bluuebunny/crossref_metadata_2025_split huggingface dataset:
Orbitofrontal cortex and learning predictions of state transitions
Authors: Chan Stephanie C.Y. , Schuck Nicolas W. , Lopatina Nina , Schoenbaum Geoffrey , Niv Yael 
Published: September 2020

AbstractLearning the transition structure of the environment – the probabilities of transitioning from one environmental state to another – is a key prerequisite for goal-directed planning and model-based decision making. To investigate the role of the orbitofrontal cortex (OFC) in goal-directed planning and decision making, we used fMRI to assess univariate and multivariate activity in the OFC while humans experienced state transitions that varied in degree of surprise. Converging with recent evidence, we found that OFC activity was related to greater learning about transition structure. However, the observed relationship was inconsistent with a straightforward interpretation of OFC activity as representing a state prediction error that would facilitate learning of transitions via error-correcting mechanisms. The state prediction error hypothesis predicts that OFC activity at the time of observing an outcome should increase expectation of that same observed outcome on subsequent trials. Instead, our results showed that OFC activity was associated with increased expectation of themore probableoutcome; that is, with more optimal predictions. These results suggest that the OFC is involved in updating or reinforcing a learned transition model on a trial-by-trial basis, specifically for the currently observed cue-outcome associations. Our findings add to the evidence of OFC involvement in learning state-to-state transition structure, while providing new constraints for algorithmic hypotheses regarding how these transitions are learned.Significance StatementThe orbitofrontal cortex (OFC) has been implicated in model-based decision making—the kind of decisions that result from planning using an “environment model” of how current actions affect our future states. However, the widely suggested role of the OFC in representing expected values of future states is not sufficient to explain why the OFC would be critical for planning in particular. A new line of evidence implicates the OFC in learning about transition structure of the environment – a key component of the “environment model” used for planning. We investigate this function, adding to the growing literature on the role of the OFC in learning and decision making, while unveiling new questions about the algorithmic role of OFC in goal-directed planning.
Wheat transcriptome profiling reveals abscisic and gibberellic acid treatments regulate early-stage phytohormone defense signaling, cell wall fortification, and metabolic switches followingFusarium graminearum-challenge
Authors: Buhrow Leann M. , Liu Ziying , Cram Dustin , Sharma Tanya , Foroud Nora A. , Pan Youlian , Loewen Michele C. 
Published: September 2020

ABSTRACTBackgroundApplication of the wheat phytohormones abscisic acid (ABA) or gibberellic acid (GA) affect Fusarium head blight (FHB) disease severity; however, the molecular underpinnings of the elicited phenotypes remain unclear. Herein, the transcriptomic responses of an FHB-susceptible wheat cultivar ‘Fielder’ were characterized upon treatment with ABA, an ABA receptor antagonist (AS6), or GA in the presence or absence ofFusarium graminearum(Fg) challenge.ResultsA total of 30,876 differentially expressed genes (DEGs) where identified in ‘Fielder’ (26,004) andFg(4,872).Fgchallenge alone resulted in the most substantial wheat DEGs contributing to 57.2% of the total transcriptomic variation. Using a combination of topology overlap and correlation analyses, 9,689Fg-related wheat DEGs were defined. Further enrichment analysis of the top 1% networked wheat DEGs identified critical expression changes within defense responses, cell structural metabolism, molecular transport, and membrane/lipid metabolism.Fg-challenged conditions also included the expression of a putativeFgABA-biosynthetic cytochrome P450 and repression of wheatFUS3for dysregulating ABA and GA crosstalk. ABA treatment alone elicited 4536 (32%) wheat DEGs common to those of theFg-challenge, andFg+ABA further enhanced 888 (12.5%) of them. These ABA elicited DEGs are involved in defense through both classical and non-classical phytohormone signaling and regulating cell wall structures including polyphenolic metabolism. Conversely,Fg+GA opposed 2239 (33%)Fg-elicited wheat DEGs, including modulating primary and secondary metabolism, defense responses, and flowering genes. ABA and jointly ABA⍰Fg⍰[Fg+ABA] treatments repressed, whileFg+GA induced an over-representation of wheat DEGs mapping to chromosome 6BL. Finally, compared toFg+ABA, co-application ofFg+AS6 did not antagonize ABA biosynthesis or signal but rather elicited antagonisticFg(557) and wheat (11) DEGs responses directly tied to stress responses, phytohormone transport, and FHB.ConclusionsComparative transcriptomics highlight the effects of wheat phytohormones on individual pathway and global metabolism simultaneously. Application of ABA may reduce FHB severity through misregulating defense mechanisms and cell wall fortification pathways. GA application may alter primary and secondary metabolism, creating a metabolic shift to ultimately reduce FHB severity. By comparing these findings to those previously reported for four additional plant genotypes, an additive model of the wheat-Fginteraction is proposed.
Individual Ants Do Not Show Active-rest Rhythms in Natural Nest Conditions
Authors: Fujioka Haruna , Abe Masato S. , Okada Yasukazu 
Published: September 2020

AbstractCircadian rhythms, which respond to the day/night cycle on the earth, arise from the endogenous timekeeping system within organisms, called the biological clock. For accurate circadian rhythms, endogenous oscillations are synchronized to light and temperature. In social insects, both abiotic and biotic factors (i.e., social interactions) play a significant role in active/rest rhythm regulation. However, it is challenging to monitor individual active-rest rhythms in a colony because of the large group size and small body size. Therefore, it is unclear how social interactions coordinate each individual’s active/rest rhythms. This study developed an image-based tracking system using 2D barcodes for <I>Diacamma</I> sp. (a monomorphic ant) and measured the locomotor activities of all colony members under laboratory colony conditions. We also investigated the effect of broods on active/rest rhythms by removing all broods under colony conditions. Active/rest rhythms appeared only in solitary ants, not under colony conditions. In addition, arrhythmic active-rest rhythms were retained after brood removal. Therefore, a mixture of social interactions, not abiotic factors, induces the loss of active/rest rhythms. These results contribute to the knowledge of the diversity pattern of circadian rhythms in social insects.
Report 32: Age groups that sustain resurging COVID-19 epidemics in the United States
Authors: Monod Mélodie , Blenkinsop Alexandra , Xi Xiaoyue , Hebert Daniel , Bershan Sivan , Tietze Simon , Bradley Valerie C , Chen Yu , Coupland Helen , Filippi Sarah , Ish-Horowicz Jonathan , McManus Martin , Mellan Thomas , Gandy Axel , Hutchinson Michael , T Unwin H Juliette , C Vollmer Michaela A , Weber Sebastian , Zhu Harrison , Bezancon Anne , Ferguson Neil M , Mishra Swapnil , Flaxman Seth , Bhatt Samir , Ratmann Oliver 
Published: September 2020

SummaryFollowing initial declines, in mid 2020, a resurgence in transmission of novel coronavirus disease (COVID-19) has occurred in the United States and parts of Europe. Despite the wide implementation of non-pharmaceutical interventions, it is still not known how they are impacted by changing contact patterns, age and other demographics. As COVID-19 disease control becomes more localised, understanding the age demographics driving transmission and how these impacts the loosening of interventions such as school reopening is crucial. Considering dynamics for the United States, we analyse aggregated, age-specific mobility trends from more than 10 million individuals and link these mechanistically to age-specific COVID-19 mortality data. In contrast to previous approaches, we link mobility to mortality via age specific contact patterns and use this rich relationship to reconstruct accurate transmission dynamics. Contrary to anecdotal evidence, we find little support for age-shifts in contact and transmission dynamics over time. We estimate that, until August, 63.4% [60.9%-65.5%] of SARS-CoV-2 infections in the United States originated from adults aged 20-49, while 1.2% [0.8%-1.8%] originated from children aged 0-9. In areas with continued, community-wide transmission, our transmission model predicts that re-opening kindergartens and elementary schools could facilitate spread and lead to additional COVID-19 attributable deaths over a 90-day period. These findings indicate that targeting interventions to adults aged 20-49 are an important consideration in halting resurgent epidemics and preventing COVID-19-attributable deaths when kindergartens and elementary schools reopen.One sentence summaryAdults aged 20-49 are a main driver of the COVID-19 epidemic in the United States; yet, in areas with resurging epidemics, opening schools will lead to more COVID-19-attributable deaths, so more targeted interventions in the 20-49 age group could bring epidemics under control, avert deaths, and facilitate the safe reopening of schools.
Dimerization mechanism and structural features of human LI-cadherin
Authors: Yui Anna , Caaveiro Jose M. M. , Kuroda Daisuke , Nakakido Makoto , Nagatoishi Satoru , Goda Shuichiro , Maruno Takahiro , Uchiyama Susumu , Tsumoto Kouhei 
Published: September 2020

AbstractLI-cadherin is a member of the cadherin superfamily, which encompasses a group of Ca2+-dependent cell adhesion proteins. The expression of LI-cadherin is observed on various types of cells in the human body, such as normal small intestine and colon cells, and gastric cancer cells. Because its expression is not observed on normal gastric cells, LI-cadherin is a promising target for gastric cancer imaging. However, since the cell adhesion mechanism of LI-cadherin has remained unknown, rational design of therapeutic molecules targeting this cadherin has been hampered. Here, we have studied the homodimerization mechanism of LI-cadherin. We report the crystal structure of the LI-cadherin EC1-4 homodimer. The EC1-4 homodimer exhibited a unique architecture different from that of other cadherins reported so far. The crystal structure also revealed that LI-cadherin possesses a noncanonical calcium ion-free linker between EC2 and EC3. Various biochemical techniques and molecular dynamics (MD) simulations were employed to elucidate the mechanism of homodimerization. We also showed that the formation of the homodimer observed by the crystal structure is necessary for LI-cadherin-dependent cell adhesion by performing cell aggregation assay.
Periplasmic Expression of SpyTagged Antibody Fragments Enables Rapid Modular Antibody Assembly
Authors: Hentrich Christian , Kellmann Sarah-Jane , Putyrski Mateusz , Cavada Manuel , Hanuschka Hanh , Knappik Achim , Ylera Francisco 
Published: September 2020

AbstractAntibodies are essential tools in research and diagnostics. While antibody fragments can be rapidly produced inEscherichia coli, full-length antibodies with an Fc region or antibodies modified with probes are time and labor intensive in production.SpyTag/SpyCatcher protein ligation technology could covalently attach such functionalities to antibody fragments equipped with a SpyTag. However, we found that the necessarily periplasmic expression of such antibody fragments inE. coliled to rapid cleavage of the SpyTag by proteases.Here we show how this cleavage can be prevented, making the SpyTag technology accessible forE. coliproduced antibodies. We demonstrate a modular toolbox for rapid creation of synthetic IgGs, oligomerized antibodies, and antibodies with different tags or enzymatic functionalities and measure their performance in a variety of immunoassays. Furthermore, we demonstrate surface immobilization, high-throughput screening of antibody libraries, and rapid prototyping of antibodies based on modular antibody assembly.
MBG: Minimizer-based Sparse de Bruijn Graph Construction
Authors: Rautiainen Mikko , Marschall Tobias 
Published: September 2020

MotivationDe Bruijn graphs can be constructed from short reads efficiently and have been used for many purposes. Traditionally long read sequencing technologies have had too high error rates for de Bruijn graph-based methods. Recently, HiFi reads have provided a combination of long read length and low error rate, which enables de Bruijn graphs to be used with HiFi reads.ResultsWe have implemented MBG, a tool for building sparse de Bruijn graphs from HiFi reads. MBG outperforms existing tools for building dense de Bruijn graphs, and can build a graph of 50x coverage whole human genome HiFi reads in four hours on a single core. MBG also assembles the bacterialE. coligenome into a single contig in 8 seconds.AvailabilityPackage manager:https://anaconda.org/bioconda/mbgand source code:https://github.com/maickrau/MBG
Slow rhythmic eye motion predicts periodic alternation of bistable perception
Authors: Choi Woochul , Lee Hyeonsu , Paik Se-Bum 
Published: September 2020

AbstractBistable perception is characterized by periodic alternation between two different perceptual interpretations, the mechanism of which is poorly understood. Herein, we show that perceptual decisions in bistable perception are strongly correlated with slow rhythmic eye motion, the frequency of which varies across individuals. From eye gaze trajectory measurements during three types of bistable tasks, we found that each subject’s gaze position oscillates slowly(less than 1Hz), and that this frequency matches that of bistable perceptual alternation. Notably, the motion of the eye apparently moves in opposite directions before two opposite perceptual decisions, and this enables the prediction of the timing and direction of perceptual alternation from eye motion. We also found that the correlation between eye movement and a perceptual decision is maintained during variations of the alternation frequency by the intentional switching or retaining of perceived states. This result suggests that periodic bistable perception is phase-locked with rhythmic eye motion.
Adaptation of a microfluidic qPCR system for enzyme kinetics studies
Authors: Rembeza Elzbieta , Engqvist Martin KM 
Published: September 2020

AbstractMicrofluidic platforms offer a drastic increase in throughput while minimizing sample usage and hands-on time, which makes them important tools for large-scale biological studies. A range of such systems have been developed for enzyme activity studies, although their complexity largely hinders their application by a wider scientific community. Here we present adaptation of an easy-to-use commercial microfluidic qPCR system for performing enzyme kinetics studies. We demonstrate functionality of the Fluidigm Biomark HD system (the Fluidigm system) by determining kinetic properties of three oxidases in a resorufin-based fluorescent assay. The results obtained in the microfluidic system proved reproducible and comparable to the ones obtained in a standard microplate-based assay. With a wide range of easy-to-use, off-the-shelf components, the microfluidic system presents itself as a simple and customizable platform for high-throughput enzyme activity studies.Graphical abstract
Selective metal ion utilization contributes to the transformation of the activity of yeast polymerase η from DNA polymerization toward RNA polymerization
Authors: Balint Eva , Unk Ildiko 
Published: September 2020

ABSTRACTPolymerase eta (Polη) is a translesion synthesis DNA polymerase directly linked to cancer development. It can bypass several DNA lesions thereby rescuing DNA damage-stalled replication complexes. We previously presented evidence implicatingSaccharomyces cerevisiaePolη in transcription elongation, and identified its specific RNA extension and translesion RNA synthetic activities. However, RNA synthesis by Polη proved rather inefficient under conditions optimal for DNA synthesis. Searching for factors that could enhance its RNA synthetic activity, we have identified the divalent cation of manganese. Here we show, that manganese triggers drastic changes in the activity of Polη. It increases the efficiency of ribonucleoside incorporation into RNA by ∼400-2000-fold opposite undamaged DNA, and ∼3000 and ∼6000-fold opposite TT dimer and 8oxoG, respectively. Importantly, preference for the correct base is maintained with manganese during RNA synthesis. In contrast, activity is strongly impaired, and base discrimination almost lost during DNA synthesis by Polη with manganese. Moreover, Polη shows strong preference for manganese during RNA synthesis even at 25-fold excess magnesium concentration. Based on these, we suggest that selective metal cofactor usage plays an important role in determining the specificity of Polη during synthesis enabling it to function at both replication and transcription.
Women born to older mothers have reduced fertility: Evidence from a natural fertility population
Authors: van den Berg Niels , van Dijk Ingrid , Mourits Rick 
Published: September 2020

AbstractAre daughters of older mothers less fertile? The human mutation rate is high and increases with chronological age. As female oocytes age, they become less functional, reducing female chances at successful reproduction. Increased oocyte mutation loads at advanced age may be passed on to offspring, decreasing fertility among daughters born to older mothers. In this paper we study the effects of maternal ageing on her daughter’s fertility, including total number of children, age at last birth, and neonatal mortality among her children. We study fertility histories of two generations of women from disjoint families from a pre-transitional historical population in the Dutch province of Zeeland. Using mixed effect Poisson models to take within family (sibling) relations into account, we show that fertility is reduced among married daughters who were born at advanced maternal age, with fewer children ever born and earlier ages at last birth. We do not find consistent evidence for effects on neonatal mortality. These results may indicate that women born to older mothers are negatively affected by their mothers’ increased oocyte mutation load.
SHIMS 3.0: Highly efficient single-haplotype iterative mapping and sequencing using ultra-long nanopore reads
Authors: Bellott Daniel W. , Cho Ting-Jan , Jackson Emily K. , Skaletsky Helen , Hughes Jennifer F. , Page David C. 
Published: September 2020

AbstractThe reference sequence of structurally complex regions can only be obtained through a highly accurate clone-based approach that we call Single-Haplotype Iterative Mapping and Sequencing (SHIMS). In recent years, improvements to SHIMS have reduced the cost and time required by two orders of magnitude, but internally repetitive clones still require extensive manual effort to transform draft assemblies into reference-quality finished sequences. Here we describe SHIMS 3.0, an extension of our SHIMS sequencing strategy, using ultra-long nanopore reads to augment the Illumina data from SHIMS 2.0 assemblies and resolve internally repetitive structures. This greatly minimizes the need for manual finishing of Illumina-based draft assemblies, allowing a small team with no prior finishing experience to sequence challenging targets with high accuracy. This protocol proceeds from clone-picking to finished assemblies in 2 weeks for about 80 dollars per clone. We recently used this protocol to produce reference sequence of structurally complex palindromes on chimpanzee and rhesus macaque X chromosomes; as a further demonstration of the capabilities of SHIMS 3.0, we finish the TSPY array on the human Y chromosome, which could not be resolved by previous sequencing methods. Our protocol provides access to structurally complex regions that would otherwise be inaccessible from whole-genome shotgun data or require an impractical amount of manual effort to generate an accurate assembly.
A convolutional neural network for common coordinate registration of high-resolution histology images
Authors: Daly Aidan C. , Geras Krzysztof J. , Bonneau Richard A. 
Published: September 2020

AbstractRegistration of histology images from multiple sources is a pressing problem in large-scale studies of spatial -omics data. Researchers often perform “common coordinate registration,” akin to segmentation, in which samples are partitioned based on tissue type to allow for quantitative comparison of similar regions across samples. Accuracy in such registration requires both high image resolution and global awareness, which mark a difficult balancing act for contemporary deep learning architectures. We present a novel convolutional neural network (CNN) architecture that combines (1) a local classification CNN that extracts features from image patches sampled sparsely across the tissue surface, and (2) a global segmentation CNN that operates on these extracted features. This hybrid network can be trained in an end-to-end manner, and we demonstrate its relative merits over competing approaches on a reference histology dataset as well as two published spatial transcriptomics datasets. We believe that this paradigm will greatly enhance our ability to process spatial -omics data, and has general purpose applications for the processing of high-resolution histology images on commercially available GPUs.
Multi-Objective Approach for Identifying Cancer Subnetwork Markers
Authors: Bayat Faezeh , Davoodi Mansoor 
Published: September 2020

AbstractIdentifying genetic markers for cancer is one of the main challenges in the recent researches. Between different cohorts of genetic markers such as genes or a group of genes like pathways or sub-network, identifying functional modules like subnetwork markers has been more challenging. Network-based classification methods have been successfully used for finding effective cancer subnetwork markers. Combination of metabolic networks and molecular profiles of tumor samples has led researchers to a more accurate prediction of subnetwork markers. However, topological features of the network have not been considered in the activity of the subnetwork. Here, we apply a novel protein-protein interaction network-based classification method that considers topological features of the network in addition to the expression profiles of the samples. We have considered the problem of identifying cancer subnetwork markers as a multi-objective problem which in this approach, each subnetwork’s activity level is measured according to both objectives of the problem; Differential expression level of the genes and topological features of the nodes in the network. We found that the subnetwork markers identified by this method achieve higher performance in the classification of cancer outcome in comparison to the other subnetwork markers.