bluuebunny/crossref_metadata_2025_split huggingface dataset:
Episodic memory retrieval success is associated with rapid replay of episode content
Authors: Wimmer G. Elliott , Liu Yunzhe , Vehar Neža , Behrens Timothy E.J. , Dolan Raymond J. 
Published: September 2019

AbstractMemory for everyday experience shapes our representation of the structure of the world, while retrieval of these experiences is fundamental for informing our future decisions. The fine-grained neurophysiological mechanisms that support such retrieval are largely unknown. We studied participants who first experienced, without repetition, unique multi-component episodes. One day later, they engaged in cued retrieval of these episodes whilst undergoing magnetoencephalography (MEG). By decoding individual episode elements, we found that trial-by-trial successful retrieval was supported by sequential replay of episode elements, with a temporal compression factor greater than 60. The direction of replay supporting this retrieval, either backward or forward, depended on whether a participant’s goal was to retrieve elements of an episode that followed or preceded a retrieval cue, respectively. This sequential replay was weaker in very high performing participants, where instead we found evidence for simultaneous clustered reactivation. Our results demonstrate that memory-mediated decisions are supported by a rapid replay mechanism that can flexibly shift in direction in response to task requirements.One Sentence SummaryRecall of extended episodes of experience is supported by compressed replay of memory elements that flexibly changes direction depending on task temporal orientation.
Surveying the sweetpotato rhizosphere, endophyte, and surrounding soil microbiomes at two North Carolina farms reveals underpinnings of sweetpotato microbiome community assembly
Authors: Pepe-Ranney C , Keyser C , Trimble J , Bissinger B 
Published: September 2019

AbstractFarmers grow sweetpotatoes worldwide and some sub-Saharan African and Asian diets include sweetpotato as a staple, yet the sweetpotato microbiome is conspicuously less studied relative to crops such as maize, soybean, and wheat. Studying sweetpotato microbiome ecology may reveal paths to engineer the microbiome to improve sweetpotato yield, and/or combat sweetpotato pests and diseases. We sampled sweetpotatoes and surrounding soil from two North Carolina farms. We took samples from sweetpotato fields under two different land management regimes, conventional and organic, and collected two sweetpotato cultivars, ‘Beauregard’ and ‘Covington’. By comparing SSU rRNA gene amplicon sequence profiles from sweetpotato storage root skin, rhizosphere, and surrounding soil we found the skin microbiome possessed the least composition heterogeneity among samples and lowest alpha-diversity and was significantly nested by the rhizosphere in amplicon sequence variant (ASV) membership. Many ASVs were specific to a single field and/or only found in either the skin, rhizosphere, or surrounding soil. Notably, sweetpotato skin enriched forPlanctomycetaceaein relative abundance at both farms. This study elucidates underpinnings of sweetpotato microbiome community assembly, quantifies microbiome composition variance within a single farm, and reveals microorganisms associated with sweetpotato skin that belong to common but uncultured soil phylotypes.
Intrinsic base substitution patterns in diverse species reveal links to cancer and metabolism
Authors: Gelova Suzana P. , Doherty Kassidy N. , Alasmar Salma , Chan Kin 
Published: September 2019

AbstractAnalyses of large-scale sequencing data reveal that mutagenic processes create distinctive patterns of base substitutions, called mutational signatures. Here, we analyzed substitution patterns from seven model species and single nucleotide polymorphisms (SNPs) in 42 species, totalling >1.9 billion variants. We found that the base substitution patterns for many species most closely match mutational signature 5 in cancers. Signature 5 is also ubiquitous in cancers and normal human cells, suggesting similar patterns of mutation across species are likely due to conserved biochemistry. Finally, we present evidence from yeast that sugar metabolism is directly linked to this form of DNA damage. We propose that conserved metabolic processes in cells are coupled to continuous generation of mutations, which are acted upon by genetic selection to drive the evolution of species, and cancers.One Sentence SummaryEnergy metabolism produces DNA damage leading to similar patterns of base substitutions in many species and in human cancers.
Metabolic insight into bacterial community assembly across ecosystem boundaries
Authors: Wisnoski Nathan I. , Muscarella Mario E. , Larsen Megan L. , Peralta Ariane L. , Lennon Jay T. 
Published: September 2019

ABSTRACTThe movement of organisms across habitat boundaries has important consequences for populations, communities, and ecosystems. However, because most species are not well adapted to all habitat types, dispersal into suboptimal habitats could induce physiological changes associated with persistence strategies that influence community assembly. For example, high rates of cross-boundary dispersal are thought to maintain sink populations of terrestrial bacteria in aquatic habitats, but these bacteria may also persist by lowering their metabolic activity, introducing metabolic heterogeneity that buffers the population against niche selection. To differentiate between these assembly processes, we analyzed bacterial composition along a hydrological flow path from terrestrial soils through an aquatic reservoir by sequencing the active and total (active + inactive) portions of the community. When metabolic heterogeneity was ignored, our data were consistent with views that cross-boundary dispersal is important for structuring aquatic bacterial communities. In contrast, we found evidence for strong niche selection when metabolic heterogeneity was explicitly considered, suggesting that, relative to persistence strategies, dispersal may have a weaker effect on aquatic community assembly than previously thought. By accounting for metabolic heterogeneity in complex communities, our findings clarify the roles of local- and regional-scale assembly processes in terrestrial-aquatic meta-ecosystems.
Neuromodulation of pelvic nerve during early phase of spinal cord injury in rats using implantable prototype devices - a preliminary study
Authors: Peh Wendy Yen Xian , Alam Monzurul , Ahmed Rakib Uddin , Lee Sanghoon , Ong Li Jing , Lu Shuhao , Mogan Roshini , Gammad Gil Gerald Lasam , Ng Kian Ann , Rusly Astrid , Nag Sudip , Zheng Yong-Ping , Yen Shih-Cheng 
Published: September 2019

AbstractObjectivesThe bladder becomes retentive during the early phase of spinal cord injury, and requires proper bladder management to prevent damage to the lower urinary tract and kidney. We investigated the effects of on-demand pelvic nerve stimulation on the areflexive bladder during the earliest phase of complete spinal cord injury in rats and the use of pelvic nerve signals as a proxy to estimate intravesical pressure for closed-loop applications.Materials and MethodsIn order to stimulate the pelvic nerves in female Sprague-Dawley rats with complete spinal cord transection (T7 level), a flexible electrode was implanted unilaterally on pelvic nerve, and electrical stimulation was provided by a custom-built nerve stimulator. Stimulation-evoked voiding was monitored in the awake state while size, capacity and spontaneous contractions of the bladder were analysed under anaesthesia. Separately, recordings of the pelvic nerve signals, external urethral sphincter activity and intravesical pressure were performed in animals with intact and transected spinal cord under anaesthesia.ResultsSuccessful pelvic nerve stimulation enabled more frequent voiding, reduced overdistension of bladder, and preserved non-voiding spontaneous bladder contractions. Typical bladder management protocol for SCI rats (manual expression every 8 – 12 hours) resulted in more severe bladder overdistention. Signal processing of the recorded extraneural pelvic nerve signals successfully reconstructed changes in intravesical pressure, demonstrating their use in estimating the fullness and contractions of the bladder.ConclusionsThe preliminary results suggest that pelvic nerve stimulators can serve as an alternative method for frequent emptying of the areflexive bladder. Simultaneous recording of the same pelvic nerve will be useful for development of a closed-loop neuroprosthesis.
How to choose sets of ancestry informative markers: A supervised feature selection approach
Authors: Pfaffelhuber Peter , Grundner-Culemann Franziska , Lipphardt Veronika , Baumdicker Franz 
Published: September 2019

AbstractInference of the Biogeographical Ancestry (BGA) of a person or trace relies on three ingredients: (1) A reference database of DNA samples including BGA information; (2) a statistical clustering method; (3) a set of loci which segregate dependent on geographical location, i.e. a set of so-called Ancestry Informative Markers (AIMs). We used the theory of feature selection from statistical learning in order to obtain AIM-sets for BGA inference. Using simulations, we show that this learning procedure works in various cases, and outperforms ad hoc methods, based on statistics likeFSTor informativeness for the choice of AIMs. Applying our method to data from the 1000 genomes project (excluding Admixed Americans) we identified an AIMset of 17 SNPs, which partly overlaps with existing ones. For continental BGA, the AIMset outperforms existing AIMsets on the 1000 genomes dataset, and gives a vanishing misclassification error.
Over eight hundred cannabis strains characterized by the relationship between their psychoactive effects, perceptual profiles, and chemical compositions
Authors: de la Fuente Alethia , Zamberlan Federico , Ferrán Andrés Sánchez , Carrillo Facundo , Tagliazucchi Enzo , Pallavicini Carla 
Published: September 2019

AbstractBackgroundCommercially available cannabis strains have multiplied in recent years as a consequence of regional changes in legislation for medicinal and recreational use. Lack of a standardized system to label plants and seeds hinders the consistent identification of particular strains with their elicited psychoactive effects. The objective of this work was to leverage information extracted from large databases to improve the identification and characterization of cannabis strains.MethodsWe analyzed a large publicly available dataset where users freely reported their experiences with cannabis strains, including different subjective effects and flavour associations. This analysis was complemented with information on the chemical composition of a subset of the strains. Both supervised and unsupervised machine learning algorithms were applied to classify strains based on self-reported and objective features.ResultsMetrics of strain similarity based on self-reported effect and flavour tags allowed machine learning classification into three major clusters corresponding toCannabis sativa,Cannabis indica, and hybrids. Synergy between terpene and cannabinoid content was suggested by significative correlations between psychoactive effect and flavour tags. The use of predefined tags was validated by applying semantic analysis tools to unstructured written reviews, also providing breed-specific topics consistent with their purported medicinal and subjective effects. While cannabinoid content was variable even within individual strains, terpene profiles matched the perceptual characterizations made by the users and could be used to predict associations between different psychoactive effects.ConclusionsOur work represents the first data-driven synthesis of self-reported and chemical information in a large number of cannabis strains. Since terpene content is robustly inherited and less influenced by environmental factors, flavour perception could represent a reliable marker to predict the psychoactive effects of cannabis. Our novel methodology contributes to meet the demands for reliable strain classification and characterization in the context of an ever-growing market for medicinal and recreational cannabis.
MAP Kinase inhibition reshapes tumor microenvironment of mouse pancreatic cancer by depleting anti-inflammatory macrophages
Authors: Delfino Pietro , Neander Christian , Filippini Dea , D’Agosto Sabrina L. , Vicentini Caterina , Fiorini Elena , Lupo Francesca , Fiorini Claudia , Rusev Borislav , Temgue Tane Gael D. , De Sanctis Francesco , Simbolo Michele , Ugel Stefano , Bronte Vincenzo , Fassan Matteo , Lawlor Rita T. , Boschi Federico , Barbi Stefano , Scarpa Aldo , Cheung Phyllis F. , Siveke Jens T. , Corbo Vincenzo 
Published: September 2019

ABSTRACTThe RAF/MEK/ERK (MAP Kinase) pathway is the index oncogenic signaling towards which many compounds have been developed and tested for the treatment of KRAS-driven cancers, including pancreatic ductal adenocarcinoma (PDA). Here, we explored the immunological changes induced by targeted MEK1/2 inhibition (MEKi) using trametinib in preclinical mouse models of PDA. We evaluated the dynamic changes in the immune contexture of mouse PDA upon MEKi using a multidimensional approach (mRNA analyses, flow cytometry, and immunophenotyping). Effect of MEKi on the viability and metabolism of macrophages was investigated in vitro. We showed that transcriptional signatures of MAP Kinase activation are enriched in aggressive human PDA subtype (squamous/basal-like/quasimesenchymal), while short term MEKi treatment in mouse PDA induced subtype switching. Integrative mRNA expression and immunophenotypic analyses showed that MEKi reshapes the immune landscape of PDA by depleting rather than reprogramming macrophages, while augmenting infiltration by neutrophils. Depletion of macrophages is observed early in the course of in vivo treatment and is at least partially due to their higher sensitivity to MEKi. Tumor-associated macrophages were consistently reported to interfere with gemcitabine uptake by PDA cells. Here, our in vivo studies show a superior antitumor activity upon combination of MEKi and gemcitabine using a sequential rather than simultaneous dosing protocol. Our results show that MEK inhibition induces a dramatic remodeling of the tumor microenvironment of mouse PDA through depletion of macrophages, which substantially improves the antitumor activity of gemcitabine.
Understanding the effect of temperature on Bluetongue disease risk in livestock
Authors: El Moustaid Fadoua , Thronton Zorian , Slamani Hani , Ryan Sadie J. , Johnson Leah R. 
Published: September 2019

AbstractThe transmission of vector-borne diseases is governed by complex factors including pathogen characteristics, vector-host interactions, and environmental conditions. Temperature is a major driver for many vector-borne diseases including Bluetongue viral (BTV) disease, a midge-borne febrile disease of ruminants, notably livestock, whose etiology ranges from mild or asymptomatic to rapidly fatal, thus threatening animal agriculture and the economy of affected countries. Using modeling tools, we seek to predict where transmission can occur based on suitable temperatures for BTV. We fit thermal performance curves to temperature sensitive midge life history traits, using a Bayesian approach. Then, we incorporated these into a new formula for the disease basic reproductive number,R0, to include trait responses, for two species of key midge vectors,Culicoides sonorensisandCulicoides variipennis. Our results show that outbreaks of BTV are more likely between 15°C and 33°C with predicted peak transmission at 26°C. The greatest uncertainty inR0is associated with the uncertainty in: mortality and fecundity of midges near optimal temperature for transmission; midges’ probability of becoming infectious post infection at the lower edge of the thermal range; and the biting rate together with vector competence at the higher edge of the thermal range. We compare ourR0to two otherR0formulations and show that incorporating thermal curves into all three leads to similar BTV risk predictions. To demonstrate the utility of this model approach, we created global suitability maps indicating the areas at high and long-term risk of BTV transmission, to assess risk, and anticipate potential locations of establishment.
Neural hierarchical models of ecological populations
Authors: Joseph Maxwell B. 
Published: September 2019

AbstractNeural networks are increasingly being used in science to infer hidden dynamics of natural systems from noisy observations, a task typically handled by hierarchical models in ecology. This paper describes a class of hierarchical models parameterized by neural networks: neural hierarchical models. The derivation of such models analogizes the relationship between regression and neural networks. A case study is developed for a neural dynamic occupancy model of North American bird populations, trained on millions of detection/non-detection time series for hundreds of species, providing insights into colonization and extinction at a continental scale. Flexible models are increasingly needed that scale to large data and represent ecological processes. Neural hierarchical models satisfy this need, providing a bridge between deep learning and ecological modeling that combines the function representation power of neural networks with the inferential capacity of hierarchical models.
Subjective value, not a gridlike code, describes neural activity in ventromedial prefrontal cortex during value-based decision-making
Authors: Lee Sangil , Yu Linda Q. , Lerman Caryn , Kable Joseph W. 
Published: September 2019

AbstractAcross many studies, ventromedial prefrontal cortex (vmPFC) activity has been found to correlate with subjective value during value-based decision-making. Recently, however, vmPFC has also been shown to reflect a hexagonal gridlike code during navigation through physical and conceptual space. This raises the possibility that the subjective value correlates previously observed in vmPFC may have actually been a misconstrued gridlike signal. Here, we first show that, in theory, a hexagonal gridlike code of two-dimensional attribute space could mimic vmPFC activity previously attributed to subjective value. However, using fMRI data from a large number of subjects performing an intertemporal choice task, we show clear and unambiguous evidence that subjective value is a better description of vmPFC activity than a hexagonal gridlike code. In fact, we find no significant evidence at all for a hexagonal gridlike code in vmPFC activity during intertemporal choice. This result limits the generality of gridlike modulation as description of vmPFC activity. We suggest that vmPFC may flexibly switch representational schemes so as to encode the most relevant information for the current task.
Effects of feeding treatment on growth rate and performance of primiparous Holstein dairy heifers
Authors: Le Cozler Yannick , Jurquet Julien , Bedere Nicolas. 
Published: September 2019

AbstractThe objective of this study was to investigate effects of feeding-rearing programs that aim for first calving at 20-27 months (mo) of age on growth, reproduction and production performance of Holstein cows at nulliparous and primiparous stages. We hypothesised that, in a seasonal autumn-calving strategy, heifers born late in the season could catch up to the growth of heifers born earlier and be inseminated during the same period, at a body weight (BW) of at least 370 kg. This approach would result in first calving age at 21-22 mo of age without impairing their later performance. To test this hypothesis, we studied 217 heifers over 3 years. They were split into three treatment groups: control feeding (SD), an intensive-plane diet (ID1) from birth to 6 mo of age or an intensive-plane diet from birth to one year of age. Heifers in groups SD and ID1 were born from September until the end of November, while those in ID2 were born later. The present study showed that late-born heifers (ID2) could catch up with the growth of the others due to the feeding treatment, although they were still 42 kg lighter than the SD and ID1 heifers at first calving. No difference in reproductive performance was observed among groups. Once primiparous, the cows reared with the ID2 treatment tended to produce less milk than SD and ID1 cows (ca. 400 kg less on a 305 d basis throughout lactation), and no differences in milk composition, feed intake, body condition score or BW were observed among groups. Age at first service (AFS) was classified a posteriori into three classes: 12.5 (AFS12.5), 14.0 (AFS14.0) and 15.5 mo (AFS15.5) of age. Heifers in AFS12.5 grew faster than those in AFS14.0 and AFS15.5. Once primiparous, the AFS12.5 cows tended to produce less milk at peak than AFS14.0 and AFS15.5 cows (ca. 1.5 kg/d less) although no difference in total milk yield during lactation was observed. No differences in milk composition, feed intake, body condition score or BW were observed among groups. These results support the conclusion that the feeding treatment can enable late-born heifers to catch up to the growth of heifers born earlier in the season. This strategy results in an earlier first calving that does not impair their reproductive performance but does decrease milk yield slightly during first lactation. Future studies should investigate long-term effects of this strategy.
Platelet proteolytic machinery assessment in Alzheimer’s Diseases
Authors: Muriu Roy G. , Sage Jessica M. , Agbas Abdulbaki 
Published: September 2019

AbstractAimPlatelets provide substantial information about the proteolytic system profile in neurodegenerative diseases. Assessment of autophagy and proteasome target proteins in platelets may reflect tissue proteolytic machinery profile in central nervous system in Alzheimer’s diseases (AD). We aimed to demonstrate the optimum assay conditions and identify target proteins in platelet proteolytic machinery.MethodsPlatelet samples were obtained from clinically verified AD patients and age-matched non-demented control subjects that were recruited by University of Kansas Alzheimer’s disease Center.Autophagosome participating proteins in platelets were identified by Western blotting analysis. Standard gel electrophoresis and electro transfer apparatus were used for protein transfer onto the membrane. Several antibodies were tested to identify the best working antibodies, and their concentrations were optimized. An ELISA kit was used for platelet proteasome protein determination. Infrared imaging technology was used for visualizing the proteins on the membrane.ResultsAutophagosome participating proteins showed elevated levels in AD patient platelet cytosol. Only LC3-I autophagosome protein levels were significantly elevated. The concentrations of platelet lysate proteasome were assessed. AD patient’s proteasome levels were elevated but they were statistically not important as compared to controls.ConclusionsPlatelets can be used for assessing whether proteolytic system is functional. Blood-based sampling from human donors is less-invasive and analyzing platelet proteolytic system profile may help to develop pharmaceutical intervention approaches for neurodegenerative diseases in general.