bluuebunny/crossref_metadata_2025_split huggingface dataset:
Value Certainty in Drift-Diffusion Models of Preferential Choice
Authors: Lee Douglas , Usher Marius 
Published: August 2020

AbstractThedrift-diffusion model(DDM) is widely used and broadly accepted for its ability to account for binary choices (in both the perceptual and preferential domains) and response times (RT), as a function of the stimulus or the choice alternative (or option) values. The DDM is built on an evidence accumulation-to-bound concept, where, in the value domain, a decision maker repeatedly samples the mental representations of the values of the available options until satisfied that there is enough evidence (or support) in favor of one option over the other. As the signals that drive the evidence are derived from value estimates that are not known with certainty, repeated sequential samples are necessary to average out noise. The classic DDM does not allow for different options to have different levels of precision in their value representations. However, recent studies have shown that decision makers often report levels of certainty regarding value estimates that vary across choice options. There is therefore a need to extend the DDM to include an option-specific value certainty component. We present several such DDM extensions and validate them against empirical data from four previous studies. The data support best a DDM version in which the drift of the accumulation is based on a sort of signal-to-noise ratio of value for each option (rather than a mere accumulation of samples from the corresponding value distributions). This DDM variant accounts for the impact of value certainty on both choice consistency and response time present in the empirical data.
Adaptation across geographic ranges is consistent with strong selection in marginal climates and legacies of range expansion
Authors: Bontrager Megan , Usui Takuji , Lee-Yaw Julie A. , Anstett Daniel N. , Branch Haley A. , Hargreaves Anna L. , Muir Christopher D. , Angert Amy L. 
Published: August 2020

AbstractEvery species experiences limits to its geographic distribution. Some evolutionary models predict that populations at range edges are less well-adapted to their local environments due to drift, expansion load, or swamping gene flow from the range interior. Alternatively, populations near range edges might be uniquely adapted to marginal environments. In this study, we use a database of transplant studies that quantify performance at broad geographic scales to test how local adaptation, site quality, and population quality change from spatial and climatic range centers towards edges. We find that populations from poleward edges perform relatively poorly, both on average across all sites (15% lower population quality) and when compared to other populations at home (31% relative fitness disadvantage), consistent with these populations harboring high genetic load. Populations from equatorial edges also perform poorly on average (18% lower population quality) but, in contrast, outperform foreign populations (16% relative fitness advantage), suggesting that populations from equatorial edges have strongly adapted to unique environments. Finally, we find that populations from sites that are thermally extreme relative to the species’ niche demonstrate strong local adaptation, regardless of their geographic position. Our findings indicate that both nonadaptive processes and adaptive evolution contribute to variation in adaptation across species’ ranges.
Theoretical basis for stabilizing messenger RNA through secondary structure design
Authors: Wayment-Steele Hannah K. , Kim Do Soon , Choe Christian A. , Nicol John J. , Wellington-Oguri Roger , Watkins Andrew M. , Sperberg R. Andres Parra , Huang Po-Ssu , Participants Eterna , Das Rhiju 
Published: August 2020

AbstractRNA hydrolysis presents problems in manufacturing, long-term storage, world-wide delivery, and in vivo stability of messenger RNA (mRNA)-based vaccines and therapeutics. A largely unexplored strategy to reduce mRNA hydrolysis is to redesign RNAs to form double-stranded regions, which are protected from in-line cleavage and enzymatic degradation, while coding for the same proteins. The amount of stabilization that this strategy can deliver and the most effective algorithmic approach to achieve stabilization remain poorly understood. Here, we present simple calculations for estimating RNA stability against hydrolysis, and a model that links the average unpaired probability of an mRNA, or AUP, to its overall hydrolysis rate. To characterize the stabilization achievable through structure design, we compare AUP optimization by conventional mRNA design methods to results from more computationally sophisticated algorithms and crowdsourcing through the OpenVaccine challenge on the Eterna platform. These computational tests were carried out on both model mRNAs and COVID-19 mRNA vaccine candidates. We find that rational design on Eterna and the more sophisticated algorithms lead to constructs with low AUP, which we term ‘superfolder’ mRNAs. These designs exhibit wide diversity of sequence and structure features that may be desirable for translation, biophysical size, and immunogenicity, and their folding is robust to temperature, choice of flanking untranslated regions, and changes in target protein sequence, as illustrated by rapid redesign of superfolder mRNAs for B.1.351, P.1, and B.1.1.7 variants of the prefusion-stabilized SARS-CoV-2 spike protein. Increases in in vitro mRNA half-life by at least two-fold appear immediately achievable.Significance statementMessenger RNA (mRNA) medicines that encode and promote translation of a target protein have shown promising use as vaccines in the current SARS-CoV-2 pandemic as well as infectious diseases due to their speed of design and manufacturing. However, these molecules are intrinsically prone to hydrolysis, leading to poor stability in aqueous buffer and major challenges in distribution. Here, we present a principled biophysical model for predicting RNA degradation, and demonstrate that the stability of any mRNA can be increased at least two-fold over conventional design techniques. Furthermore, the predicted stabilization is robust to post-design modifications. This conceptual framework and accompanying algorithm can be immediately deployed to guide re-design of mRNA vaccines and therapeutics to increase in vitro stability.
Plant traits that influence flower visits by birds in a montane forest
Authors: Gonzalez Oscar 
Published: August 2020

AbstractIn a bird-flowering plant network, birds select plants that present traits attractive to them. I studied plant characteristics that might predict flower visitation rate by the most common bird visitors in a bird-flowering plant network located in an elfin forest of the Andes. The nectarivorous birds which had the highest number of interactions with flowering plants in this network were the Coppery Metaltail (Metallura theresiae), the Great Sapphirewing (Pterophanes cyanopterus), and the Moustached Flowerpiercer (Diglossa mystacalis). I analyzed different flower traits (flower aggregation, nectar volume, nectar energy, color, orientation, and dimensions of the corolla) of the common plants that these birds visited with a principal component analysis. The plants most visited by birds wereBrachyotum lutescensandTristerix longebracteatus.While nectar traits of the plants seemed to be the best predictor for bird visitation, there was no statistical association between visitation and plant traits, except forMetallura theresiaein the dry season. I discuss the possible causes of resource partitioning for these nectarivorous birds.
Epigenetic reprogramming of plasmacytoid dendritic cells drives type I interferon-dependent differentiation of acute myeloid leukemias for therapeutic benefit
Authors: Salmon Jessica M. , Todorovski Izabela , Vervoort Stephin J. , Stanley Kym L. , Kearney Conor J. , Martelotto Luciano , Rossello Fernando , Semple Tim , Mir-Arnau Gisela , Zethoven Magnus , Bots Michael , Vidacs Eva , McArthur Kate , Gressier Elise , de Weerd Nicky , Lichte Jens , Kelly Madison J. , Cluse Leonie , Hogg Simon J. , Hertzog Paul J. , Kats Lev , de Carvalho Daniel D. , Scheu Stefanie , Bedoui Sammy , Kile Benjamin T. , Wei Andrew , Dominguez Pilar M. , Johnstone Ricky W. 
Published: August 2020

ABSTRACTPharmacological inhibition of epigenetic enzymes can have therapeutic benefit, particularly against hematological malignancies. While these agents can affect tumor cell growth and proliferation, recent studies have demonstrated that pharmacological de-regulation of epigenetic modifiers may additionally mediate anti-tumor immune responses. Here we discovered a novel mechanism of immune regulation through the inhibition of histone deacetylases (HDACs). In a genetically engineered model of t(8;21) AML, leukemia cell differentiation and therapeutic benefit mediated by the HDAC inhibitor panobinostat required activation of the type I interferon (IFN) signaling pathway. Plasmacytoid dendritic cells (pDCs) were identified as the cells producing type I IFN in response to panobinostat, through transcriptional activation of IFN genes concomitant with increased H3K27 acetylation at these loci. Depletion of pDCs abrogated panobinostat-mediated activation of type I IFN signaling in leukemia cells and impaired therapeutic efficacy, while combined treatment of panobinostat and recombinant IFNα improved therapeutic outcomes. These discoveries offer a new therapeutic approach for t(8;21) AML and demonstrate that epigenetic rewiring of pDCs enhances anti-tumor immunity, opening the possibility of exploiting this cell type as a new target for immunotherapy.
Computational Modeling: Human Dynamic Model
Authors: Liu Lijia , Cooper Joseph L. , Ballard Dana H. 
Published: August 2020

AbstractImprovements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide useful constraints for underlying neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. A 48 degree of freedom dynamic model of humans has been developed to report humanoid movements’ energetic components. It has sufficient speed and accuracy to analyze and synthesize real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to believably animate a humanoid character or estimate internal joint forces used during a movement for creating effort-contingent experimental stimuli. A virtual reality environment developed as part of this research supports controlled experiments for systematically recording human behaviors.
A genome-scale phylogeny of Fungi; insights into early evolution, radiations, and the relationship between taxonomy and phylogeny
Authors: Li Yuanning , Steenwyk Jacob L. , Chang Ying , Wang Yan , James Timothy Y. , Stajich Jason E. , Spatafora Joseph W. , Groenewald Marizeth , Dunn Casey W. , Hittinger Chris Todd , Shen Xing-Xing , Rokas Antonis 
Published: August 2020

AbstractPhylogenomic studies based on genome-scale amounts of data have greatly improved understanding of the tree of life. Despite their diversity, ecological significance, and biomedical and industrial importance, large-scale phylogenomic studies of Fungi are lacking. Furthermore, several evolutionary relationships among major fungal lineages remain controversial, especially those at the base of the fungal phylogeny. To begin filling these gaps and assess progress toward a genome-scale phylogeny of the entire fungal kingdom, we compiled a phylogenomic data matrix of 290 genes from the genomes of 1,644 fungal species that includes representatives from most major fungal lineages; we also compiled 11 additional data matrices by subsampling genes or taxa based on filtering criteria previously shown to improve phylogenomic inference. Analyses of these 12 data matrices using concatenation- and coalescent-based approaches yielded a robust phylogeny of the kingdom in which ∼85% of internal branches were congruent across data matrices and approaches used. We found support for several relationships that have been historically contentious (e.g., for the placement of Wallemiomycotina (Basidiomycota), as sister to Agaricomycotina), as well as evidence for polytomies likely stemming from episodes of ancient diversification (e.g., at the base of Basidiomycota). By examining the relative evolutionary divergence of taxonomic groups of equivalent rank, we found that fungal taxonomy is broadly aligned with genome sequence divergence, but also identified lineages, such as the subphylum Saccharomycotina, where current taxonomic circumscription does not fully account for their high levels of evolutionary divergence. Our results provide a robust phylogenomic framework to explore the tempo and mode of fungal evolution and directions for future fungal phylogenetic and taxonomic studies.
Dissociable Roles of Pallidal Neuron Subtypes in Regulating Motor Patterns
Authors: Cui Qiaoling , Pamukcu Arin , Cherian Suraj , Chang Isaac Y. M. , Berceau Brianna L. , Xenias Harry S. , Higgs Mathew H. , Rajamanickam Shivakumar , Chen Yi , Du Xixun , Zhang Yu , McMorrow Hayley , Abecassis Zachary A. , Boca Simina M. , Justice Nicholas J. , Wilson Charles J. , Chan C. Savio 
Published: August 2020

AbstractWe have previously established that PV+neurons and Npas1+neurons are distinct neuron classes in the GPe— they have different topographical, electrophysiological, circuit, and functional properties. Aside from Foxp2+neurons, which are a unique subclass within the Npas1+class, we lack driver lines that effectively capture other GPe neuron subclasses. In this study, we examined the utility of Kcng4-Cre, Npr3-Cre, and Npy2r-Cre mouse lines (both males and females) for the delineation of GPe neuron subtypes. By using these novel driver lines, we have provided the most exhaustive investigation of electrophysiological studies of GPe neuron subtypes to date. Corroborating our prior studies, GPe neurons can be divided into two statistically distinct clusters that map onto PV+and Npas1+classes. By combining optogenetics and machine learning-based tracking, we showed that optogenetic perturbation of GPe neuron subtypes generated unique behavioral structures. Our findings further highlighted the dissociable roles of GPe neurons in regulating movement and anxiety-like behavior. We concluded that Npr3+neurons and Kcng4+neurons are distinct subclasses of Npas1+neurons and PV+neurons, respectively. Finally, by examining local collateral connectivity, we inferred the circuit mechanisms involved in the motor patterns observed with optogenetic perturbations. In summary, by identifying mouse lines that allow for manipulations of GPe neuron subtypes, we created new opportunities for interrogations of cellular and circuit substrates that can be important for motor function and dysfunction.Significance statementWithin the basal ganglia, the external globus pallidus (GPe) has long been recognized for its involvement in motor control. However, we lacked an understanding of precisely how movement is controlled at the GPe level as a result of its cellular complexity. In this study, by using transgenic and cell-specific approaches, we showed that genetically-defined GPe neuron subtypes have distinct roles in regulating motor patterns. In addition, thein vivocontributions of these neuron subtypes are in part shaped by the local, inhibitory connections within the GPe. In sum, we have established the foundation for future investigations of motor function and disease pathophysiology.
MQF and buffered MQF: Quotient filters for efficient storage of k-mers with their counts and metadata
Authors: Shokrof Moustafa , Brown C. Titus , Mansour Tamer A. 
Published: August 2020

AbstractBackgroundSpecialized data structures are required for online algorithms to efficiently handle large sequencing datasets. The counting quotient filter (CQF), a compact hashtable, can efficiently store k-mers with a skewed distribution.ResultHere, we present the mixed-counters quotient filter (MQF) as a new variant of the CQF with novel counting and labeling systems. The new counting system adapts to a wider range of data distributions for increased space efficiency and is faster than the CQF for insertions and queries in most of the tested scenarios. A buffered version of the MQF can offload storage to disk, trading speed of insertions and queries for a significant memory reduction. The labeling system provides a flexible framework for assigning labels to member items while maintaining good data locality and a concise memory representation. These labels serve as a minimal perfect hash function but are ~10 fold faster than BBhash, with no need to re-analyze the original data for further insertions or deletions.ConclusionThe MQF is a flexible and efficient data structure that extends our ability to work with high throughput sequencing data.
Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy
Authors: Krieger Teresa G , Blanc Solange Le , Jabs Julia , Ten Foo Wei , Ishaque Naveed , Jechow Katharina , Debnath Olivia , Leonhardt Carl-Stephan , Giri Anamika , Eils Roland , Strobel Oliver , Conrad Christian 
Published: August 2020

AbstractPancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished ‘classical’ pancreatic tumors from ‘basal-like’ tumors with more aggressive clinical behaviour. We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report ‘classical’ and ‘basal-like’ cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with ‘classical’ subtype cells concentrated at the endpoint of this hierarchy. In an imaging-based drug screen, expression of ‘classical’ subtype genes also correlates with better response to clinical drugs. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model forin vitrostudies of tumor heterogeneity.
Synthesis and Evaluation of a Stable Isostere of Malonyllysine
Authors: Bergholtz Sarah E. , Jing Yihang , Kulkarni Rhushikesh A. , Zengeya Thomas T. , Meier Jordan L. 
Published: August 2020

AbstractLysine malonylation is a recently characterized posttranslational modification involved in the regulation of energy metabolism and gene expression. Two unique features of this posttranslational modification are its negative charge and potential susceptibility to decarboxylation, both of which pose possible challenges to its study. As a step towards addressing these challenges, here we report the synthesis and evaluation of a stable isostere of malonyllysine. First, we find that synthetic substitution of the malonyl group with a tetrazole isostere results in amino acids resistant to thermal decarboxylation. Next, we demonstrate that protected variants of this amino acid are readily incorporated into peptides. Finally, we show that tetrazole isosteres of malonyllysine can be recognized by anti-malonyllysine antibodies, validating their ability to mimic features of the endogenous lysine modification. Overall, this study establishes a new chemical strategy for stably mimicking a metabolite-derived posttranslational modification, providing a foothold for tool development and functional analyses.
Developmental retrotransposon activation primes host immunity for future viral-clearance
Authors: Wang Lu , Tracy Lauren , Zhang ZZ Zhao 
Published: August 2020

AbstractTransposons are thought to be largely suppressed under physiological conditions, ensuring that their mobilization is a rare event. By tracking mobilization, we show that during metamorphosis at theDrosophilapupal stage, theGypsyretrotransposon selectively mobilizes in regenerating tissues. In the newly formed tissues, this wave ofGypsyactivation primes the host’s innate immune system by inducing the production ofantimicrobialpeptides (AMPs). Moreover, early immune-priming functions ofGypsyare essential for combating viral invasion in adult flies: flies withGypsybeing silenced at the pupal stage are unable to clear viruses and succumb to viral infection. Our data reveal that regulated activation of transposons during animal developmental endows a long-term benefit in pathogen warfare.
Movie-watching outperforms rest for functional connectivity-based prediction of behavior
Authors: Finn Emily S. , Bandettini Peter A. 
Published: August 2020

AbstractA major goal of human neuroscience is to relate differences in brain function to differences in behavior across people. Recent work has established that whole-brain functional connectivity patterns are relatively stable within individuals and unique across individuals, and that features of these patterns predict various traits. However, while functional connectivity is most often measured at rest, certain tasks may enhance individual signals and improve sensitivity to behavioral differences. Here, we show that compared to the resting state, functional connectivity measured during naturalistic viewing—i.e., movie watching—yields more accurate predictions of trait-like phenotypes in the both cognitive and emotional domains. Traits could be predicted using less than three minutes of data from single video clips, and clips with highly social content gave the most accurate predictions. Results suggest that naturalistic stimuli amplify individual differences in behaviorally relevant brain networks.
Whole-organism eQTL mapping at cellular resolution with single-cell sequencing
Authors: Ben-David Eyal , Boocock James , Guo Longhua , Zdraljevic Stefan , Bloom Joshua S. , Kruglyak Leonid 
Published: August 2020

AbstractGenetic regulation of gene expression underlies variation in disease risk and other complex traits. The effect of expression quantitative trait loci (eQTLs) varies across cell types; however, the complexity of mammalian tissues makes studying cell-type eQTLs highly challenging. We developed a novel approach in the model nematodeCaenorhabditis elegansthat uses single cell RNA sequencing to map eQTLs at cellular resolution in a single one-pot experiment. We mapped eQTLs across cell types in an extremely large population of genetically distinctC. elegnasindividuals. We found cell-type-specifictrans-eQTL hotspots that affect the expression of core pathways in the relevant cell types. Finally, we found single-cell-specific eQTL effects in the nervous system, including an eQTL with opposite effects in two individual neurons. Our results show that eQTL effects can be specific down to the level of single cells.