content experts. Title screening and hand searching identified 478 potentially relevant PA programs. Full record review identified 72 PA programs that met KT tool criteria. The most comprehensive search approach was targeted websites, which identified 25 (35%) unique PA programs, followed by content experts (n = 12; 17%). Only four (5.6%) unique PA programs were identified via custom Google searching. No PA programs were uniquely identified through peer- or grey literature database searches. This study describes and applies a systematic scoping study methodology that serves as a basis for identifying and selecting “real-world” initiatives that are central to the development of evidence-based KT tools.
Inflammasomes: An Emerging Mechanism Translating Environmental Toxicant Exposure Into Neuroinflammation in Parkinson’s Disease
Authors: Anderson Faith L , Coffey Madeleine M , Berwin Brent L , Havrda Matthew C 
Published: September 2018

Abstract
Evidence indicates that complex gene-environment interactions underlie the incidence and progression of Parkinson’s disease (PD). Neuroinflammation is a well-characterized feature of PD widely believed to exacerbate the neurodegenerative process. Environmental toxicants associated with PD, such as pesticides and heavy metals, can cause cellular damage and stress potentially triggering an inflammatory response. Toxicant exposure can cause stress and damage to cells by impairing mitochondrial function, deregulating lysosomal function, and enhancing the spread of misfolded proteins. These stress-associated mechanisms produce sterile triggers such as reactive oxygen species (ROS) along with a variety of proteinaceous insults that are well documented in PD. These associations provide a compelling rationale for analysis of sterile inflammatory mechanisms that may link environmental exposure to neuroinflammation and PD progression. Intracellular inflammasomes are cytosolic assemblies of proteins that contain pattern recognition receptors, and a growing body of evidence implicates the association between inflammasome activation and neurodegenerative disease. Characterization of how inflammasomes may function in PD is a high priority because the majority of PD cases are sporadic, supporting the widely held belief that environmental exposure is a major factor in disease initiation and progression. Inflammasomes may represent a common mechanism that helps to explain the strong association between exposure and PD by mechanistically linking environmental toxicant-driven cellular stress with neuroinflammation and ultimately cell death.
Need for Thorough Standardization of CO2 Laser Evoked Potential Procedure
Authors: Tudor Katarina I. , Petravić Damir , Krbot Skorić Magdalena , Išgum Velimir 
Published: September 2018

Purpose:
The objective of this study was to determine normative values of laser evoked potentials and anthropometric correlations in a healthy middle-aged working population.

Methods:
In 51 subjects, CO2 laser stimulation was applied bilaterally onto dorsal surface of the feet, hands, and neck using constant duration of stimulus and beam diameter, changing just the intensity of stimulation. Amplitudes and latencies of the laser evoked potential negative–positive complex were recorded, and relationship with height, age and gender was statistically analyzed.

Results:
There was a significant correlation between the latencies obtained for feet, hands, and height. P2 amplitudes for feet, hands, and neck, and negative–positive pk-pk amplitudes for hands and neck correlated negatively with age. The values obtained did not differ significantly between male and female gender, except for N2 latencies for hands.

Conclusions:
Clinically useful reference values for laser evoked potentials in a healthy middle-aged population were provided, which are interesting from the physiological point of view.
Functional implications of impaired dynamic cerebral autoregulation in young healthy women; a comparative investigation
Authors: Labrecque Lawrence , Rahimaly Kevan , Imhoff Sarah , Paquette Myriam , Blanc Olivier Le , Malenfant Simon , Drapeau Audrey , Smirl Jonathan D. , Bailey Damian M. , Brassard Patrice 
Published: September 2018

ABSTRACTWomen exhibit higher prevalence of orthostatic hypotension with presyncopal symptoms compared to men. These symptoms could be influenced by an attenuated ability of the cerebrovasculature to respond to rapid changes in blood pressure (BP) [dynamic cerebral autoregulation (dCA)]. However, the influence of sex on dCA remains equivocal. We compared dCA in 11 women (25 ± 2 y) and 11 age-matched men (24 ± 1 y) using a multimodal approach including a sit-to-stand maneuver and forced oscillations (5 min of squat-stand performed at 0.05 and 0.10 Hz). The prevalence of initial orthostatic hypotension (IOH; decrease in systolic ≥ 40 mmHg and/or diastolic BP ≥ 20 mmHg) during the first 15 sec of sit-to-stand was determined as a functional outcome. In women, the decrease in mean middle cerebral artery blood velocity (MCAvmean) following the sit-to-stand was greater (−20 ± 8 vs. -11 ± 7 cm sec-1; p=0.018) and the onset of the regulatory change (time lapse between the beginning of the sit-to-stand and the increase in the conductance index (MCAvmean/mean arterial pressure(MAP)) was delayed (p=0.007). Transfer function analysis gain during 0.05 Hz squat-stand was ∼48% higher in women (6.4 ± 1.3 vs. 3.8 ± 2.3 sec; p=0.017). The prevalence of IOH was comparable between groups (4/9 vs. 5/9, p=0.637). These results indicate the cerebrovasculature of healthy women has an attenuated ability to react to large and rapid changes in BP in the face of preserved orthostasis, which could be related to a higher cerebrovascular reserve to face a rapid transient hypotension.NEWS & NOTEWORTHYThe novel findings of this study are that healthy women have impaired dynamic cerebral autoregulation, although the prevalence of orthostatic intolerance was similar in women and men. These results indicate the cerebrovasculature of healthy women has an attenuated ability to react to large and rapid changes in blood pressure in the face of preserved orthostasis, which could be related to a higher cerebrovascular reserve to face a rapid transient hypotension.
Estimation of task-based modulations in functional connectivity with MEG: a comparison of methods
Authors: Soto Juan L.P. , Jerbi Karim 
Published: September 2018

AbstractFor the assessment of functional interactions between distinct brain regions there is a great variety of mathematical techniques, with well-known properties, relative merits and shortcomings; however, the methods that deal specifically with task-based fluctuations in interareal coupling are scarce, and their relative performance is unclear. In the present article, we compare two approaches used in the estimation of correlation changes between the envelope amplitudes of narrowband brain activity obtained from magnetoencephalography (MEG) recordings. One approach is an implementation of semipartial canonical correlation analysis (SP-CCA), which is formally equivalent to the psychophysiological interactions technique successfully applied to functional magnetic resonance data. The other approach, which has been used in recent electrophysiology studies, consists of simply computing linear correlation coefficients of signals from two experimental conditions and taking their differences. We compared the two approaches with simulations and with multi-subject MEG signals acquired during a visuomotor coordination study. The analyses with simulated activity showed that computing differences in correlation coefficients (DCC) provided better discrimination between true coupling changes and spurious effects; on the other hand, SP-CCA resulted in significant effects around the reference location which were not found with DCC, and which may be due to field spread. Based on our findings, we recommend the use of DCC for the detection of task-based changes in connectivity, as it provided better performance than SP-CCA.
Label free 3D analysis of organelles in living cells by refractive index shows pre-mitotic organelle spinning in mammalian stem cells
Authors: Sandoz Patrick A. , Tremblay Christopher , Equis Sebastien , Pop Sorin , Pollaro Lisa , Cotte Yann , van der Goot F. Gisou , Frechin Mathieu 
Published: September 2018

AbstractHolo-tomographic microscopy (HTM) is a label-free non-phototoxic microscopy method reporting the fine changes of a cell’s refractive indexes (RI) in 3D. By combining HTM with epifluorescence, we demonstrate that cellular organelles such as Lipid droplets and mitochondria show a specific RI signature that distinguishes them with high resolution and contrast. We further show that HTM allows to follow in unprecedented ways the dynamics of mitochondria, lipid droplets as well as that of endocytic structures in live cells over long period of time, which led us to observe to our knowledge for the first time a global organelle spinning occurring before mitosis.
Modeling slow-processing of toxin messenger RNAs in type-I Toxin-Antitoxin systems: post-segregational killing and noise filtering
Authors: Himeoka Yusuke , Mitarai Namiko 
Published: September 2018

AbstractIn type-I toxin-antitoxin (TA) systems, the action of growth-inhibiting toxin proteins is counteracted by the antitoxin small RNAs (sRNAs) that prevent the translation of toxin messenger RNAs (mRNAs). When a TA module is encoded on a plasmid, the short lifetime of antitoxin sRNA compared to toxin mRNAs mediates post-segregational killing (PSK) that contribute the plasmid maintenance, while some of the chromosomal encoded TA loci have been reported to contribute to persister formation in response to a specific upstream signal. Some of the well studied type-I TA systems such ashok/sokare known to have a rather complex regulatory mechanism. Transcribed full-length toxin mRNAs fold such that the ribosome binding site is not accessible and hence cannot be translated. The mRNAs are slowly processed by RNases, and the truncated mRNAs can be either translated or bound by antitoxin sRNA to be quickly degraded. We analyze the role of this extra processing by a mathematical model. We first consider the PSK scenario, and demonstrate that the extra processing compatibly ensures the high toxin expression upon complete plasmid loss, without inducing toxin expression upon acquisition of a plasmid or decrease of plasmid number to a non-zero number. We further show that the extra processing help filtering the transcription noise, avoiding random activation of toxins in transcriptionally regulated TA systems as seen in chromosomal ones. The present model highlights impacts of the slow processing reaction, offering insights on why the slow processing reactions are commonly identified in multiple type-I TA systems.
Heart evoked brain oscillatory networks and its interruption in early stages of Alzheimer’s disease
Authors: Castellanos Nazareth , Diez Gustavo G. , Pereda Ernesto , López María Eugenia , Bruña Ricardo , Bartolomé Myriam G. , Maestú Fernando 
Published: September 2018

AbstractUnderstanding how the heart influences brain dynamics will suppose a deep change for the neuroscience, psychology and medicine. A mainstay questions is the heart modulation of resting state brain networks and its relation with both the cardiac dynamics and the cognitive status. We evaluated the heart evoked basal networks for controls and two groups of mild cognitive impairment patients, stable and progressive to Alzheimer’s disease without cardiovascular alteration symptoms. Our results in controls show that a healthy cognitive performance correlates with the heart modulation of brain dynamics in areas of the default mode network, and that the heart influence on brain networks varies along the cardiac cycle and the spectral band. However, the cognitive deficit produced by dementia correlates with the lack of heart modulation on brain activity. The heart influence on brain networks is disrupted in patients by producing hypersynchronization, accompanied by decreased cardiac complexity. We designed a surrogate and predictive procedure based on machine learning to compare the heart evoked results with the neural activity no locked to heartbeats. Based on our longitudinal data, we conclude that the prediction to progression to Alzheimer’s disease is higher when considering the heart - brain interaction than when taking into account only the brain dynamics. We can conclude that brain networks in control subjects were more responsive to the heart cycle, allowing a wealthier, more complex pattern of oscillations. Our results highlight the role of heart in cognitive neuroscience by showing that basal brain networks are modulated by the cardiac dynamics.
Taxonomic Classification of Ants (Formicidae) from Images using Deep Learning
Authors: Boer Marijn J. A. , Vos Rutger A. 
Published: September 2018

AbstractThe well-documented, species-rich, and diverse group of ants (Formicidae) are important ecological bioindicators for species richness, ecosystem health, and biodiversity, but ant species identification is complex and requires specific knowledge. In the past few years, insect identification from images has seen increasing interest and success, with processing speed improving and costs lowering. Here we propose deep learning (in the form of a convolutional neural network (CNN)) to classify ants at species level using AntWeb images. We used an Inception-ResNet-V2-based CNN to classify ant images, and three shot types with 10,204 images for 97 species, in addition to a multi-view approach, for training and testing the CNN while also testing a worker-only set and an AntWeb protocol-deviant test set. Top 1 accuracy reached 62% - 81%, top 3 accuracy 80% - 92%, and genus accuracy 79% - 95% on species classification for different shot type approaches. The head shot type outperformed other shot type approaches. Genus accuracy was broadly similar to top 3 accuracy. Removing reproductives from the test data improved accuracy only slightly. Accuracy on AntWeb protocol-deviant data was very low. In addition, we make recommendations for future work concerning image threshold, distribution, and quality, multi-view approaches, metadata, and on protocols; potentially leading to higher accuracy with less computational effort.
Draxin alters laminin expression during basement membrane reorganization to control cranial neural crest EMT
Authors: Hutchins Erica J. , Bronner Marianne E. 
Published: September 2018

ABSTRACTPremigratory neural crest cells arise within the dorsal neural tube and subsequently undergo an epithelial-to-mesenchymal transition (EMT) to leave the neuroepithelium and initiate migration. Draxin is a Wnt modulator that has been shown to control the timing of cranial neural crest EMT. Here we show that this process is accompanied by three stages of remodeling of the basement membrane protein laminin, from regression to expansion and channel formation. Loss of Draxin results in blocking laminin remodeling at the regression stage, whereas ectopic maintenance of Draxin blocks remodeling at the expansion stage. The latter effect is rescued by addition of Snail2, previously shown to be downstream of Draxin. Our results demonstrate an essential function for the Wnt modulator Draxin in regulating basement membrane remodeling during cranial neural crest EMT.HIGHLIGHTSCranial neural crest migrate through a laminin-rich basement membrane channelPerturbation of Draxin, a Wnt antagonist, alters laminin channel formationDraxin’s effect on laminin channel formation is largely mediated by Snail2
ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra
Authors: Lefort Gaëlle , Liaubet Laurence , Canlet Cécile , Tardivel Patrick , Pére Marie-Christine , Quesnel Hélène , Paris Alain , Iannuccelli Nathalie , Vialaneix Nathalie , Servien Rémi 
Published: September 2018

AbstractIn metabolomics, the detection of new biomarkers from NMR spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses.We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independant datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketting. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the conditions.This workflow is available through the R package ASICS, available on the Bioconductor platform.
Genome-skimming provides accurate quantification for pollen mixtures Authors
Authors: Lang Dandan , Tang Min , Hu Jiahui , Zhou Xin 
Published: September 2018

AbstractIn the face of global pollinator declines, plant-pollinator interaction networks have been studied to guide ecological conservation and restoration. In order to obtain more comprehensive and unbiased knowledge of these networks, perspectives of both plants and pollinators need to be considered integratively. Metabarcoding has seen increasing applications in characterizing pollen transported by pollinators. However, amplification bias across taxa could lead to unpredictable artefacts in pollen compositions. We examined the efficacy of a PCR-free genome-skimming method in quantifying mixed pollen, using mock samples constructed with known pollen species (5 mocks of flower pollen and 14 mocks of bee pollen). The results demonstrated a high level of repeatability and accuracy in identifying pollen from mixtures of varied species ratios. All pollen species were detected in all mock samples, and pollen frequencies estimated from the number of sequence reads of each species were significantly correlated with pollen count proportions (linear model, R2=86.7%, P = 2.2e- 16). For >97% of the mixed taxa, pollen proportion could be quantified by sequencing to the correct order of magnitude, even for species which constituted only 0.2% of the total pollen. We also showed that DNA extracted from pollen grains equivalent to those collected from a single honeybee corbicula was sufficient for the genome-skimming pipeline. We conclude that genome-skimming is a feasible approach to identifying and quantifying pollen compositions for mixed pollen samples. By providing reliable and sensitive taxon identification and relative abundance, this method is expected to improve the understanding of pollen diversity transported by pollinators and their ecological roles in the plant-pollinator networks.
Skewed temperature dependence affects range and abundance in a warming world
Authors: Hurford Amy , Cobbold Christina A. , Molnár Péter K. 
Published: September 2018

AbstractPopulation growth metrics such asR0are usually asymmetric functions of temperature, with cold-skewed curves arising when the positive effects of a temperature increase outweigh the negative effects, and warm-skewed curves arising in the opposite case. Classically, cold-skewed curves are interpreted as more beneficial to a species under climate warming, because cold-skewness implies increased population growth over a larger proportion of the species’ fundamental thermal niche than warm-skewness. However, inference based on the shape of the fitness curve alone, and without considering the synergistic effects of net reproduction, density, and dispersal may yield an incomplete understanding of climate change impacts. We formulate a moving-habitat integrodifference equation model to evaluate how fitness curve skewness affects species’ range size and abundance during climate warming. In contrast to classic interpretations, we find that climate warming adversely affects populations with cold-skewed fitness curves, positively affects populations with warm-skewed curves and has relatively little or mixed effects on populations with symmetric curves. Our results highlight the synergistic effects of fitness curve skewness, spatially heterogeneous densities, and dispersal in climate change impact analyses, and that the common approach of mapping changes only inR0may be misleading.
Modeling long lifespans in eusocial insect populations
Authors: RaviTeja Donepudi , Ramaswamy Ramakrishna 
Published: September 2018

AbstractAlong with division of labour, and life-history complexities, a characteristic of eusocial insect societies is the greatly extended lifespan for queens. The colony structure reduces the extrinsic mortality of the queen, and according to classical evolutionary theories of ageing, this greatly increases the lifespan. We explore the relationship between the evolution of longevity and the evolution of eusociality by introducing age-structure into a previously proposed evolutionary model and also define an associated agent-based model. A set of three population structures are defined: (i) solitary with all reproductive individuals, (ii) monogynous eusocial with a single queen, and (iii) polygynous eusocial, with multiple queens.In order to compare the relative fitnesses we compete all possible pairs of these strategies as well as all three together, analysing the effects of parameters such as the probability of progeny migration, group benefits, and extrinsic mortality on the evolution of long lifespans. Simulations suggest that long lifespans appear to evolve only in eusocial populations, and further, that long lifespans enlarge the region of parameter space where eusociality evolves. When all three population strategies compete, the agent-based simulations indicate that solitary strategies are largely confined to shorter lifespans. For long lifespan strategies the solitary behaviour results only for extreme (very low or very high) migration probability. For median and small values of migration probability, the polygynous eusocial and monogynous eusocial strategies give advantage to the population respectively. For a given migration probability, with an increase in lifespan, the dominant strategy changes from solitary to polygynous to monogynous eusociality. The evolution of a long lifespan is thus closely linked to the evolution of eusociality, and our results are in accord with the observation that the breeding female in monogynous eusocial species has a longer lifespan than those in solitary or polygynous eusocial species.