bluuebunny/crossref_metadata_2025_split huggingface dataset:
Postnatal functional inactivation of the ventral subiculum enhances dopaminergic responses in the core part of the nucleus accumbens following ketamine injection in adult rats
Authors: Saoud Hana , De Beus Duco , Eybrard Séverine , Louilot Alain 
Published: December 2019

AbstractFor almost two decades schizophrenia has been considered to be a functional disconnection disorder. This functional disconnectivity between several brain regions could have a neurodevelopmental origin. Various approaches suggest the ventral subiculum (SUB) is a particular target region for neurodevelopemental disturbances in schizophrenia. It is also commonly acknowledged that there is a striatal dopaminergic (DA) dysregulation in schizophrenia which may depend on a subiculo-striatal disconnection involving glutamatergic NMDA receptors.The present study was designed to investigate, in adult rats, the effects of the non-competitive NMDA receptor antagonist ketamine on DA responses in the ventral striatum, or, more specifically, the core part of the nucleus accumbens (Nacc), following postnatal functional inactivation of the SUB. Functional inactivation of the left SUB was carried out by local tetrodotoxin (TTX) microinjection at postnatal day 8 (PND8), i.e. at a critical point in the neurodevelopmental period. DA variations were recorded using in vivo voltammetry in freely moving adult rats (11 weeks). Locomotor activity was recorded simultaneously with the extracellular levels of DA in the core part of the Nacc. Data obtained during the present study showed that after administration of ketamine, the two indexes were higher in TTX animals than PBS animals, the suggestion being that animals microinjected with TTX in the left SUB at PND8 present greater reactivity to ketamine than animals microinjected with PBS. These findings could provide new information regarding the involvement of NMDA glutamatergic receptors in the core part of the Nacc in the pathophysiology of schizophrenia.
Intermittent access cocaine self-administration produces psychomotor sensitization: effects of withdrawal, sex and cross-sensitization
Authors: Carr Crystal C. , Ferrario Carrie R. , Robinson Terry E. 
Published: December 2019

AbstractThe psychomotor activating effects of drugs such as cocaine or amphetamine can change in very different ways – showing sensitization or tolerance – depending on whether they are administered more or less intermittently. This behavioral plasticity is thought to reflect, at least in part, changes in dopamine (DA) neurotransmission, and therefore, may provide insights into how repeated drug use promotes the development of substance use disorders. Indeed, the most widely used preclinical model of cocaine addiction, which involves Long Access (LgA) self-administration procedures, is reported to produce tolerance to cocaine’s psychomotor activating effects and effects on DA activity. This is cited as evidence in support of the view that in addiction, drug-seeking and-taking is motivated to overcome this DA deficiency and associated anhedonia. In contrast, Intermittent Access (IntA) cocaine self-administration is more effective than LgA in producing addiction-like behavior, but sensitizes DA neurotransmission. There is, however, very little information concerning the effects of IntA experience on the psychomotor activating effects of cocaine. The purpose of the studies reported here, therefore, was to determine whether IntA experience produces psychomotor sensitization with similar characteristics to that produced by the intermittent, noncontingent administration of cocaine. It did. The psychomotor sensitization produced by IntA experience with cocaine: (1) was greater after a long (30 days) vs short (1 day) period of withdrawal; (2) was greater in females than males; and (3) resulted in cross-sensitization to another psychomotor stimulant drug, amphetamine. This pattern of cocaine experience-dependent plasticity favors an incentive-sensitization view of addiction.
Revisiting the Global Workspace: Orchestration of the functional hierarchical organisation of the human brain
Authors: Deco Gustavo , Vidaurre Diego , Kringelbach Morten L. 
Published: December 2019

AbstractA central, unsolved challenge in neuroscience is how the brain orchestrates function by organising the flow of information necessary for the underlying computation. It has been argued that this whole-brain orchestration is carried out by a core subset of integrative brain regions, commonly referred to as the ‘global workspace’, although quantifying the constitutive brain regions has proven elusive. We developed a normalised directed transfer entropy (NDTE) framework for determining the pairwise bidirectional causal flow between brain regions and applied it to multimodal whole-brain neuroimaging from over 1000 healthy participants. We established the full brain hierarchy and common regions in a ‘functional rich club’ (FRIC) coordinating the functional hierarchical organisation during rest and task. FRIC contains the core set of regions, which similar to a ‘club’ of functional hubs are characterized by a tendency to be more densely functionally connected among themselves than to the rest of brain regions from where they integrate information. The invariant global workspace is the intersection of FRICs across rest and seven tasks, and was found to consist of the precuneus, posterior and isthmus cingulate cortices, nucleus accumbens, putamen, hippocampus and amygdala that orchestrate the functional hierarchical organisation based on information from perceptual, long-term memory, evaluative and attentional systems. We confirmed the causal significance and robustness of this invariant global workspace by systematically lesioning a generative whole-brain model accurately simulating the functional hierarchy defined by NDTE. Overall, this is a major step forward in understanding the complex choreography of information flow within the functional hierarchical organisation of the human brain.
Artificial upward trends in Greek marine landings: a case of presentist bias in European fisheries
Authors: Tsikliras Athanassios C. , Dimarchopoulou Donna , Pardalou Androniki 
Published: December 2019

AbstractAccording to the official landings as reported by the international databases for Greece, the declining trend of the Greek marine fisheries landings that had been continuous since the mid 1990s has been reversed during the last two years, with the total marine fisheries landings showing elevated catches after 2016. We claim that this upward trend is an artifact that is attributed to the combined reporting of the landings of additional fleets since 2016 that had been separately reported before and resulted in 20-30% inflation of the landings. In 2016, the Greek statistical authorities included the landings of 10 000 small-scale coastal vessels with engine horsepower lower than 20 HP together with the remaining coastal vessels, purse-seiners and trawlers whose landings formed the official reported Greek marine fisheries landings from 1970 to 2015. We acknowledge that this act of partial catch reconstruction improved the resolution of the landings and the officially reported values are now more realistic. However, the artificial, albeit inadvertent, inflation of the official Greek marine fisheries landings as they appear in international databases is a clear case of ‘presentist bias’ and may distort stock assessments and ecosystem modeling. As the currently misleading data stand, they are cause for substantial misinterpretation and analytical errors that can influence fisheries policy and have serious implications for fisheries management. We suggest that researchers should refrain from using the combined time-series and that a correction should be applied to the original time series (1970-2015) to account for the entire small-scale coastal fleet.
Information content of cheek and lip colour in relation to the timing of ovulation in women
Authors: Rigaill Lucie 
Published: December 2019

AbstractVarious animal species have evolved a sexual communication system with females displaying and males discriminating information about the timing of ovulation through sexual signals. More research is now investigating the potential ovulatory signalling function of female red skin colour in human and non-human primates. However, to date it is still challenging to draft satisfying hypotheses about the evolution and function of female red skin colour, due to methodological discrepancies between human and non-human primate studies. The present study used a within-individual design and objective methods to analyse the relationship between fine-scale variation in cheek and lip colour (luminance and redness) and the estimated day of ovulation in 15 cycling women. Lip, but not cheek, colour appeared to contain information about the timing of ovulation, with lips getting darker around ovulation. This study adds to the growing evidence that female red skin colour may play a role in sexual signalling in human and non-human primates but also underlines variation in trait forms and functions at the species-level.
Phylogenomic analysis of the APETALA2 transcription factor subfamily across angiosperms reveals both deep conservation and lineage-specific patterns
Authors: Kerstens Merijn H.L. , Schranz M. Eric , Bouwmeester Klaas 
Published: December 2019

ABSTRACTThe APETALA2 (AP2) subfamily of transcription factors are key regulators of angiosperm root, shoot, flower, and embryo development. The broad diversity of anatomical and morphological structures is potentially associated with the genomic dynamics of theAP2subfamily. However, a comprehensive phylogenomic analysis of theAP2subfamily across angiosperms is lacking. We combined phylogenetic and synteny analysis of distinctAP2subclades in the completed genomes of 107 angiosperm species. We identified major changes in copy number variation and genomic context within subclades across lineages, and discuss how these changes may have contributed to the evolution of lineage-specific traits. MultipleAP2subclades show highly conserved patterns of copy number and synteny across angiosperms, while others are more dynamic and show distinct lineage-specific patterns. As examples of lineage-specific morphological divergence due toAP2subclade dynamics, we hypothesize that that loss ofPLETHORA1/2in monocots correlates with the absence of taproots, whereas independent lineage-specific changes ofPLETHORA4/BABY BOOMandWRINKLED1genes in Brassicaceae and monocots point towards regulatory divergence of embryogenesis between these lineages. Additionally, copy number expansion ofTOE1andTOE3/AP2in asterids is implicated with differential regulation of flower development. Moreover, we show that the genomic context ofAP2s is in general highly specialised per angiosperm lineage. Our study is the first to shed light on the evolutionary divergence of theAP2subfamily subclades across major angiosperm lineages and emphasises the need for lineage-specific characterisation of developmental networks to further understand trait variability.SIGNIFICANCE STATEMENTAPETALA2 transcription factors are crucial regulators of embryogenesis and post-embryonic development in plants. Characterising the genomic dynamics ofAPETALA2genes across 107 angiosperms provided evolutionary insights into gene-family and morphological divergence across major angiosperm lineages.
Paracrine and autocrine R-spondin signalling is essential for the maintenance and differentiation of renal stem cells
Authors: Vidal V.P.I. , Gregoire E. , Szenker-Ravi E. , Leushacke M. , Reversade B. , Chaboissier MC. , Schedl A. 
Published: December 2019

AbstractDuring kidney development, WNT/β-catenin signalling has to be tightly controlled to ensure proliferation and differentiation of renal stem cells. Here we show that the two signalling molecules RSPO1 and RSPO3 act in a functionally redundant manner to permit WNT/β-catenin signalling and their genetic deletion leads to a rapid decline of renal progenitors. By contrast, tissue specific deletion in cap mesenchymal cells abolishes mesenchyme to epithelial transition (MET) that is linked to a loss ofBmp7expression, absence of SMAD1/5 phosphorylation and a concomitant failure to activateLef1, Fgf8andWnt4, thus explaining the observed phenotype on a molecular level. Surprisingly, the full knockout of LGR4/5/6, the cognate receptors of R-spondins, only mildly affects progenitor numbers, but does not interfere with MET. Taken together our data demonstrate key roles for R-spondins in permitting stem cell maintenance and differentiation and revealLgr-dependent and independent functions for these ligands during kidney formation.
MAtCHap: an ultra fast algorithm for solving the single individual haplotype assembly problem
Authors: Magi Alberto 
Published: December 2019

AbstractBackgroundHuman genomes are diploid, which means they have two homologous copies of each chromosome and the assignment of heterozygous variants to each chromosome copy, the haplotype assembly problem, is of fundamental importance for medical and population genetics.While short reads from second generation sequencing platforms drastically limit haplotype reconstruction as the great majority of reads do not allow to link many variants together, novel long reads from third generation sequencing can span several variants along the genome allowing to infer much longer haplotype blocks.However, the great majority of haplotype assembly algorithms, originally devised for short sequences, fail when they are applied to noisy long reads data, and although novel algorithm have been properly developed to deal with the properties of this new generation of sequences, these methods are capable to manage only datasets with limited coverages.ResultsTo overcome the limits of currently available algorithms, I propose a novel formulation of the single individual haplotype assembly problem, based on maximum allele co-occurrence (MAC) and I develop an ultra-fast algorithm that is capable to reconstruct the haplotype structure of a diploid genome from low- and high-coverage long read datasets with high accuracy. I test my algorithm (MAtCHap) on synthetic and real PacBio and Nanopore human dataset and I compare its result with other eight state-of-the-art algorithms. All the results obtained by these analyses show that MAtCHap outperforms other methods in terms of accuracy, contiguity, completeness and computational speed.AvailabilityMAtCHap is publicly available at https://sourceforge.net/projects/matchap/.
Developing synergistic drug combinations to restore antibiotic sensitivity in drug-resistant Mycobacterium tuberculosis
Authors: Omollo Charles , Singh Vinayak , Kigondu Elizabeth , Wasuna Antonina , Agarwal Pooja , Moosa Atica , Ioerger Thomas R. , Mizrahi Valerie , Chibale Kelly , Warner Digby F. 
Published: December 2019

ABSTRACTTuberculosis (TB) is a leading global cause of mortality owing to an infectious agent, accounting for almost one-third of antimicrobial resistance (AMR) deaths annually. We aimed to identify synergistic anti-TB drug combinations with the capacity to restore therapeutic efficacy against drug-resistant mutants of the causative agent, Mycobacterium tuberculosis. We investigated combinations containing the known translational inhibitors, spectinomycin (SPT) and fusidic acid (FA), or the phenothiazine, chlorpromazine (CPZ), which disrupts mycobacterial energy metabolism. Potentiation of whole-cell drug efficacy was observed in SPT-CPZ combinations. This effect was lost against an M. tuberculosis mutant lacking the major facilitator superfamily (MFS) efflux pump, Rv1258c. Notably, the SPT-CPZ combination restored SPT efficacy against an SPT-resistant mutant carrying a g1379t point mutation in rrs, encoding the mycobacterial 16S ribosomal RNA. Combinations of SPT with FA, which targets the mycobacterial elongation factor G, exhibited potentiating activity against wild-type M. tuberculosis. Moreover, this combination produced a marginal potentiating effect against both FA-monoresistant and SPT-monoresistant mutants. Finally, combining SPT with the frontline anti-TB agents, rifampicin (RIF) and isoniazid, resulted in enhanced activity in vitro and ex vivo against both drug-susceptible M. tuberculosis and a RIF-monoresistant rpoB S531L mutant.These results support the utility of novel potentiating drug combinations in restoring antibiotic susceptibility of M. tuberculosis strains carrying genetic resistance to any one of the partner compounds.
Genomic investigation of the strawberry pathogen Phytophthora fragariae indicates pathogenicity is associated with transcriptional variation in three key races
Authors: Adams Thomas M. , Armitage Andrew D. , Sobczyk Maria K. , Bates Helen J. , Tabima Javier F. , Kronmiller Brent A. , Tyler Brett M. , Grünwald Niklaus J. , Dunwell Jim M. , Nellist Charlotte F. , Harrison Richard J. 
Published: December 2019

ABSTRACTThe oomycete Phytophthora fragariae is a highly destructive pathogen of cultivated strawberry (Fragaria × ananassa), causing the root rotting disease, ‘red core’. The host-pathogen interaction has a well described gene-for-gene resistance relationship, but to date neither candidate avirulence nor resistance genes have been identified. We sequenced a set of American, Canadian and UK isolates of known race type, along with three representatives of the closely related pathogen of the raspberry (Rubus idaeus), Phytophthora rubi, and found a clear population structure, with a high degree of nucleotide divergence seen between some race types and abundant private variation associated with race types 4 and 5. In contrast, between isolates defined as UK races 1, 2 & 3 (UK1-2-3) there was no evidence of gene loss or gain; or the presence of insertions/deletions (INDELs) or Single Nucleotide Polymorphisms (SNPs) within or in proximity to putative pathogenicity genes could be found associated with race variation. Transcriptomic analysis of representative UK1-2-3 isolates revealed abundant expression variation in key effector family genes associated with pathogen race; however, further long read sequencing did not reveal any long range polymorphisms to be associated with avirulence to race UK2 or UK3 resistance, suggesting either control in trans or other stable forms of epigenetic modification modulating gene expression. This work reveals the combined power of population resequencing to uncover race structure in pathosystems and in planta transcriptomic analysis to identify candidate avirulence genes. This work has implications for the identification of putative avirulence genes in the absence of associated expression data and points towards the need for detailed molecular characterisation of mechanisms of effector regulation and silencing in oomycete plant pathogens.
Machine learning on drug-specific data to predict small molecule teratogenicity
Authors: Challa Anup P. , Beam Andrew L. , Shen Min , Peryea Tyler , Lavieri Robert R. , Lippmann Ethan S. , Aronoff David M. 
Published: December 2019

AbstractPregnant women are an especially vulnerable population, given the sensitivity of a developing fetus to chemical exposures. However, prescribing behavior for the gravid patient is guided on limited human data and conflicting cases of adverse outcomes due to the exclusion of pregnant populations from randomized, controlled trials. These factors increase risk for adverse drug outcomes and reduce quality of care for pregnant populations. Herein, we propose the application of artificial intelligence to systematically predict the teratogenicity of a prescriptible small molecule from information inherent to the drug. Using unsupervised and supervised machine learning, our model probes all small molecules with known structure and teratogenicity data published in research-amenable formats to identify patterns among structural, meta-structural, and in vitro bioactivity data for each drug and its teratogenicity score. With this workflow, we discovered three chemical functionalities that predispose a drug towards increased teratogenicity and two moieties with potentially protective effects. Our models predict three clinically-relevant classes of teratogenicity with AUC = 0.8 and nearly double the predictive accuracy of a blind control for the same task, suggesting successful modeling. We also present extensive barriers to translational research that restrict data-driven studies in pregnancy and therapeutically “orphan” pregnant populations. Collectively, this work represents a first-in-kind platform for the application of computing to study and predict teratogenicity.
TNFPred: Identifying tumor necrosis factors using hybrid features based on word embeddings
Authors: Nguyen Trinh-Trung-Duong , Le Nguyen-Quoc-Khanh , Ho Quang-Thai , Phan Dinh-Van , Ou Yu-Yen 
Published: December 2019

AbstractBackgroundCytokines are a class of small proteins that act as chemical messengers and play a significant role in essential cellular processes including immunity regulation, hematopoiesis, and inflammation. As one important family of cytokines, tumor necrosis factors have association with the regulation of a various biological processes such as proliferation and differentiation of cells, apoptosis, lipid metabolism, and coagulation. The implication of these cytokines can also be seen in various diseases such as insulin resistance, autoimmune diseases, and cancer. Considering the interdependence between this kind of cytokine and others, classifying tumor necrosis factors from other cytokines is a challenge for biological scientists. In this research, we employed a word embedding technique to create hybrid features which was proved to efficiently identify tumor necrosis factors given cytokine sequences. We segmented each protein sequence into protein words and created corresponding word embedding for each word. Then, word embedding-based vector for each sequence was created and input into machine learning classification models. When extracting feature sets, we not only diversified segmentation sizes of protein sequence but also conducted different combinations among split grams to find the best features which generated the optimal prediction. Furthermore, our methodology follows Chou’s 5-step rules to build a reliable classification tool.ResultsWith our proposed hybrid features, prediction models obtain more promising performance compared to seven prominent sequenced-based feature kinds. Results from 10 independent runs on the surveyed dataset show that on an average, our optimal models obtain an area under the curve of 0.984 and 0.998 on 5-fold cross-validation and independent test, respectively.ConclusionsThese results show that biologists can use our model to identify tumor necrosis factors from other cytokines efficiently. Moreover, this study proves that natural language processing techniques can be applied reasonably to help biologists solve bioinformatics problems efficiently.
Liposomes Under Real Cell Conditions Behave Like Real Cells with a Single Pulsed Electric Field
Authors: Urabe Gen , Shimada Masaharu , Ogata Takumi , Katsuki Sunao 
Published: December 2019

AbstractLiposomes are widely assumed to present a straightforward physical model of cells. However, almost all previous liposome experiments with pulsed electric fields (PEFs) have been conducted in low-conductivity liquids, a condition that differs significantly from that of cells in medium. Here, we prepared liposomes consisting of soy bean lecithin and cholesterol, at a molar ratio of 1:1, in higher-conductivity liquid that approximated the conditions of red blood cells in phosphate-buffered saline, with inner and outer liquid conductivities of 0.6 and 1.6 S/m, respectively. We found that a single 1.1 kV/cm, 400 μs PEF promoted cell-like spontaneous division of liposomes.