bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mixture coding and segmentation in the anterior piriform cortex
Authors: Penker Sapir , Licht Tamar , Hofer Katharina T. , Rokni Dan 
Published: December 2019

AbstractCoding of odorous stimuli has been mostly studied using single isolated stimuli. However, a single sniff of air in a natural environment is likely to introduce airborne chemicals emitted by multiple objects into the nose. The olfactory system is therefore faced with the task of segmenting odor mixtures to identify objects in the presence of rich and often unpredictable backgrounds. The piriform cortex is thought to be the site of object recognition and scene segmentation, yet the nature of its responses to odorant mixtures is largely unknown. In this study, we asked two related questions. 1) How are mixtures represented in the piriform cortex? And 2) Can the identity of individual mixture components be read out from mixture representations in the piriform cortex? To answer these questions, we recorded single unit activity in the piriform cortex of naïve mice while sequentially presenting single odorants and their mixtures. We find that a normalization model explains mixture responses well, both at the single neuron, and at the population level. Additionally, we show that mixture components can be identified from piriform cortical activity by pooling responses of a small population of neurons - in many cases a single neuron is sufficient. These results indicate that piriform cortical representations are well suited to perform figure-background segmentation without the need for learning.
“Campylobacter jejunimotility integrates specialized cell shape, flagellar filament, and motor, to coordinate action of its opposed flagella in viscous media”
Authors: Cohen Eli J. , Nakane Daisuke , Kabata Yoshiki , Hendrixson David R. , Nishizaka Takayuki , Beeby Morgan 
Published: December 2019

AbstractCampylobacter jejunirotates a flagellum at each pole to swim through the viscous mucosa of its hosts’ gastrointestinal tracts. Despite their importance for host colonization, however, howC. jejunicoordinates rotation of these two opposing flagella is unclear. As well as their polar placement,C. jejuni’sflagella deviate from the Enterobacteriaceael norm in other ways: their flagellar motors produce much higher torque and their flagellar filament is made of two different zones of two different flagellins. To understand howC. jejuni’sopposed motors coordinate, and what contribution these factors play inC. jejunimotility, we developed strains with flagella that could be fluorescently labeled, and observed them by high-speed video microscopy. We found thatC. jejunicoordinates its dual flagella by wrapping the leading filament around the cell body during swimming in high-viscosity media and that its differentiated flagellar filament has evolved to facilitate this wrapped-mode swimming. Unexpectedly,C. jejuni’s helical body is important for facile unwrapping of the flagellar filament from the cell body during switching of swimming trajectory. Our findings demonstrate how multiple facets ofC. jejuni’sflagella and cell plan have co-evolved for optimal motility in high-viscosity environments.
Arginase Inhibition Supports Survival and Differentiation of Neuronal Precursors in Adult Alzheimer’s Disease Mice
Authors: Polis Baruh , Gurevich Vyacheslav , Bloch Naamah , Samson Abraham O. 
Published: December 2019

AbstractAdult neurogenesis is a complex physiological process, which plays a central role in maintaining cognitive functions, and consists of progenitor cell proliferation, newborn cell migration, and cell maturation. Adult neurogenesis is susceptible to alterations under various physiological and pathological conditions. A substantial decay of neurogenesis has been documented in Alzheimer’s disease (AD) patients and animal AD models; however, several treatment strategies can halt any further decline and even induce neurogenesis.Our previous results indicated a potential effect of arginase inhibition, with norvaline, on various aspects of neurogenesis in triple-transgenic mice. To better evaluate this effect, we chronically administer an arginase inhibitor, norvaline, to triple-transgenic and wild-type mice, and apply an advanced immunohistochemistry approach with several biomarkers and bright-field microscopy.Remarkably, we evidence a significant reduction in the density of neuronal progenitors, which demonstrate a different phenotype in the hippocampi of triple-transgenic mice as compared to wild-type animals. However, norvaline shows no significant effect upon the progenitor cell number and constitution. We demonstrate that norvaline treatment leads to an escalation of the polysialylated neuronal cell adhesion molecule immunopositivity, which suggests an improvement in the newborn neuron survival rate. Additionally, we identify a significant increase in the hippocampal microtubule-associated protein 2 stain intensity. We also explore the molecular mechanisms underlying the effects of norvaline on adult mice neurogenesis and provide insights into their machinery.
Chemical transcription roadblocking for nascent RNA display
Authors: Strobel Eric J. , Lis John T. , Lucks Julius B. 
Published: December 2019

AbstractSite-specific arrest of RNA polymerase is fundamental to several technologies that measure RNA structure and function. Currentin vitrotranscription ‘roadblocking’ approaches inhibit transcription elongation using a protein blockade bound to the DNA template. One limitation of protein-mediated transcription roadblocking is that it requires the inclusion of a protein factor that is extrinsic to the minimalin vitrotranscription reaction. In this work, we show that interrupting the transcribed DNA strand with an internal desthiobiotin-triethylene glycol modification efficiently and stably haltsEscherichia coliRNA polymerase transcription. To facilitate diverse applications of chemical transcription roadblocking, we establish a simple and sequence-independent method for the preparation of internally modified double-stranded DNA templates by sequential PCR and translesion synthesis. By encoding an intrinsic stall site within the template DNA, our chemical transcription roadblocking approach enables nascent RNA molecules to be displayed from RNA polymerase in a minimalin vitrotranscription reaction.
Selective and invariant features of neural response surfaces measured with principal curvature
Authors: Golden James R. , Vilankar Kedarnath P. , Field David J. 
Published: December 2019

AbstractThe responses of most visual cortical neurons are highly nonlinear functions of image stimuli. With the sparse coding network, a recurrent model of V1 computation, we apply techniques from differential geometry to these nonlinear responses and classify them as forms of selectivity or invariance. The selectivity and invariance of responses of individual neurons are quantified by measuring the principal curvatures of neural response surfaces in high-dimensional image space. An extended two-layer version of the network model that captures some properties of higher visual cortical areas is also characterized using this approach. We argue that this geometric view allows for the quantification of feature selectivity and invariance in network models in a way that provides insight into the computations necessary for object recognition.
Prolonged reaction times help to eliminate residual errors in visuomotor adaptation
Authors: Langsdorf Lisa , Maresch Jana , Hegele Mathias , McDougle Samuel D. , Schween Raphael 
Published: December 2019

AbstractOne persistent curiosity in visuomotor adaptation tasks is that participants often do not reach maximal performance. This incomplete asymptote has been explained as a consequence of obligatory computations within the implicit adaptation system, such as an equilibrium between learning and forgetting. A body of recent work has shown that in standard adaptation tasks, cognitive strategies operate alongside implicit learning. We reasoned that incomplete learning in adaptation tasks may primarily reflect a speed-accuracy trade-off on time-consuming motor planning. Across three experiments, we find evidence supporting this hypothesis, showing that hastened motor planning may primarily lead to under-compensation. When an obligatory waiting period was administered before movement start, participants were able to fully counteract imposed perturbations (experiment 1). Inserting the same delay between trials - rather than during movement planning - did not induce full compensation, suggesting that the motor planning interval predicts the learning asymptote (experiment 2). In the last experiment, we asked participants to continuously report their movement intent. We show that emphasizing explicit re-aiming strategies (and concomitantly increasing planning time) also lead to complete asymptotic learning. Findings from all experiments support the hypothesis that incomplete adaptation is, in part, the result of an intrinsic speed-accuracy trade-off, perhaps related to cognitive strategies that require parametric attentional reorienting from the visual target to the goal.
Oxygen consumption of drift-feeding rainbow trout: the energetic tradeoff between locomotion and feeding in flow
Authors: Johansen J.L. , Akanyeti O. , Liao J.C. 
Published: December 2019

AbstractTo forage in fast, turbulent flow environments where prey are abundant, predatory fishes must deal with the high associated costs of locomotion. Prevailing theory suggests that many species exploit hydrodynamic refuges to minimize the cost of locomotion while foraging. Here we challenge this theory based on direct oxygen consumption measurements of drift-feeding trout (Oncorhynchus mykiss)foraging in the freestream and from behind a flow refuge at velocities up to 100 cm s-1. We demonstrate that refuging is not energetically beneficial when foraging in fast flows due to a high attack cost and low prey capture success associated with leaving a station-holding refuge to intercept prey. By integrating optimum foraging theory with empirical data from respirometry and video imaging, we develop a mathematical model to predict when drift-feeding fishes should exploit or avoid refuges based on prey density, size and flow velocity. Our foraging and refuging model provides new mechanistic insights into the locomotor costs, habitat use, and prey selection of fishes foraging in current-swept habitats.
Benzaldehyde Synthases Are Encoded by Cinnamoyl-CoA Reductase Genes in Cucumber (Cucumis sativusL.)
Authors: Liu Baoxiu , Wei Guo , Hu Zhongyi , Wang Guodong 
Published: December 2019

AbstractBenzaldedyde, commonly detected in plant VOC (volatile organic compounds) profiling, is derived from phenylalanine. However, the last enzymatic step for benzaldedyde formation, designated as benzaldehyde synthase, remains elusive for long time. Here, we demonstrated that cinnamoyl-CoA reductases are responsible for benzaldedyde production in cucumber (Cucumis sativusL.). Comprehensive tissue specificity of VOC profiling revealed that benzaldehyde was specifically accumulated in root and flower of cucumber plants. VOC-gene correlation analysis suggested that severalCCRs are candidate genes for benzaldehyde production:CsaCCR7had a root-specific expression pattern whileCsaCCR9andCsaCCR18showed a flower-specific expression pattern. Enzymatic assay demonstrated that CsaCCR7, CsaCCR9 and CsaCCR18 convert benzoyl-CoA to benzaldehyde. Subcellular localization experiments revealed that CsaCCR7 and CsaCCR18 are localized in cytosol, while CsaCCR9 was localized in peroxisome. In contrast to the long-standing view that CCR enzymes are involved in lignin biosynthesis in plants, it is the first time here to add a new biochemical role of CCR as benzaldehyde synthase in plants.HighlightsBenzaldehyde is mainly produced in flower and root of cucumber plants.14 genes encoding CCR enzyme from cucumber are comprehensively analyzed.Three CsaCCRs, function as benzaldehyde synthases, utilize benzoyl-CoA as substrate to produce benzaldehydein vitro.
Transgenic mouse facial nerve model of synkinesis: Original Research
Authors: Ahmed Mostafa M , Deich Alexander , Balfour Grace , Laury Adrienne , Lorin Arkady , Silliman David , Williams Richard L. 
Published: December 2019

AbstractHypothesisOur central hypothesis is that inhibition of Schwann cell de-differentiation, in the post-injury setting, will reduce synkinesis and improve facial muscle functionBackgroundNo therapies exist to improve the accuracy of facial nerve regeneration. Following peripheral nerve injury, adult reactive Schwann cells de-differentiate and express glial fibrillary acidic protein (GFAP); suggesting that reactive Schwann cells impact axonal regeneration precision.MethodsTransgenic GFAP-thymidine kinase (TK) mouse model was employed, allowing selective downregulation of reactive GFAP expressing Schwann cells on exposure of 7 day osmotic pump delivery of ganciclovir. Adult female transgenic GFAP-TK mice had right facial nerve transected and then immediately repaired with tissue glue, they then either were treated with saline or ganciclovir (GCV). At 6 weeks post-injury, mice were exposed to random air puffs events while high speed videography recorded whisker and eye movement. MatLab code video processing with publicly available BIOTACT algorithm automatically tracked whiskers.ResultsWhisker velocity was calculated using binning statistical analysis. Saline treated animals confirmed our model’s ability to detect aberrant movement such that intact (left) facial nerves caused whisker protraction, while repaired (right) facial nerves had retraction. Administration of GCV increased whisker retraction compared to saline. GCV did not impact intact animal whisker movement compared to repaired whiskers.ConclusionsInhibition of reactive Schwann cell proliferation appears to worse the degree of synkinesis, providing important insight into a potential therapeutic target for facial nerve injury.
Vineyard ecosystems are structured and distinguished by fungal communities impacting the flavour and quality of wine
Authors: Liu Di , Chen Qinglin , Zhang Pangzhen , Chen Deli , Howell Kate S. 
Published: December 2019

AbstractThe flavours of foods and beverages are formed by the agricultural environment where the plants are grown. In the case of wine, the location and environmental features of the vineyard site imprint the wine with distinctive aromas and flavours. Microbial growth and metabolism play an integral role in wine production from the vineyard to the winery, by influencing grapevine health, wine fermentation, and the flavour, aroma and quality of finished wines. The mechanism by which microbial distribution patterns drive wine metabolites is unclear and while flavour has been correlated with bacterial composition for red wines, bacterial activity provides a minor biochemical conversion in wine fermentation. Here, we collected samples across six distinct winegrowing areas in southern Australia to investigate regional distribution patterns of both fungi and bacteria and how this corresponds with wine aroma compounds. Results show that soil and must microbiota distinguish winegrowing regions and are related to wine chemical profiles. We found a strong relationship between microbial and wine metabolic profiles, and this relationship was maintained despite differing abiotic drivers (soil properties and weather/ climatic measures). Notably, fungal communities played the principal role in shaping wine aroma profiles and regional distinctiveness. We found that the soil microbiome is a potential source of grape- and must-associated fungi, and therefore the weather and soil conditions could influence the wine characteristics via shaping the soil fungal community compositions. Our study describes a comprehensive scenario of wine microbial biogeography in which microbial diversity responds to surrounding environments and ultimately sculpts wine aromatic characteristics. These findings provide perspectives for thoughtful human practices to optimise food and beverage flavour and composition through understanding of fungal activity and abundance.
iPromoter-BnCNN: a novel branched CNN based predictor for identifying and classifying sigma promoters
Authors: Amin Ruhul , Rahman Chowdhury Rafeed , Sifat Habibur Rahman , Liton Nazmul Khan , Rahman Moshiur , Ahmed Sajid , Shatabda Swakkhar 
Published: December 2019

AbstractMotivationPromoter is a short region of DNA which is responsible for initiating transcription of specific genes. Development of computational tools for automatic identification of promoters is in high demand. According to the difference of functions, promoters can be of different types. Promoters may have both intra and inter class variation and similarity in terms of consensus sequences. Accurate classification of various types of sigma promoters still remains a challenge.ResultsWe presentiPromoter-BnCNNfor identification and accurate classification of six types of promoters -σ24,σ28,σ32,σ38,σ54,σ70. It is a CNN based classifier which combines local features related to monomer nucleotide sequence, trimer nucleotide sequence, dimer structural properties and trimer structural properties through the use of parallel branching. We conducted experiments on a benchmark dataset and compared with six state-of-the-art tools to show our supremacy on 5-fold cross-validation. Moreover, we tested our classifier on an independent test dataset.AvailabilityOur proposed tool iPromoter-BnCNN web server is freely available athttp://103.109.52.8/iPromoter-BnCNN. The runnable source code can be found here.Contactrafeed@cse.uiu.ac.bdSupplementary informationSupplementary data (benchmark dataset, independent test dataset, model files, structural property information, attention mechanism details and web server usage) are available atBioinformatics. online.
Maximization of non-nitrogenous metabolite production inE. coliusing population systems biology
Authors: Rajagopal Sreenath , Ghatak Arindam , Mookherjee Debdatto , Hmar Rothangmawi Victoria , Shanbhag Anirudh P. , Katagihallimath Nainesh , Venkataraman Janani , Ramanujan KS , Datta Santanu 
Published: December 2019

AbstractTheE. colimetabolome is an interconnected set of enzymes that has measurable kinetic parameters ascribed for the production of most of its metabolites. Flux Balance Analysis (FBA) or Ordinary Differential Equation (ODE) models are used to increase product yield using defined media. However, they either give a range (FBA) or exact amount (ODE) of metabolite yield which isn’t true as the transcriptome diversity of individual cells isn’t considered. We formulate the metabolic-behaviour of individual cells by using a POpulation SYstems-Biology ALgorithm (POSYBAL) which predicts multiple-gene knockouts for increasing industrially relevant metabolites. We validate this prediction for producing isobutanol (Heterogenous metabolite) and shikimate (Homogenous metabolite) where, the product-yield was increased by 40 times (~2000 ppm) and 42 times (~3000 ppm) respectively. Also, we introduce a nitrogen-swap in standard media to its low-nitrogen counterpart during post-growth phase to redistribute flux towards non-nitrogenous pathways for increasing overall product-yield. Further, our model shows growth-phase diversity in bacterial population even under normal glucose-uptake, portraying a real-world scenario of diverse and robust environment thus, making it evolutionarily favourable to threats such as anti-bacterial attack.
Computations, optimization and tuning of deep feedforward neural networks
Authors: Rahman Md. Shoaibur 
Published: December 2019

AbstractThis article presents an overview of the generalized formulations of the computations, optimization, and tuning of a deep feedforward neural network. A small network has been used to systematically explain the computing steps, which were then used to establish the generalized forms of the computations in forward and backward propagations for larger networks. Additionally, some of the commonly used cost functions, activation functions, optimization algorithms, and hyper-parameters tuning approaches have been discussed.
Neuropeptide VF neurons promote sleep via the serotonergic raphe
Authors: Lee Daniel A. , Oikonomou Grigorios , Cammidge Tasha , Hong Young , Prober David A. 
Published: December 2019

ABSTRACTAlthough several sleep-regulating neurons have been identified, little is known about how they interact with each other for sleep/wake control. We previously identified neuropeptide VF (NPVF) and the hypothalamic neurons that produce it as a sleep-promoting system (Lee et al., 2017). Here we use zebrafish to describe a neural circuit in whichneuropeptide VF(npvf)-expressing neurons control sleep via the serotonergic raphe nuclei (RN), a hindbrain structure that promotes sleep in both diurnal zebrafish and nocturnal mice. Using genetic labeling and calcium imaging, we show thatnpvf-expressing neurons innervate and activate serotonergic RN neurons. We additionally demonstrate that optogenetic stimulation ofnpvf-expressing neurons induces sleep in a manner that requires NPVF and is abolished when the RN are ablated or lack serotonin. Finally, genetic epistasis demonstrates that NPVF acts upstream of serotonin in the RN to maintain normal sleep levels. These findings reveal a novel hypothalamic-hindbrain circuit for sleep/wake control.
Statistical agnostic mapping: a framework in neuroimaging based on concentration inequalities
Authors: Gorriz J.M. ,   SiPBA Group,   Cam Neuroscience Group,   International Initiatives
Published: December 2019

ABSTRACTIn the 70s a novel branch of statistics emerged focusing its effort in selecting a function in the pattern recognition problem, which fulfils a definite relationship between the quality of the approximation and its complexity. These data-driven approaches are mainly devoted to problems of estimating dependencies with limited sample sizes and comprise all the empirical out-of sample generalization approaches, e.g. cross validation (CV) approaches. Although the latter arenot designed for testing competing hypothesis or comparing different modelsin neuroimaging, there are a number of theoretical developments within this theory which could be employed to derive a Statistical Agnostic (non-parametric) Mapping (SAM) at voxel or multi-voxel level. Moreover, SAMs could relieve i) the problem of instability in limited sample sizes when estimating the actual risk via the CV approaches, e.g. large error bars, and provide ii) an alternative way of Family-wise-error (FWE) corrected p-value maps in inferential statistics for hypothesis testing. In this sense, we propose a novel framework in neuroimaging based on concentration inequalities, which results in (i) a rigorous development for model validation with a small sample/dimension ratio, and (ii) a less-conservative procedure than FWE p-value correction, to determine the brain significance maps from the inferences made using small upper bounds of the actual risk.
CSF1R inhibition by a small molecule inhibitor affects hematopoiesis and the function of macrophages
Authors: Lei Fengyang , Cui Naiwen , Zhou Chengxin , Chodosh James , Vavvas Demetrios G. , Paschalis Eleftherios I. 
Published: December 2019

AbstractColony-stimulating factor 1 receptor (CSF1R) inhibition has been proposed as a method for microglia depletion, with the assumption that it does not affect peripheral immune cells. Here, we show that CSF1R inhibition by PLX5622 indeed affects the myeloid and lymphoid compartments, causes long-term changes in bone marrow-derived macrophages by suppressing their IL-1β, CD68 and phagocytosis, but not CD208, following exposure to endotoxin, and also reduces the population of tissue resident macrophages of peritoneum, lung, liver, but not spleen. Thus, small molecule CSF1R inhibition is not restricted to microglia only, but rather causes strong effects on circulating and tissue macrophages that perdure long after cessation of the treatment. Given that peripheral monocytes repopulate the CNS after CSF1R inhibition, these changes may have practical implications on relevant experimental data.