bluuebunny/crossref_metadata_2025_split huggingface dataset:
Levels of Representation in a Deep Learning Model of Categorization
Authors: Guest Olivia , Love Bradley C. 
Published: May 2019

AbstractDeep convolutional neural networks (DCNNs) rival humans in object recognition. The layers (or levels of representation) in DCNNs have been successfully aligned with processing stages along the ventral stream for visual processing. Here, we propose a model of concept learning that uses visual representations from these networks to build memory representations of novel categories, which may rely on the medial temporal lobe (MTL) and medial prefrontal cortex (mPFC). Our approach opens up two possibilities:a) formal investigations can involve photographic stimuli as opposed to stimuli handcrafted and coded by the experimenter;b) model comparison can determine which level of representation within a DCNN a learner is using during categorization decisions. Pursuing the latter point, DCNNs suggest that the shape bias in children relies on representations at more advanced network layers whereas a learner that relied on lower network layers would display a color bias. These results confirm the role of natural statistics in the shape bias (i.e., shape is predictive of category membership) while highlighting that the type of statistics matter, i.e., those from lower or higher levels of representation. We use the same approach to provide evidence that pigeons performing seemingly sophisticated categorization of complex imagery may in fact be relying on representations that are very low-level (i.e., retinotopic). Although complex features, such as shape, relatively predominate at more advanced network layers, even simple features, such as spatial frequency and orientation, are better represented at the more advanced layers, contrary to a standard hierarchical view.
Juvenile hormone interacts with multiple factors to modulate aggression and dominance in groups of orphan bumble bee (Bombus terrestris) workers
Authors: Pandey Atul , Motro Uzi , Bloch Guy 
Published: May 2019

AbstractJuvenile hormone (JH) is a key regulator of insect development and reproduction. Given that JH commonly affects adult insect fertility, it has been hypothesized to also regulate behaviors such as dominance and aggression that are associated with reproduction. We tested this hypothesis in the bumble beeBombus terrestrisfor which JH has been shown to be the major gonadotropin. We used the allatoxin Precocene-I (P-I) to reduce hemolymph JH titers and replacement therapy with the natural JH to revert this effect. In small orphan groups of workers with similar body size but mixed treatment, P-I treated bees showed lower aggressiveness, oogenesis, and dominance rank compared with control and replacement therapy treated bees. In similar groups in which all bees were treated similarly, there was a clear dominance hierarchy, even in P-I and replacement therapy treatment groups in which the bees showed similar levels of ovarian activation. In a similar experiment in which bees differed in body size, larger bees were more likely to be dominant despite their similar JH treatment and ovarian state. In the last experiment, we show that JH manipulation does not affect dominance rank in groups that had already established a stable dominance hierarchy. These findings solve previous ambiguities concerning whether or not JH affects dominance in bumble bees. JH positively affects dominance, but bees with similar levels of JH can nevertheless establish dominance hierarchies. Thus, multiple factors including JH, body size, and previous experience affect dominance and aggression in social bumble bees.
Mammalian gene expression variability is explained by underlying cell state
Authors: Foreman Robert , Wollman Roy 
Published: May 2019

AbstractGene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here we exploit the qualitative difference in the patterns of covariance between these two sources to quantify their relative contributions to expression variance in mammalian cells. Using multiplexed error robust RNA fluorescent in situ hybridization (MERFISH) we measured the multivariate gene expression distribution of 150 genes related to Ca2+signaling coupled with the dynamic Ca2+response of live cells to ATP. We show that after controlling for cellular phenotypic states such as size, cell cycle stage, and Ca2+response to ATP, the remaining variability is effectively at the Poisson limit for most genes. These findings demonstrate that the majority of expression variability results from cell state differences and that the contribution of transcriptional bursting is relatively minimal.
RNA polymerase mutations cause cephalosporin resistance in clinicalNeisseria gonorrhoeaeisolates
Authors: Palace Samantha G. , Wang Yi , Rubin Daniel H. F. , Welsh Michael A. , Mortimer Tatum D. , Cole Kevin , Eyre David W. , Walker Suzanne , Grad Yonatan H. 
Published: May 2019

AbstractIncreasingNeisseria gonorrhoeaeresistance to ceftriaxone, the last antibiotic recommended for empiric gonorrhea treatment, poses an urgent public health threat. However, the genetic basis of reduced susceptibility to ceftriaxone is not completely understood: while most ceftriaxone resistance in clinical isolates is caused by target site mutations inpenA, others lack these mutations. Here, we show thatpenA-independent ceftriaxone resistance has evolved multiple times through distinct mutations inrpoBandrpoD. We identify five mutations in these genes that each increase resistance to ceftriaxone, including one mutation that arose independently in two lineages, and show that clinical isolates from multiple lineages are a single nucleotide change from ceftriaxone resistance. These RNA polymerase mutations result in large-scale transcriptional changes without altering susceptibility to other antibiotics, reducing growth rate, or deranging cell morphology. These results underscore the unexpected diversity of pathways to resistance and the importance of continued surveillance for novel resistance mutations.
Multicellular behavior enables cooperation in microbial cell aggregates
Authors: Ebrahimi Ali , Schwartzman Julia , Cordero Otto X. 
Published: May 2019

SummaryDuring the degradation of biological materials such as biopolymers, extracellular enzymes liberate oligosaccharides that act as common goods and become available for all cells in the local neighborhood. This phenomenon can lead to cooperative growth, whereby cell-cell aggregation increases both the per-capita availability of resources and the per cell growth rate. However, aggregation can also have detrimental consequences for growth, as gradients form within aggregates limiting the resource accessibility. We used a computational model to show that high bacterial densities and high enzyme secretion rates restrict cooperation in aggregates larger than 10μm, due to the emergence of polymer and oligomer counter-gradients. We compared these predictions against experiments performed with two well-studied alginate degrading Vibrios, one of which displayed a strong density dependent growth. We observed that both strains can form large aggregates (<50μm), overcoming diffusion limitation by rearranging their internal structure. The non-cooperative, strong enzyme producer formed aggregates with internal channels that allowed exchange between the bulk environment and the aggregate core, whereas the cooperative, weak enzyme producer formed dense aggregates that developed a hollow structure as they grew. These internal structures allowed cells to avoid overcrowded areas near the core, enabling the development of large cell aggregates. Our study shows that bacterial behavior can help overcome competition imposed by resource gradients within cell aggregates.
Using Deep Learning to Annotate the Protein Universe
Authors: Bileschi Maxwell L. , Belanger David , Bryant Drew , Sanderson Theo , Carter Brandon , Sculley D. , DePristo Mark A. , Colwell Lucy J. 
Published: May 2019

AbstractUnderstanding the relationship between amino acid sequence and protein function is a long-standing problem in molecular biology with far-reaching scientific implications. Despite six decades of progress, state-of-the-art techniques cannot annotate 1/3 of microbial protein sequences, hampering our ability to exploit sequences collected from diverse organisms. In this paper, we explore an alternative methodology based on deep learning that learns the relationship between unaligned amino acid sequences and their functional annotations across all 17929 families of the Pfam database. Using the Pfam seed sequences we establish rigorous benchmark assessments that use both random and clustered data splits to control for potentially confounding sequence similarities between train and test sequences. Using Pfam full, we report convolutional networks that are significantly more accurate and computationally efficient than BLASTp, while learning sequence features such as structural disorder and transmembrane helices. Our model co-locates sequences from unseen families in embedding space, allowing sequences from novel families to be accurately annotated. These results suggest deep learning models will be a core component of future protein function prediction tools.
Click-PD: A Quantitative Method for Base-Modified Aptamer Discovery
Authors: Gordon Chelsea K. L. , Wu Diana , Feagin Trevor A. , Pusuluri Anusha , Csordas Andrew T. , Eisenstein Michael , Hawker Craig J. , Niu Jia , Soh H. Tom 
Published: May 2019

ABSTRACTBase-modified aptamers that incorporate non-natural chemical moieties can achieve greatly improved affinity and specificity relative to natural DNA or RNA aptamers. However, conventional methods for generating base-modified aptamers require considerable expertise and resources. In this work, we have accelerated and generalized the process of generating base-modified aptamers by combining a click-chemistry strategy with a fluorescence-activated cell sorting (FACS)-based screening methodology that measures the affinity and specificity of individual aptamers at a throughput of ∼10^7 per hour. Our “click-PD” strategy offers many advantages. First, almost any chemical modification can be introduced with a commercially-available polymerase. Second, click-PD can screen vast numbers of individual aptamers based on quantitative on- and off-target binding measurements to simultaneously achieve high affinity and specificity. Finally, it requires minimal specialized equipment or reagents besides a FACS instrument which is now widely-available. Using click-PD, we generated a boronic acid-modified aptamer with ∼1 μM affinity for epinephrine, a target for which no aptamer has been reported to date. We subsequently generated a mannose-modified aptamer with nanomolar affinity for the lectin concanavalin A (ConA). The strong affinity of both aptamers is fundamentally dependent upon the presence of chemical modifications, and we show that their removal essentially eliminates aptamer binding. Importantly, our ConA aptamer exhibited exceptional specificity, with minimal binding to other structurally-similar lectins. Finally, we show that our aptamer remarkable biological activity. Indeed, to the best of our knowledge, this aptamer is the most potent inhibitor of Con A-mediated hemagglutination reported to date.
Natural and Pathogenic Protein Sequence Variation Affecting Prion-Like Domains Within and Across Human Proteomes
Authors: Cascarina Sean M. , Ross Eric D. 
Published: May 2019

ABSTRACTProtein aggregation is involved in a variety of muscular and neurodegenerative disorders. For many of these disorders, current models suggest a prion-like molecular mechanism of disease, whereby proteins aggregate and spread to neighboring cells in an infectious manner. A variety of proteins with prion-like domains (PrLDs) have recently been linked to these disorders. The development of prion prediction algorithms has facilitated the large-scale identification of PrLDs among “reference” proteomes for various organisms. However, the degree to which intraspecies protein sequence diversity influences predicted aggregation propensity for PrLDs has not been systematically examined. Here, we explore protein sequence variation introduced at genetic, post-transcriptional, and post-translational levels, and its influence on predicted aggregation propensity for human PrLDs. We find that sequence variation is relatively common among PrLDs and in some cases can result in relatively large differences in predicted aggregation propensity. Analysis of a database of sequence variants associated with human disease reveals a number of mutations within PrLDs that are predicted to increase aggregation propensity. Our analyses expand the list of candidate human PrLDs, estimate the effects of sequence variation on the aggregation propensity of PrLDs, and suggest the involvement of prion-like mechanisms in additional human diseases.
Genetic Risk Factors for Colorectal Cancer in Multiethnic Indonesians
Authors: Yusuf Irawan , Miskad Upik A. , Lusikooy Ronald E. , Arsyad Arham , Irwan Akram , Mathew George , Suriapranata Ivet , Kusuma Rinaldy , Pardamean Bens , Fitra Kacamarga Muhamad , Budiarto Arif , Wawan Cenggoro Tjeng , Pardamean Carissa I. , McMahan Christopher , Joyner Chase , Baurley James W. 
Published: May 2019

AbstractPurposeColorectal cancer is a common cancer in Indonesia, yet it has been understudied. We conduct a genome-wide association study focused on evaluation and discovery of colorectal cancer risk factors in Indonesians.MethodsWe administered detailed questionnaires and collecting blood samples from 162 colorectal cancer cases throughout Makassar, Indonesia. We also established a control set of 193 healthy individuals frequency matched by age, sex, and ethnicity. A genome-wide association analysis was performed on 84 cases and 89 controls passing quality control. We evaluated known colorectal cancer genetic variants using logistic regression and established a genome-wide polygenic risk model using a Bayesian variable selection technique.ResultsWe replicate associations for rs9497673, rs6936461 and rs7758229 on chromosome 6; rs11255841 on chromosome 10; and rs4779584, rs11632715, and rs73376930 on chromosome 15. Polygenic modeling identified 10 SNP associated with colorectal cancer risk.ConclusionsThis work helps characterize the relationship between variants in theSCL22A3,SCG5,GREM1, andSTXBP5-AS1genes and colorectal cancer in a diverse Indonesian population. With further biobanking and international research collaborations, variants specific to colorectal cancer risk in Indonesians will be identified.
Timing of arrival in the breeding area is repeatable and affects reproductive success in a non-migratory population of blue tits
Authors: Gilsenan Carol , Valcu Mihai , Kempenaers Bart 
Published: May 2019

ABSTRACTEvents in one part of the annual cycle often affect the performance (and subsequently fitness) of individuals later in the season (carry-over effects). An important aspect of this relates to the timing of activities. For example, many studies on migratory birds have shown that relatively late spring arrival in the breeding area reduces both the likelihood of getting a mate or territory and reproductive success.In contrast, relatively little is known about movements of individuals in non-migratory populations during the non-breeding season. Few studies have investigated the timing of arrival at the breeding area in such species, possibly due to the assumption that most individuals remain in the area during the non-breeding season.In this study, we used four years of data from a transponder-based automated recording system set up in a non-migratory population of blue tits (Cyanistes caeruleus) to describe individual variation in arrival at the breeding site. We investigated whether this variation can be explained by individual characteristics (sex, body size, or status), and we assessed its effect on aspects of reproductive success in the subsequent breeding season.We found substantial variation in arrival date and demonstrate that this trait is individual-specific (repeatable). Females arrived later than males, but the arrival dates of social pair members were more similar than expected by chance. Arrival predicted both whether an individual would end up breeding that season, and several aspects of its breeding success.Our study suggests that non-migratory species show a form of incipient migration behaviour in that they leave the breeding area during the non-breeding season. We conclude that the timing of pre-breeding events, in particular arrival date, may be an overlooked, but important, fitness-relevant trait in non-migratory species.
Mitochondrial mass governs the extent of T cell senescence
Authors: Callender Lauren A. , Carroll Elizabeth C. , Bober Emilia A , Akbar Arne N. , Solito Egle , Henson Sian M. 
Published: May 2019

AbstractThe susceptibility of human CD4+ and CD8+ T cells to senesce differs, with CD8+ T cells acquiring an immunosenescent phenotype faster than their CD4+ T cell compartment. We show here that it is the inherent difference in mitochondrial content that drives this phenotype, with senescent human CD4+ T cells displaying a higher mitochondrial mass. The loss of mitochondria in the senescent human CD8+ T cells has knock-on consequences for nutrient usage, metabolism and function. Mitochondrial dysfunction has been linked to both cellular senescence and ageing, however it is still unclear whether mitochondria play a causal role in senescence. Our data shows that reducing mitochondrial function in human CD4+ T cells, through the addition of low dose rotenone, causes the generation of a CD4+ T cell with a CD8+ -like phenotype. Therefore we wish to propose that it is the inherent metabolic stability that governs the susceptibility to an immunosenescent phenotype.
Chromatin interaction analysis with updated ChIA-PET Tool (V3)
Authors: Li Guoliang , Sun Tongkai , Chang Huidan , Cai Liuyang , Hong Ping , Zhou Qiangwei 
Published: May 2019

AbstractUnderstanding chromatin interactions is important since they create chromosome conformation and link the cis- and trans-regulatory elements to their target genes for transcriptional regulation. Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a genome-wide high-throughput technology that detects chromatin interactions associated with a specific protein of interest. Previously we developed ChIA-PET Tool in 2010 for ChIA-PET data analysis. Here we present the updated version of ChIA-PET Tool (V3), is a computational package to process the next-generation sequence data generated from ChIA-PET experiments. It processes the short-read data and long-read ChIA-PET data with multithreading and generates the statistics of results in a HTML file. In this paper, we provide a detailed demonstration of the design of ChIA-PET Tool V3 and how to install it and analyze a specific ChIA-PET data set with it. At present, other ChIA-PET data analysis tools have developed including ChiaSig, MICC, Mango and ChIA-PET2 and so on. We compared our tool with other tools using the same public data set in the same machine. Most of peaks detected by ChIA-PET Tool V3 overlap with those from other tools. There is higher enrichment for significant chromatin interactions of ChIA-PET Tool V3 in APA plot. ChIA-PET Tool V3 is open source and is available at GitHub (https://github.com/GuoliangLi-HZAU/ChIA-PET_Tool_V3/).
Dietary methionine restriction targets one carbon metabolism in humans and produces broad therapeutic responses in cancer
Authors: Gao Xia , Sanderson Sydney M. , Dai Ziwei , Reid Michael A. , Cooper Daniel E. , Lu Min , Richie John P. , Ciccarella Amy , Calcagnotto Ana , Mikhael Peter G. , Mentch Samantha J. , Liu Juan , Ables Gene , Kirsch David G. , Hsu David S. , Nichenametla Sailendra N. , Locasale Jason W. 
Published: May 2019

AbstractNutrition exerts profound effects on health and dietary interventions are commonly used to treat diseases of metabolic etiology. Although cancer has a substantial metabolic component, the principles that define whether nutrition may be used to influence tumour outcome are unclear. Nevertheless, it is established that targeting metabolic pathways with pharmacological agents or radiation can sometimes lead to controlled therapeutic outcomes. In contrast, whether specific dietary interventions could influence the metabolic pathways that are targeted in standard cancer therapies is not known. We now show that dietary restriction of methionine (MR), an essential amino acid, and the reduction of which has aging and obesogenic properties, influences cancer outcome through controlled and reproducible changes to one carbon metabolism. This pathway metabolizes methionine and further is the target of a host of cancer interventions involving chemotherapy and radiation. MR produced therapeutic responses in chemoresistant RAS-driven colorectal cancer patient derived xenografts and autochthonous KRASG12D+/−;TP53−/− -driven soft tissue sarcomas resistant to radiation. Metabolomics revealed the therapeutic mechanisms to occur through tumor cell autonomous effects on the flux through one carbon metabolism that impacted redox and nucleotide metabolism, thus interacting with the antimetabolite or radiation intervention. Finally, in a controlled and tolerated feeding study in humans, MR resulted in similar effects on systemic metabolism as obtained in responsive mice. These findings provide evidence that a targeted dietary manipulation can affect specific tumor cell metabolism to mediate broad aspects of cancer outcome.
Combinatorial perturbation analysis reveals divergent regulations of mesenchymal genes during epithelial-to-mesenchymal transition
Authors: Watanabe Kazuhide , Panchy Nicholas , Noguchi Shuhei , Suzuki Harukazu , Hong Tian 
Published: May 2019

AbstractEpithelial-to-mesenchymal transition (EMT), a fundamental transdifferentiation process in development, produces diverse phenotypes in different physiological or pathological conditions. Many genes involved in EMT have been identified to date, but mechanisms contributing to the phenotypic diversity and those governing the coupling between the dynamics of epithelial (E) genes and that of the mesenchymal (M) genes are unclear. In this study, we employed combinatorial perturbations to mammary epithelial cells to induce a series of EMT phenotypes by manipulating two essential EMT-inducing elements, namely TGF-β and ZEB1. By measuring transcriptional changes in more than 700 E- and M-genes, we discovered that the M-genes exhibit a significant diversity in their dependency to these regulatory elements and identified three groups of M-genes that are controlled by different regulatory circuits. Notably, functional differences were detected among the M-gene clusters in motility regulation and in survival of breast cancer patients. We computationally predicted and experimentally confirmed that the reciprocity and reversibility of EMT are jointly regulated by ZEB1. Our integrative analysis reveals the key roles of ZEB1 in coordinating the dynamics of a large number of genes during EMT, and it provides new insights into the mechanisms for the diversity of EMT phenotypes.