bluuebunny/crossref_metadata_2025 huggingface dataset:
Unintentional rewilding: lessons for trophic rewilding from other forms of species introductions
Authors: Tanentzap Andrew J. , Smith Bethany R.
Published: October 2018

Trophic rewilding involves adding species into ecosystems to restore extinct, top-down interactions, but limited quantitative data have prevented a systematic attempt to quantify its outcomes. Here, we exploit species introductions that have occurred for purposes other than restoration to inform trophic rewilding. We compiled 51 studies with 158 different responses of lower trophic levels to a species introduction that restored an extinct interaction, whether it intended to do so or not. Unintentional introductions were compared with checklists of extinct animals to identify potential analogues. Using the latest meta-analysis techniques, we found that the few cases of intentional rewilding had similar effects to unintentional rewilding, though there were large taxonomic and geographical biases. We also tested predictions from studies on trophic cascades about the factors that should influence rewilding. Unintentional rewilding was stronger where introduced consumers were non-invasive, but there was no effect of time that compared sites differed in introduction status, latitude or coevolution of responses with a taxonomically related analogue. Our study now shows that rewilding can reinstate extinct trophic interactions and highlights remaining data gaps that need closure to restore ecosystems across larger scales than has been previously possible.

This article is part of the theme issue ‘Trophic rewilding: consequences for ecosystems under global change’.
Climate explains recent population divergence, introgression and persistence in tropical mountains: phylogenomic evidence from Atlantic Forest warbling finches
Authors: do Amaral Fábio Raposo , Alvarado-Serrano Diego F. , Maldonado-Coelho Marcos , Pellegrino Katia C. M. , Miyaki Cristina Y. , Montesanti Julia A. C. , Lima-Ribeiro Matheus S. , Hickerson Michael J. , Thom Gregory
Published: October 2018

Taxa with disjunct distributions are common in montane biotas and offer excellent opportunities to investigate historical processes underlying genetic and phenotypic divergence. In this context, subgenomic datasets offer novel opportunities to explore historical demography in detail, which is key to better understand the origins and maintenance of diversity in montane regions. Here we used a large ultraconserved elements dataset to get insights into the main biogeographic processes driving the evolution of the Montane Atlantic Forest biota. Specifically, we studied two species of warbling finches disjunctly distributed across a region of complex geological and environmental history. We found that a scenario of three genetically differentiated populations is best supported by genomic clustering methods. Also, demographic simulations support simultaneous isolation of these populations at ~10 kya, relatively stable population sizes over recent time, and recent gene flow. Our results suggest a dual role of climate: population divergence, mediated by isolation in mountain tops during warm periods, as well as population maintenance - allowing persistence mediated by shifts in elevation distribution during periods of climate change, with episodic bouts contact and gene flow. Additional support for the role of climate comes from evidence of their contact in a recent past. We propose that two major gaps, which we call São Paulo and Caparaó subtropical gaps, have been historically important in the divergence of cold adapted organisms in the Atlantic Forest, and could be associated to cryptic diversity. Finally, our results suggest that shallow divergence and past gene flow may be common in montane organisms, but complex demographic histories may be detectable only when using subgenomic or genomic datasets.
Feature-specific prediction errors for visual mismatch
Authors: Stefanics Gabor , Stephan Klaas Enno , Heinzle Jakob
Published: October 2018

Predictive coding (PC) theory posits that our brain employs a predictive model of the environment to infer the causes of its sensory inputs. A fundamental but untested prediction of this theory is that the same stimulus should elicit distinct precision weighted prediction errors (pwPEs) when different (feature-specific) predictions are violated, even in the absence of attention. Here, we tested this hypothesis using functional magnetic resonance imaging (fMRI) and a multi-feature roving visual mismatch paradigm where rare changes in either color (red, green), or emotional expression (happy, fearful) of faces elicited pwPE responses in human participants. Using a computational model of learning and inference, we simulated pwPE and prediction trajectories of a Bayes-optimal observer and used these to analyze changes in blood oxygen level dependent (BOLD) responses to changes in color and emotional expression of faces while participants engaged in a distractor task. Controlling for visual attention by eye-tracking, we found pwPE responses to unexpected color changes in the fusiform gyrus. Conversely, unexpected changes of facial emotions elicited pwPE responses in cortico-thalamo-cerebellar structures associated with emotion and theory of mind processing. Predictions pertaining to emotions activated fusiform, occipital and temporal areas. Our results are consistent with a general role of PC across perception, from low-level to complex and socially relevant object features, and suggest that monitoring of the social environment occurs continuously and automatically, even in the absence of attention.

Highlights

Changes in color or emotion of physically identical faces elicit prediction errors

Prediction errors to such different features arise in distinct neuronal circuits

Predictions pertaining to emotions are represented in multiple cortical areas

Feature-specific prediction errors support predictive coding theories of perception
Predicting the effects of deep brain stimulation using a reduced coupled oscillator model
Authors: Weerasinghe Gihan , Duchet Benoit , Cagnan Hayriye , Brown Peter , Bick Christian , Bogacz Rafal
Published: October 2018

Deep brain stimulation (DBS) is known to be an effective treatment for a variety of neurological disorders, including Parkinson’s disease and essential tremor (ET). At present, it involves administering a train of pulses with constant frequency via electrodes implanted into the brain. New ‘closed-loop’ approaches involve delivering stimulation according to the ongoing symptoms or brain activity and have the potential to provide improvements in terms of efficiency, efficacy and reduction of side effects. The success of closed-loop DBS depends on being able to devise a stimulation strategy that minimizes oscillations in neural activity associated with symptoms of motor disorders. A useful stepping stone towards this is to construct a mathematical model, which can describe how the brain oscillations should change when stimulation is applied at a particular state of the system. Our work focuses on the use of coupled oscillators to represent neurons in areas generating pathological oscillations. Using a reduced form of the Kuramoto model, we analyse how a patient should respond to stimulation when neural oscillations have a given phase and amplitude. We predict that, provided certain conditions are satisfied, the best stimulation strategy should be phase specific but also that stimulation should have a greater effect if applied when the amplitude of brain oscillations is lower. We compare this surprising prediction with data obtained from ET patients. In light of our predictions, we also propose a new hybrid strategy which effectively combines two of the strategies found in the literature, namely phase-locked and adaptive DBS.

Author summary

Deep brain stimulation (DBS) involves delivering electrical impulses to target sites within the brain and is a proven therapy for a variety of neurological disorders. Closed loop DBS is a promising new approach where stimulation is applied according to the state of a patient. Crucial to the success of this approach is being able to predict how a patient should respond to stimulation. Our work focusses on DBS as applied to patients with essential tremor (ET). On the basis of a theoretical model, which describes neurons as oscillators that respond to stimulation and have a certain tendency to synchronize, we provide predictions for how a patient should respond when stimulation is applied at a particular phase and amplitude of the ongoing tremor oscillations. Previous experimental studies of closed loop DBS provided stimulation either on the basis of ongoing phase or amplitude of pathological oscillations. Our study suggests how both of these measurements can be used to control stimulation. As part of this work, we also look for evidence for our theories in experimental data and find our predictions to be satisfied in one patient. The insights obtained from this work should lead to a better understanding of how to optimise closed loop DBS strategies.
Characterization of BSN175: A Drug to Treat Prader-Willi Syndrome
Authors: Ackerman Alyson , Lodder Robert A.
Published: October 2018

The purpose of this research is to choose the best analytical method for determining stability of BSN175. This research uses an accelerated stability study to compare the decomposed and stable drug using IR and 1H NMR spectroscopy. The Bootstrap Error-adjusted Single-sample Technique (BEST) was used to compare the effectiveness of these analytical methods and choose the best option for determining stability.
Polygenic prediction of breast cancer: comparison of genetic predictors and implications for screening
Authors: Läll Kristi , Lepamets Maarja , Palover Marili , Esko Tõnu , Metspalu Andres , Tõnisson Neeme , Padrik Peeter , Mägi Reedik , Fischer Krista
Published: October 2018

Background

Published genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aims to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies.

Methods

Four different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) are compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors are studied in both cohorts.

Results

The metaGRS that combines two genetic risk scores (metaGRS2 - based on 75 and 898 Single Nucleotide Polymorphisms, respectively) has the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS2 corresponds to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10-135) in the UK Biobank and accounting for family history marginally attenuates the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 9.1*10-129). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS2 compared to women in the lowest 50% is 4.2 (95% CI 2.8 to 6.2, p = 8.1*10-13). The different GRSs are only moderately correlated with each other and are associated with different known predictors of BC. The classification of genetic risk for the same individual may vary considerably depending on the chosen GRS.

Conclusions

We have shown that metaGRS2 that combines on the effects of more than 900 SNPs provides best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS2 indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.
Directing voluntary temporal attention increases fixational stability
Authors: Denison Rachel N. , Yuval-Greenberg Shlomit , Carrasco Marisa
Published: October 2018

Our visual input is constantly changing, but not all moments are equally relevant. Temporal attention, the prioritization of visual information at specific points in time, increases perceptual sensitivity at behaviorally relevant times. The dynamic processes underlying this increase are unclear. During fixation, humans make small eye movements called microsaccades, and inhibiting microsaccades improves perception of brief stimuli. Here we asked whether temporal attention changes the pattern of microsaccades in anticipation of brief stimuli. Human observers (female and male) judged brief stimuli presented within a short sequence. They were given either an informative precue to attend to one of the stimuli, which was likely to be probed, or an uninformative (neutral) precue. We found strong microsaccadic inhibition before the stimulus sequence, likely due to its predictable onset. Critically, this anticipatory inhibition was stronger when the first target in the sequence (T1) was precued (task-relevant) than when the precue was uninformative. Moreover, the timing of the last microsaccade before T1 and the first microsaccade after T1 shifted, such that both occurred earlier when T1 was precued than when the precue was uninformative. Finally, the timing of the nearest pre- and post-T1 microsaccades affected task performance. Directing voluntary temporal attention therefore impacts microsaccades, helping to stabilize fixation at the most relevant moments, over and above the effect of predictability. Just as saccading to a relevant stimulus can be an overt correlate of the allocation of spatial attention, precisely timed gaze stabilization can be an overt correlate of the allocation of temporal attention.

Significance statement

We pay attention at moments in time when a relevant event is likely to occur. Such temporal attention improves our visual perception, but how it does so is not well understood. Here we discovered a new behavioral correlate of voluntary, or goal-directed, temporal attention. We found that the pattern of small fixational eye movements called microsaccades changes around behaviorally relevant moments in a way that stabilizes the position of the eyes. Microsaccades during a brief visual stimulus can impair perception of that stimulus. Therefore, such fixation stabilization may contribute to the improvement of visual perception at attended times. This link suggests that in addition to cortical areas, subcortical areas mediating eye movements may be recruited with temporal attention.
Laws for Glia Organization Conserved Across Mammals
Authors: Pinto-Duarte Antonio , Bogue Katharine , Sejnowski Terrence J. , Srinivasan Shyam
Published: October 2018

The organizational principles of glia remain largely unknown despite their vital role in nervous system function. Previous work has shown that the number of glia per unit volume of neocortex is constant across mammalian species. We hypothesize that the conservation of glia volume density within brain regions might be a governing principle of organization across species. To test this hypothesis, we used stereology, light microscopy, and data available in the literature to examine five brain regions: the cerebral cortex and four brain regions that differ from the cerebral cortex and each other - the anterior piriform cortex, the posterior piriform cortex, the entorhinal cortex, and the cerebellum. We discovered two orderly relationships: First, glia volume density within a brain region was constant across species, including humans, although it significantly differed between regions, suggesting that glia density might constitute a region-specific marker. Second, the ratio of glia to neuron increased with brain volume according to a ¼ power law in the primate frontal cortex and the neocortex, the mammalian paleocortex, and the cerebellum. These relationships show that the development of glia and neurons are coupled, and suggest that what a neural circuit computes depends as much on its glial components as on its neurons.

Main Points

The volume density of glia (i.e., number of glia per unit volume) within a brain region is con-served across mammalian species including humans.

The ratio of glia to neuron increases with bigger brains.

The volume density of glia is significantly different across functionally and architecturally dif-ferent brain regions and could function as a region-specific marker.

Glia obey scaling constraints that are different from scaling constraints for neurons.
Complement 3 signaling is necessary for the developmental refinement of olfactory bulb circuitry
Authors: Lehmann Katherine S. , Wood Alynda , Cummings Diana , Bai Li , Stevens Beth , Belluscio Leonardo
Published: October 2018

The olfactory system depends upon organizational maps that are developmentally refined and maintained, however the cellular and molecular mechanisms that underlie these processes are unknown. Studies have shown that microglia and complement molecules are important for the developmental refinement of circuitry within the visual system, thus we asked whether they played a similar role in the olfactory system through the formation of the olfactory bulb (OB) maps, the glomerular and intrabulbar maps. Our findings revealed that microglia in mature animals engulf olfactory sensory neuron (OSN) axons and the synaptic terminals of tufted cells in the glomerular and intrabulbar maps respectively, suggesting microglia could anatomically shape the mature OB circuitry. To determine the mechanisms underlying this axonal pruning activity we used complement 3 (C3) and complement receptor 3 (CR3) knockout mice to investigate if C3 signaling was necessary for precise OB map development. Our results demonstrate that glomerular and intrabulbar map disorganization as typically present in early postnatal mice persists into adulthood when C3 signaling is disrupted. These data clearly establish the C3/CR3 pathway as necessary for the proper developmental refinement of both olfactory maps. We further present the olfactory system as a unique platform to study the role of glia in the development and adult refinement of regenerating circuits.
The genome of the plague-resistant great gerbil reveals species-specific duplication of an MHCII gene
Authors: Nilsson Pernille , Solbakken Monica H. , Schmid Boris V. , Orr Russell J. S. , Lv Ruichen , Cui Yujun , Song Yajun , Zhang Yujiang , Stenseth Nils Chr. , Yang Ruifu , Jakobsen Kjetill S. , Easterday W. Ryan , Jentoft Sissel
Published: October 2018

The great gerbil (Rhombomys opimus) is a social rodent living in permanent, complex burrow systems distributed throughout Central Asia, where it serves as the main host of several important vector-borne infectious diseases and is defined as a key reservoir species for plague (Yersinia pestis). Studies from the wild have shown that the great gerbil is largely resistant to plague but the genetic basis for resistance is yet to be determined. Here, we present a highly contiguous annotated genome assembly of great gerbil, covering over 96 % of the estimated 2.47 Gb genome. Comparative genomic analyses focusing on the immune gene repertoire, reveal shared gene losses withinTLRgene families (i.e.TLR8, TLR10and all members ofTLR11-subfamily) for the Gerbillinae lineage, accompanied with signs of diversifying selection ofTLR7andTLR9. Most notably, we find a great gerbil-specific duplication of theMHCII DRBlocus.In silicoanalyses suggest that the duplicated gene provides high peptide binding affinity forYersiniaeepitopes. The great gerbil genome provides new insights into the genomic landscape that confers immunological resistance towards plague. The high affinity forYersiniaepitopes could be key in our understanding of the high resistance in great gerbils, putatively conferring a faster initiation of the adaptive immune response leading to survival of the infection. Our study demonstrates the power of studying zoonosis in natural hosts through the generation of a genome resource for further comparative and experimental work on plague survival and evolution of host-pathogen interactions.
Nonlinear and Nonlocal Elasticity in Coarse-Grained Differential-Tension Models of Epithelia
Authors: Pierre A. Haas , Raymond E. Goldstein
Published: October 2018

The shapes of epithelial tissues result from a complex interplay of contractile forces in the cytoskeleta of the cells in the tissue, and adhesion forces between them. A host of discrete, cell-based models describe these forces by assigning different surface tensions to the apical, basal, and lateral sides of the cells. These differential-tension models have been used to describe the deformations of epithelia in different living systems, but the underlying continuum mechanics at the scale of the epithelium are still unclear. Here, we derive a continuum theory for a simple differential-tension model of a two-dimensional epithelium and study the buckling of this epithelium under imposed compression. The analysis reveals howthe cell-level properties encoded in the differential-tension model lead to linear, nonlinear as well as nonlocal elastic behavior at the continuum level.
Why would parthenogenetic females systematically produce males who never transmit their genes to females?
Authors: Grosmaire Manon , Launay Caroline , Siegwald Marion , Félix Marie-Anne , Gouyon Pierre-Henri , Delattre Marie
Published: October 2018

In pseudogamous species, females use the sperm of males from another species to activate their oocytes and produce females, without using the sperm DNA. Here we report a novel reproductive strategy found in the pseudogamous nematode Mesorhabditis belari, which produces its own males at low frequency. We find that the 8% of M. belari males are necessary to fertilize all oocytes but pass on their genes only to males, and never to females. Thus, the production of males has no impact on the genetic diversity of females. Using game theory, we show that the production of males at low frequency constitutes an efficient strategy only if sons are more likely to mate with their sisters. We validate this prediction experimentally by revealing a mating preference between siblings. We uncover the remarkable reproductive strategy of parthenogenetic females that pay the cost of producing males while males do not spread their genes.
Trem2promotes anti-inflammatory responses in microglia and is suppressed under pro-inflammatory conditions
Authors: Liu Wenfei , Taso Orjona , Wang Rui , Bayram Sevinc , Garcia-Reitboeck Pablo , Mallach Anna , Andrews William D. , Piers Thomas M. , Graham Andrew C. , Botia Juan A. , Pocock Jennifer M. , Cummings Damian M. , Hardy John , Edwards Frances A. , Salih Dervis A.
Published: October 2018

Genome-wide association studies have reported that, amongst other microglial genes, variants inTREM2can profoundly increase the incidence of developing Alzheimer’s disease (AD). We have investigated the role of TREM2 in primary microglial cultures from wild type mice by using siRNA to decreaseTrem2expression, and in parallel from knock-in mice heterozygous or homozygous for theTrem2R47H AD risk variant. The prevailing phenotype ofTrem2R47H knock-in mice was decreased expression levels ofTrem2in microglia, which resulted in decreased density of microglia in the hippocampus. Overall, primary microglia with reducedTrem2expression, either by siRNA or from the R47H knock-in mice, displayed a similar phenotype. Comparison of the effects of decreasedTrem2expression under conditions of LPS pro-inflammatory or IL-4 anti-inflammatory stimulation revealed the importance ofTrem2in driving a number of the genes up-regulated in the anti-inflammatory phenotype. RNA-seq analysis showed that IL-4 induced the expression of a programme of genes includingArg1andAp1b1in microglia, which showed an attenuated response to IL-4 whenTrem2expression was decreased. Genes showing a similar expression profile toArg1were enriched for STAT6 transcription factor recognition elements in their promoter, andTrem2knockdown decreased levels of the transcription factor STAT6. LPS-induced pro-inflammatory stimulation suppressedTrem2expression, thus preventing TREM2’s anti-inflammatory drive. Given that anti-inflammatory signaling is associated with tissue repair, understanding the signaling mechanisms downstream ofTrem2in coordinating the pro- and anti-inflammatory balance of microglia, particularly mediating effects of the IL-4-regulated anti-inflammatory pathway, has important implications for fighting neurodegenerative disease.

Graphical abstract
Genetic population variation and phylogeny ofSinomenium acutum(Menispermaceae) in subtropical China through chloroplast marker
Authors: He Ying , Guo Chun , Zeng Xiyao , Yang Hua , Xiong Xingyao , Qiu Ping
Published: October 2018

Sinomenium acutum(Menispermaceae) is a traditional Chinese medicine. In recent years, extensive harvesting for medicinal purposes has resulted in a sharp decline in its population. Genetic information is crucial for the proper exploitation and conservation ofSinomenium acutum, but little is known about it at present. In this study, we analyzed 77 samples from 4 populations using four non-coding regions (atpI-atpH,trnQ-5’rps16,trnH-psbA, andtrnL-trnF) of chloroplast DNA and 14 haplotypes (from C1 to C14) were identified. C1 and C3 were common haplotypes, which were shared by all populations, and C3 was an ancestral haplotype, the rest were rare haplotypes. Obvious phylogeographic structure was not existed inferred byGST/NSTtest. Mismatch distribution, Tajima’s D and Fu’s FStests failed to support a rapid demographic expansion inSinomenium acutum. AMOVA highlighted that the high level of genetic differentiation within population. Low genetic variation among populations illustrated gene flow was not restricted. Genetic diversity analyses demonstrated that the populations of Xuefeng, Dalou, and Daba Mountains were possible refugia localities ofSinomenium acutum. Based on this study, we proposed a preliminary protection strategy for it that C1, C3, C11 and C12 must be collected. These results offer an valuable and useful information for this species of population genetic study as well as further conservation.
Prokaryotic community shifts during soil formation on sands in the tundra zone
Authors: Zhelezova Alena , Chernov Timofey , Tkhakakhova Azida , Xenofontova Natalya , Semenov Mikhail , Kutovaya Olga
Published: October 2018

A chronosequence approach,i.e., a comparison of spatially distinct plots with different stages of succession, is commonly used for studying microbial community dynamics during paedogenesis. The successional traits of prokaryotic communities following sand fixation processes have previously been characterized for arid and semi-arid regions, but they have not been considered for the tundra zone, where the environmental conditions are unfavourable for the establishment of complicated biocoenoses. In this research, we characterized the prokaryotic diversity and abundance of microbial genes found in a typical tundra and wooded tundra along a gradient of increasing vegetation – unfixed aeolian sand, semi-fixed surfaces with mosses and lichens, and mature soil under fully developed plant cover. Microbial communities from typical tundra and wooded tundra plots at three stages of sand fixation were compared using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing of 16S rRNA gene libraries. The abundances of ribosomal genes increased gradually in both chronosequences, and a similar trend was observed for the functional genes related to the nitrogen cycle (nifH, bacterialamoA, nirKandnirS). The relative abundance ofPlanctomycetesincreased, while those ofThaumarchaeota, CyanobacteriaandChloroflexidecreased from unfixed sands to mature soils. According to β-diversity analysis, prokaryotic communities of unfixed sands were more heterogeneous compared to those of mature soils. Despite the differences in the plant cover of the two mature soils, the structural compositions of the prokaryotic communities were shaped in the same way.
Taking a deeper look: Quantifying the differences in fish assemblages between shallow and mesophotic temperate rocky reefs
Authors: Williams Joel , Jordan Alan , Harasti David , Davies Peter , Ingleton Tim
Published: October 2018

The spatial distribution of a species assemblage is often determined by habitat and climate. In the marine environment, depth can become an important factor as degrading light leads to changes in the biological habitat structure. To date, much of the focus of ecological fish research has been based on reefs in less than 40 m with little research on the ecological role of mesophotic reefs. We deployed baited remote underwater stereo video systems (stereo-BRUVS) on temperate reefs in two depth categories: shallow (20-40m) and mesophotic (80-120m), off Port Stephens, Australia. Sites were selected using data collected by swath acoustic sounder to ensure stereo-BRUVS were deployed on reef. The sounder also provided rugosity, slope and relief data for each stereo-BRUVS deployment. Multivariate analysis indicates that there are significant differences in the fish assemblages between shallow and mesophotic reefs, primarily driven by Ophthalmolepis lineolatus and Notolabrus gymnogenis only occurring on shallow reefs and schooling species of fish that were unique to each depth category: Atypichthys strigatus on shallow reefs and Centroberyx affinis on mesophotic reefs. While shallow reefs had a greater species richness and abundance of fish when compared to mesophotic reefs, mesophotic reefs hosted the same species richness of fishery targeted species. Chrysophrys auratus (pink snapper) and Nemodactylus douglassii (grey morwong) are two highly targeted species in this region. While C. auratus was numerically more abundant on shallow reefs, mesophotic reefs provide habitat for larger fish. In comparison, N. douglassii were evenly distributed across all sites sampled. Generalized linear models revealed that depth and habitat type provided the most parsimonious model for predicting the distribution of C. auratus, while habitat type alone best predicted the distribution of N. douglassii. These results demonstrate the importance of mesophotic reefs to fishery targeted species and therefore have implications for informing the management of these fishery resources on shelf rocky reefs.
Disrupted reinforcement learning during post-error slowing in ADHD
Authors: Chevrier Andre , Bhaijiwala Mehereen , Lipszyc Jonathan , Cheyne Douglas , Graham Simon , Schachar Russell
Published: October 2018

ADHD is associated with altered dopamine regulated reinforcement learning on prediction errors. Despite evidence of categorically altered error processing in ADHD, neuroimaging advances have largely investigated models of normal reinforcement learning in greater detail. Further, although reinforcement leaning critically relies on ventral striatum exerting error magnitude related thresholding influences on substantia nigra (SN) and dorsal striatum, these thresholding influences have never been identified with neuroimaging. To identify such thresholding influences, we propose that error magnitude related activities must first be separated from opposite activities in overlapping neural regions during error detection. Here we separate error detection from magnitude related adjustment (post-error slowing) during inhibition errors in the stop signal task in typically developing (TD) and ADHD adolescents using fMRI. In TD, we predicted that: 1) deactivation of dorsal striatum on error detection interrupts ongoing processing, and should be proportional to right frontoparietal response phase activity that has been observed in the SST; 2) deactivation of ventral striatum on post-error slowing exerts thresholding influences on, and should be proportional to activity in dorsal striatum. In ADHD, we predicted that ventral striatum would instead correlate with heightened amygdala responses to errors. We found deactivation of dorsal striatum on error detection correlated with response-phase activity in both groups. In TD, post-error slowing deactivation of ventral striatum correlated with activation of dorsal striatum. In ADHD, ventral striatum correlated with heightened amygdala activity. Further, heightened activities in locus coeruleus (norepinephrine), raphe nucleus (serotonin) and medial septal nuclei (acetylcholine), which all compete for control of DA, and are altered in ADHD, exhibited altered correlations with SN. All correlations in TD were replicated in healthy adults. Results in TD are consistent with dopamine regulated reinforcement learning on post-error slowing. In ADHD, results are consistent with heightened activities in the amygdala and non-dopaminergic neurotransmitter nuclei preventing reinforcement learning.
Apicomplexan motility depends on the operation of an endocytic-secretory cycle
Authors: Gras Simon , Jimenez-Ruiz Elena , Klinger Christen M. , Lemgruber Leandro , Meissner Markus
Published: October 2018

Apicomplexan parasites invade host cells in an active process, involving their ability to move by gliding motility and invasion. While the acto-myosin-system of the parasite plays a crucial role in the formation and release of attachment sites during this process, there are still open questions, such as how the force powering motility is generated. In many eukaryotes a secretory-endocytic cycle leads to recycling of receptors (integrins), necessary to form attachment sites, regulation of surface area during motility and generation of retrograde membrane flow. Here we demonstrate that endocytosis operates during gliding motility inToxoplasma gondiiand appears to be crucial for the establishment of retrograde membrane flow, since inhibition of endocytosis blocks retrograde flow and motility. We identified lysophosphatidic acid (LPA) as a potent stimulator of endocytosis and demonstrate that extracellular parasites can efficiently incorporate exogenous material, such as nanogold particles. Furthermore, we show that surface proteins of the parasite are recycled during this process. Interestingly, the endocytic and secretory pathways of the parasite converge, and endocytosed material is subsequently secreted, demonstrating the operation of an endocytic-secretory cycle. Together our data consolidate previous findings and we propose a novel model that reconciles parasite motility with observations in other eukaryotes: the fountain-flow-model for apicomplexan parasite motility.
Bayesian inference of metabolic kinetics from genome-scale multiomics data
Authors: St. John Peter C. , Strutz Jonathan , Broadbelt Linda J. , Tyo Keith E.J. , Bomble Yannick J.
Published: October 2018

Modern biological tools generate a wealth of data on metabolite and protein concentrations that can be used to help inform new strain designs. However, integrating these data sources to generate predictions of steady-state metabolism typically requires a kinetic description of the enzymatic reactions that occur within a cell. Parameterizing these kinetic models from biological data can be computationally difficult, especially as the amount of data increases. Robust methods must also be able to quantify the uncertainty in model parameters as a function of the available data, which can be particularly computationally intensive. The field of Bayesian inference offers a wide range of methods for estimating distributions in parameter uncertainty. However, these techniques are poorly suited to kinetic metabolic modeling due to the complex kinetic rate laws typically employed and the resulting dynamic system that must be solved. In this paper, we employ linear-logarithmic kinetics to simplify the calculation of steady-state flux distributions and enable efficient sampling and variational inference methods. We demonstrate that detailed information on the posterior distribution of kinetic model parameters can be obtained efficiently at a variety of different problem scales, including large-scale kinetic models trained on multiomics datasets. These results allow modern Bayesian machine learning tools to be leveraged in understanding biological data and developing new, efficient strain designs.
A comparison of visual features used by humans and machines to classify wildlife
Authors: Miao Zhongqi , Gaynor Kaitlyn M , Wang Jiayun , Liu Ziwei , Muellerklein Oliver , Norouzzadeh Mohammad Sadegh , Bowie Rauri C K , Nathan Ran , Yu Stella X , Getz Wayne M
Published: October 2018

In our quest to develop more intelligent machines, knowledge of the visual features used by machines to classify objects shall be helpful. The current state of the art in training machines to classify wildlife species from camera-trap data is to employ convolutional neural networks (CNN) encoded within deep learning algorithms. Here we report on results obtained in training a CNN to classify 20 African wildlife species with an overall accuracy of 87.5% from a dataset containing 111,467 images. We then used a gradient-weighted class-activation-mapping (Grad-CAM) procedure to extract the most salient pixels in the final convolution layer. We show that these pixels highlight features in particular images that are in most, but not all, cases similar to those used to train humans to identify these species. Further, we used mutual information methods to identify the neurons in the final convolution layer that consistently respond most strongly across a set of images of one particular species, and we then interpret the features in the image where the strongest responses occur. We also used hierarchical clustering offeature vectors(i.e., the state of the final fully-connected layer in the CNN) associated with each image to produce avisual similarity dendrogramof identified species. Finally, we evaluated how images that were not part of the training set fell within our dendrogram when these images were one of the 20 species “known” to our CNN in contrast to where they fell when these images were “unknown” to our CNN.
Genomic variants concurrently listed in a somatic and a germline mutation database have implications for disease-variant discovery and genomic privacy
Authors: Meyerson William , Gerstein Mark
Published: October 2018

Background

Mutations arise in the human genome in two major settings: the germline and soma. These settings involve different inheritance patterns, chromatin structures, and environmental exposures, all of which might be predicted to differentially affect the distribution of substitutions found in these settings. Nonetheless, recent studies have found that somatic and germline mutation rates are similarly affected by endogenous mutational processes and epigenetic factors.

Results

Here, we quantified the number of single nucleotide variants that co-occur between somatic and germline call-sets (cSNVs), compared this quantity with expectations, and explained noted departures. We found that three times as many variants are shared between the soma and germline than is expected by independence. We developed a new, general-purpose statistical framework to explain the observed excess of cSNVs in terms of the varying mutation rates of different kinds substitution types and of genomic regions. Using this metric, we find that more than 90% of this excess can be explained by our observation that the basic substitution types (such as N[C->T]G, C->A, etc.) have correlated mutation rates in the germline and soma. Matched-normal read depth analysis suggests that an appreciable fraction of this excess may also derive from germline contamination of somatic samples.

Conclusion

Overall, our results highlight the commonalities in substitution patterns between the germline and soma. The universality of some aspects of human mutation rates offers insight into the potential molecular mechanisms of human mutation. The highlighted similarities between somatic and germline mutation rates also lay the groundwork for future studies that distinguish disease-causing variants from a genomic background informed by both somatic and germline variant data. Moreover, our results also indicate that the depth of matched normal sequencing necessary to ensure genomic privacy of donors of somatic samples may be higher than previously appreciated. Furthermore, the fact that we were able to explain such a high portion of recurrent variants using known determinants of mutation rates is evidence that the genomics community has already discovered the most important predictors of mutation rates for single nucleotide variants.
Metabolome-scale genome-wide association studies reveal chemical diversity and genetic control of maize specialized metabolites
Authors: Shaoqun Zhou , Kremling Karl A. , Nonoy Bandillo , Annett Richter , Zhang Ying K. , Ahern Kevin R. , Artyukhin Alexander B. , Hui Joshua X. , Schroeder Frank C. , Buckler Edward S. , Georg Jander
Published: October 2018

One Sentence Summary

HPLC-MS metabolite profiling of maize seedlings, in combination with genome-wide association studies, identifies numerous quantitative trait loci that influence the accumulation of foliar metabolites.

Cultivated maize (Zea mays) retains much of the genetic and metabolic diversity of its wild ancestors. Non-targeted HPLC-MS metabolomics using a diverse panel of 264 maize inbred lines identified a bimodal distribution in the prevalence of foliar metabolites. Although 15% of the detected mass features were present in >90% of the inbred lines, the majority were found in <50% of the samples. Whereas leaf bases and tips were differentiated primarily by flavonoid abundance, maize varieties (stiff-stalk, non-stiff-stalk, tropical, sweet corn, and popcorn) were differentiated predominantly by benzoxazinoid metabolites. Genome-wide association studies (GWAS), performed for 3,991 mass features from the leaf tips and leaf bases, showed that 90% have multiple significantly associated loci scattered across the genome. Several quantitative trait locus hotspots in the maize genome regulate the abundance of multiple, often metabolically related mass features. The utility of maize metabolite GWAS was demonstrated by confirming known benzoxazinoid biosynthesis genes, as well as by mapping isomeric variation in the accumulation of phenylpropanoid hydroxycitric acid esters to a single linkage block in a citrate synthase-like gene. Similar to gene expression databases, this metabolomic GWAS dataset constitutes an important public resource for linking maize metabolites with biosynthetic and regulatory genes.
Analysis of natural fibre composites for aerospace structures
Authors: Brischetto Salvatore
Published: October 2018

Purpose

The main idea is the comparison between composites including natural fibres (such as the linoleum fibres) and typical composites including carbon fibres or glass fibres. The comparison is proposed for different structures (plates, cylinders, cylindrical and spherical shells), lamination sequences (cross-ply laminates and sandwiches with composite skins) and thickness ratios. The purpose of this paper is to understand if linoleum fibres could be useful for some specific aerospace applications.

Design/methodology/approach

A general exact three-dimensional shell model is used for the static analysis of the proposed structures to obtain displacements and stresses through the thickness. The shell model is based on a layer-wise approach and the differential equations of equilibrium are solved by means of the exponential matrix method.

Findings

In qualitative terms, composites including linoleum fibres have a mechanical behaviour similar to composites including glass or carbon fibres. In terms of stress and displacement values, composites including linoleum fibres can be used in aerospace applications with limited loads. They are comparable with composites including glass fibres. In general, they are not competitive with respect to composites including carbon fibres. Such conclusions have been verified for different structure geometries, lamination sequences and thickness ratios.

Originality/value

The proposed general exact 3D shell model allows the analysis of different geometries (plates and shells), materials and laminations in a unified manner using the differential equilibrium equations written in general orthogonal curvilinear coordinates. These equations written for spherical shells degenerate in those for cylinders, cylindrical shell panels and plates by means of opportune considerations about the radii of curvature. The proposed shell model allows an exhaustive comparison between different laminated and sandwich composite structures considering the typical zigzag form of displacements and the correct imposition of compatibility conditions for displacements and equilibrium conditions for transverse stresses.
Experimental and artificial neural network investigation on the effect of inclination angle on the interface temperature of CPU/metal foam heat sink
Authors: Rashidi Ali Mohammad , Paknezhad Mehrad , Yousefi Tooraj
Published: October 2018

Purpose

This study aims to clarify the relationship between inclination angle of hot surface of CPU and its temperature in absence and presence of aluminum foam as a cooling system. It proposes application of the artificial neural [multi-layer perceptron (MLP) and radial basis function] networks and adaptive neuron-fuzzy inference system (ANFIS) to predict interface temperature of central processing unit (CPU)/metal foam heat sink.

Design/methodology/approach

To provide a consistent set of data, the surface of an aluminum cone with and without installing Duocel aluminum foam was heated in a natural convection using an electrical resistor. The hot surface temperature was measured using five K-type thermocouples (±0.1°C). To develop the predictive models, ambient temperature, input power and inclination angle are taken as input which varied from 23°C to 32°C, 4 to 20 W and 0° to 90°, respectively. The hot surface temperature is taken as the output.

Findings

The results show that in the presence of foam, the hot surface temperature was less sensitive to the variations of angle, and the maximum enhancement of the heat transfer coefficient was 23 per cent at the vertical position. Both MLP network and ANFIS are comparable, but the values predicted by MLP network are in more conformity with the measured values.

Originality/value

The effect of metal foam on the inclination angle/hot surface temperature dependence is identified. The optimum angle is clarified. The applicability of the MLP networks to predict interface temperature of CPU/heat sink is approved.
Time management: presenteeism versus management-by-objectives
Authors: Amponsah-Tawiah Kwesi , Opata John Louis , Tetteh Samuel Doku
Published: October 2018

Purpose

This study examined the actual productive hours of employees from the service sector in Ghana.

Design/methodology/approach

This study adopted an exploratory cross-sectional survey design. The purposive and convenience sampling techniques were used to identify the service organizations and recruited 520 employees in Accra for the study. Specifically, these respondents were workers from banks, insurance companies, auditing firms and oil and gas companies. The data were analyzed using frequencies and other descriptive statistics.

Findings

Results showed poor time management among the study organizations. It was reported that although most workers report to work as early as 6:30 a.m., they wait until 8:30 a.m. to commence the day’s work schedule. In addition, they start thinking of break at least 15 min before actual break time which decreases productivity. In addition, employees reported spending at least 30 min on break. They also added that, they start clearing the desks about 15 min before actual closing time and leave the office at exactly 5:00 p.m.

Practical Implications

This study shows that the physical presence of workers does not necessarily mean they are working. The study proposes an alternative way to increase productivity rather than relying on physical presence of the workers.

Originality/value

This study is among the few that empirically sought to explore the actual time that workers use in a day at work. Thus, it measured actual productive hours at of service employees in Ghana.