bluuebunny/crossref_metadata_2025_split huggingface dataset:
Parental feeding preferences rather than sibling competition determine the death of smaller nestlings in asynchronous broods
Authors: Soler Manuel , Ruiz-Raya Francisco , Sánchez-Pérez Lucía , Ibáñez-Álamo Juan Diego 
Published: December 2020

AbstractHatching asynchrony is a reproductive tactic that, through the creation of competitive hierarchies among offspring, allows parents for a quick adjustment of brood size via the death of smaller nestlings. This strategy is considered to be adaptive in case of unpredictable and/or poor environments in which it would guarantee that at least larger nestlings will fledge. Brood reduction is the usual outcome in asynchronously hatched broods since first-hatched nestlings are larger and get a disproportionately larger share of the food delivered by parents, often leading the youngest nestling to starve to death soon after hatching. However, we still do not know the proximate mechanisms of such brood reduction. One possibility is that the smallest nestling is not fed because larger nestlings outcompete it, which implies that nestlings control resource allocation. Alternatively, parents might actively ignore the persistent begging from their smallest nestling, which would involve that parents control food allocation. To determine whether parents or nestlings ultimately induce brood reduction in this situation, we experimentally created asynchronous broods of Eurasian blackbird (Turdus merula) nestlings and quantified food allocation by parents in two different situations: when sibling competition was allowed and, alternatively, when competition was prevented by physically separating nestlings within the nests by using wooden barriers. Our results showed that experimentally introduced smaller nestlings received less food than their larger nestmates both when competition among nestlings was allowed and when it was prevented. When adult males and females are considered separately, males fed the smallest nestling less often regardless of whether sibling competition was allowed or not, but adult females showed no differences. We can conclude that the smallest nestling starves mainly because parents actively ignore its begging. The higher competitive ability of the larger nestlings seem to have little effect given that although the smallest nestling is fed at a higher rate when physical interactions are prevented by the wooden barrier than when not, this difference is not significant. These findings suggest that parents rather than nestlings have the main control over food allocation.
Epigenetic scores for the circulating proteome as tools for disease prediction
Authors: Gadd Danni A , Hillary Robert F , McCartney Daniel L , Zaghlool Shaza B , Stevenson Anna J , Nangle Cliff , Campbell Archie , Flaig Robin , Harris Sarah E , Walker Rosie M , Shi Liu , Tucker-Drob Elliot M , Gieger Christian , Peters Annette , Waldenberger Melanie , Graumann Johannes , McRae Allan F , Deary Ian J , Porteous David J , Hayward Caroline , Visscher Peter M , Cox Simon R , Evans Kathryn L , McIntosh Andrew M , Suhre Karsten , Marioni Riccardo E 
Published: December 2020

AbstractProtein biomarkers have been identified across many age-related morbidities. However, characterising epigenetic influences could further inform disease predictions. Here, we leverage epigenome-wide data to study links between the DNAm signatures of the circulating proteome and incident diseases. Using data from four cohorts, we trained and tested epigenetic scores (EpiScores) for 953 plasma proteins, identifying 109 scores that explained between 1% and 58% of the variance in protein levels after adjusting for known protein quantitative trait loci (pQTL) genetic effects. By projecting these EpiScores into an independent sample, (Generation Scotland; n=9,537) and relating them to incident morbidities over a follow-up of 14 years, we uncovered 137 EpiScore – disease associations. These associations were largely independent of immune cell proportions, common lifestyle and health factors and biological aging. Notably, we found that our diabetes-associated EpiScores highlighted previous top biomarker associations from proteome-wide assessments of diabetes. These EpiScores for protein levels can therefore be a valuable resource for disease prediction and risk stratification.
No evidence for whole-chromosome dosage compensation or global transcriptomic expression differences in spontaneously-aneuploid mutation accumulation lines ofSaccharomyces cerevisiae
Authors: McQueary Holly C. , Behringer Megan G. , Demario Sam , Canas Alexander Joao Jamarillo , Johnson Brittania , Tsfoni Ariella , Chamberlin John , Hall David W. 
Published: December 2020

AbstractAneuploidy, the state in which an organism’s genome contains one or more missing or additional chromosomes, often causes widespread genotypic and phenotypic effects. Most often, aneuploidies are deleterious; the most common examples in humans being Down’s syndrome (Trisomy 21) and Turner’s syndrome (monosomy X). However, aneuploidy is surprisingly common in wild yeast populations. In recent years, there has been debate as to whether yeast contain an innate dosage compensation response that operates at the gene, chromosome, or the whole-genome level, or if natural isolates are robust to aneuploidy without such a mechanism. In this study, we tested for differential gene expression in 20 aneuploid and 16 euploid lines of yeast from two previous mutation accumulation experiments, where selection was minimized and therefore aneuploidies arose spontaneously. We found no evidence for whole-chromosome dosage compensation in aneuploid yeast but did find some evidence for attenuation of expression on a gene-by-gene basis. We additionally found that aneuploidy has no effect on the expression of the rest of the genome (i.e. “trans” genes), and that very few mutually exclusive aneuploid lines shared differentially expressed genes. However, we found there was a small set of genes that exhibited a shared expression response in the euploid lines, suggesting an effect of mutation accumulation on gene expression. Our findings contribute to our understanding of aneuploidy in yeast and support the hypothesis that there is no innate dosage compensation mechanism at the whole-chromosome level.
A Kernel-Based Change Detection Method to Map Shifts in Phytoplankton Communities Measured by Flow Cytometry
Authors: Jones Corinne , Clayton Sophie , Ribalet François , Armbrust E. Virginia , Harchaoui Zaid 
Published: December 2020

SummaryAutomated, ship-board flow cytometers provide high-resolution maps of phytoplankton composition over large swaths of the world’s oceans. They therefore pave the way for understanding how environmental conditions shape community structure. Identification of community changes along a cruise transect commonly segments the data into distinct regions. However, existing segmentation methods are generally not applicable to flow cytometry data, as this data is recorded as “point cloud” data, with hundreds or thousands of particles measured during each time interval. Moreover, nonparametric segmentation methods that do not rely on prior knowledge of the number of species, are desirable to map community shifts.We present CytoSegmenter, a kernel-based change-point estimation method for segmenting point cloud data that does not rely on parametric assumptions on the data distributions. Our method relies on a Hilbertian embedding of point clouds that allows us to work with point cloud data similarly to vectorial data. The change-point locations can be found using an efficient dynamic programming algorithm. The method can be used to automatically segment long series of underway flow cytometry data.Through an analysis of 12 cruises, we demonstrate that CytoSegmenter allows us to locate abrupt changes in phytoplankton community structure. We show that the changes in community structure generally coincide with changes in the temperature and salinity of the ocean. We also illustrate how the main parameter of CytoSegmenter can be easily calibrated using limited auxiliary annotated data.CytoSegmenter is publicly available and implemented in the programming language Python. The method is generally applicable for segmenting series of point cloud data from any domain. Moreover, it readily scales to thousands of point clouds, each containing thousands of points. In the context of underway flow cytometry data, it does not require prior clustering of particles to define taxa labels, eliminating a potential source of error. This represents an important advance in automating the analysis of large datasets now emerging in biological oceanography and other fields. It also allows for the approach to potentially be applied during research cruises.
An Interactive Health Game Using Machine Learning: A Prototype
Authors: Ay Esra , Eken Burak , Önal-Süzek Tuğba 
Published: December 2020

AbstractAccording to World Health Organization (WHO) 2016 report, there are over 650 million obese adults and more than 2 billion overweight individuals in the world and it is estimated that this number will reach 2.7 billion in 2025 [1]. A sedentary lifestyle with low physical activity is considered to be one of the most effective environmental effects leading to various chronic disease phenotypes such as obesity and metabolic syndrome. On average, every 1 out of 3 people over the age of 20 in Turkey are known to have struggled with the metabolic syndrome [2]. Our project aims to apply the concept of “serious gaming”, to entertain people, play games, socialize and exercise in parallel to increase the ratio of the healthy individuals in our society. In this project, we applied machine learning techniques to integrate real-life accelerometer and gyroscope sensor data obtained from mobile phones to develop an interactive mobile based exercise game which does not require any external device such as smart watches. To our knowledge and research, our game is the first mobile-only interactive serious game that integrates machine learning techniques and an encouraging virtual environment to the individuals in need of exercise.
BAP1/ASXL complex modulation regulates Epithelial-Mesenchymal Transition during trophoblast differentiation and invasion
Authors: Perez-Garcia Vicente , Lopez-Jimenez Pablo , Burton Graham J , Moffett Ashley , Turco Margherita Y. , Hemberger Myriam 
Published: December 2020

AbstractNormal function of the placenta depends on the earliest developmental stages when trophoblast cells differentiate and invade into the endometrium to establish the definitive maternal-fetal interface. Previously, we identified the ubiquitously expressed tumour suppressor BRCA1-associated protein 1 (BAP1) as a central factor of a novel molecular node controlling early mouse placentation. However, functional insights into how BAP1 regulates trophoblast biology are still missing. Using CRISPR/Cas9 knockout and overexpression technology, here we demonstrate that the downregulation of BAP1 protein is essential to trigger epithelial-mesenchymal transition (EMT) during trophoblast differentiation associated with a gain of invasiveness. This function, which is conserved in mouse and humans, is dependent on the binding of BAP1 binding to Additional sex comb-like (ASXL1/2/3) proteins to form the Polycomb repressive deubiquitinase (PR-DUB) complex. Our results reveal that the physiological modulation of BAP1 determines the invasive properties of trophoblast, delineating a new role of the BAP1 PR-DUB complex in regulating early placentation.
Human retrosplenial theta and alpha modulation in active spatial navigation
Authors: Do Tien-Thong Nguyen , Lin Chin-Teng , Gramann Klaus 
Published: December 2020

AbstractSpatial navigation is a complex cognitive process based on multiple senses that are integrated and processed by a wide network of brain areas. Previous studies have revealed the retrosplenial complex (RSC) to be modulated in a task-related manner during navigation. However, these studies restricted participants’ movement to stationary setups, which might have impacted heading computations due to the absence of vestibular and proprioceptive inputs. Here, we investigated neural dynamics of RSC in an active spatial navigation task where participants actively ambulated from one location to several other points while the position of a landmark and the starting location were updated. The results revealed theta power in the RSC to be pronounced during heading changes but not during translational movements, indicating that physical rotations induce human RSC theta activity. This finding provides a potential evidence of head-direction computation in RSC in healthy humans during active spatial navigation.
Active and machine learning-based approaches to rapidly enhance microbial chemical production
Authors: Kumar Prashant , Adamczyk Paul A. , Zhang Xiaolin , Andrade Ramon Bonela , Romero Philip A. , Ramanathan Parameswaran , Reed Jennifer L. 
Published: December 2020

ABSTRACTIn order to make renewable fuels and chemicals from microbes, new methods are required to engineer microbes more intelligently. Computational approaches, to engineer strains for enhanced chemical production typically rely on detailed mechanistic models (e.g., kinetic/stoichiometric models of metabolism) — requiring many experimental datasets for their parameterization—while experimental methods may require screening large mutant libraries to explore the design space for the few mutants with desired behaviors. To address these limitations, we developed an active and machine learning approach (ActiveOpt) to intelligently guide experiments to arrive at an optimal phenotype with minimal measured datasets. ActiveOpt was applied to two separate case studies to evaluate its potential to increase valine yields and neurosporene productivity inEscherichia coli. In both the cases, ActiveOpt identified the best performing strain in fewer experiments than the case studies used. This work demonstrates that machine and active learning approaches have the potential to greatly facilitate metabolic engineering efforts to rapidly achieve its objectives.
A non-coding indel polymorphism in thefruitlessgene ofDrosophila melanogasterexhibits antagonistically pleiotropic fitness effects
Authors: Jardine Michael D. , Ruzicka Filip , Diffley Charlotte , Fowler Kevin , Reuter Max 
Published: December 2020

AbstractThe amount of genetic variation for fitness within populations tends to exceed that expected under mutation-selection-drift balance. Several mechanisms have been proposed to actively maintain polymorphism and account for this discrepancy, including antagonistic pleiotropy (AP), where allelic variants have opposing effects on different components of fitness. Here we identify a non-coding indel polymorphism in thefruitlessgene ofDrosophila melanogasterand measure survival and reproductive components of fitness in males and females of replicate lines carrying one or the other allele. Expressing the fruitless region in a hemizygous state we observe a pattern of AP, with one allele resulting in greater reproductive fitness while the other confers greater survival to adulthood. Different fitness effects were observed in an alternative genetic background, suggesting widespread epistatic effects. Our findings link sequence-level variation at a single locus with complex effects on a range of fitness components, thus helping to explain the maintenance of genetic variation for fitness. Transcription factors, such asfruitless, may be prime candidates for targets of balancing selection since they interact with multiple target loci and their associated phenotypic effects.
Parasitoid wasp venom targets host immune cell production in aDrosophila-parasitoid interaction
Authors: Trainor Jordann E. , Pooja KR , Mortimer Nathan T. 
Published: December 2020

AbstractThe interactions betweenDrosophila melanogasterand the parasitoid wasps that infectDrosophilaspecies provide an important model for understanding host-parasite relationships. Following parasitoid infection,D. melanogasterlarvae mount a response in which immune cells (hemocytes) form a capsule around the wasp egg, which then melanizes leading to death of the parasitoid. Previous studies have found that host hemocyte load, the number of hemocytes available for the encapsulation response, and the production of lamellocytes, an infection induced hemocyte type, are major determinants of host resistance. Parasitoids have evolved various virulence mechanisms to overcome the immune response of theD. melanogasterhost, including both active immune suppression by venom proteins and passive immune evasive mechanisms. We find that a previously undescribed parasitoid species,Asobara sp. AsDen, utilizes an active virulence mechanism to infectD. melanogasterhosts.Asobara sp. AsDeninfection inhibits host hemocyte expression ofmsn, a member of the JNK signaling pathway, which plays a role in lamellocyte production.Asobara sp. AsDeninfection restricts the production of lamellocytes as assayed by hemocyte cell morphology and alteredmsnexpression. Our findings suggest thatAsobara sp. AsDenvenom targets host signaling to suppress immunity.DeclarationsFundingThis work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM133760.Availability of data and materialSequence data has been deposited in GenBank under accession #MT498809. Custom BLAST databases are available on request to corresponding author.Authors’ contributionsConceived of or designed study: J.E.T., N.T.M.; Performed research: J.E.T., P.K.; Analyzed data: J.E.T., P.K., N.T.M.; Wrote the paper: J.E.T., P.K., N.T.M.
Coherent natural scene structure facilitates the extraction of task-relevant object information in visual cortex
Authors: Kaiser Daniel , Häberle Greta , Cichy Radoslaw M. 
Published: December 2020

AbstractLooking for objects within complex natural environments is a task everybody performs multiple times each day. In this study, we explore how the brain uses the typical composition of real-world environments to efficiently solve this task. We recorded fMRI activity while participants performed two different categorization tasks on natural scenes. In the object task, they indicated whether the scene contained a person or a car, while in the scene task, they indicated whether the scene depicted an urban or a rural environment. Critically, each scene was presented in an “intact” way, preserving its coherent structure, or in a “jumbled” way, with information swapped across quadrants. In both tasks, participants’ categorization was more accurate and faster for intact scenes. These behavioral benefits were accompanied by stronger responses to intact than to jumbled scenes across high-level visual cortex. To track the amount of object information in visual cortex, we correlated multi-voxel response patterns during the two categorization tasks with response patterns evoked by people and cars in isolation. We found that object information in object- and body-selective cortex was enhanced when the object was embedded in an intact, rather than a jumbled scene. However, this enhancement was only found in the object task: When participants instead categorized the scenes, object information did not differ between intact and jumbled scenes. Together, these results indicate that coherent scene structure facilitates the extraction of object information in a task-dependent way, suggesting that interactions between the object and scene processing pathways adaptively support behavioral goals.
Convolutional neural network for automated mass segmentation in mammography
Authors: Abdelhafiz Dina , Bi Jinbo , Ammar Reda , Yang Clifford , Nabavi Sheida 
Published: December 2020

AbstractBackgroundAutomatic segmentation and localization of lesions in mammogram (MG) images are challenging even with employing advanced methods such as deep learning (DL) methods. We developed a new model based on the architecture of the semantic segmentation U-Net model to precisely segment mass lesions in MG images. The proposed end-to-end convolutional neural network (CNN) based model extracts contextual information by combining low-level and high-level features. We trained the proposed model using huge publicly available databases, (CBIS-DDSM, BCDR-01, and INbreast), and a private database from the University of Connecticut Health Center (UCHC).ResultsWe compared the performance of the proposed model with those of the state-of-the-art DL models including the fully convolutional network (FCN), SegNet, Dilated-Net, original U-Net, and Faster R-CNN models and the conventional region growing (RG) method. The proposed Vanilla U-Net model outperforms the Faster R-CNN model significantly in terms of the runtime and the Intersection over Union metric (IOU). Training with digitized film-based and fully digitized MG images, the proposed Vanilla U-Net model achieves a mean test accuracy of 92.6%. The proposed model achieves a mean Dice coefficient index (DI) of 0.951 and a mean IOU of 0.909 that show how close the output segments are to the corresponding lesions in the ground truth maps. Data augmentation has been very effective in our experiments resulting in an increase in the mean DI and the mean IOU from 0.922 to 0.951 and 0.856 to 0.909, respectively.ConclusionsThe proposed Vanilla U-Net based model can be used for precise segmentation of masses in MG images. This is because the segmentation process incorporates more multi-scale spatial context, and captures more local and global context to predict a precise pixel-wise segmentation map of an input full MG image. These detected maps can help radiologists in differentiating benign and malignant lesions depend on the lesion shapes. We show that using transfer learning, introducing augmentation, and modifying the architecture of the original model results in better performance in terms of the mean accuracy, the mean DI, and the mean IOU in detecting mass lesion compared to the other DL and the conventional models.
Role of bradykinin type 2 receptors in human sweat secretion: translational evidence does not support a functional relationship
Authors: Wilson Thad E. , Narra Seetharam , Metzler-Wilson Kristen , Schneider Artur , Bullens Kelsey A. , Holt Ian S. 
Published: December 2020

AbstractBradykinin increases skin blood flow via a cGMP mechanism but its role in sweatingin vivois unclear. There is a current need to translate cell culture and non-human paw pad studies intoin vivohuman preparations to test for therapeutic viability for disorders affecting sweat glands. Protocol 1: physiological sweating was induced in 10 healthy subjects via perfusing warm (46-48°C) water through a tube-lined suit while bradykinin type 2 receptor (B2R) antagonist (HOE-140; 40 μM) and only the vehicle (lactated Ringer’s) were perfused intradermally via microdialysis. Heat stress increased sweat rate (HOE-140 = +0.79±0.12 and vehicle = +0.64±0.10 mg/cm2/min), but no differences were noted with B2R antagonism. Protocol 2: pharmacological sweating was induced in 6 healthy subjects via intradermally perfusing pilocarpine (1.67 mg/ml) followed by the same B2R antagonist approach. Pilocarpine increased sweating (HOE-140 = +0.38±0.16 and vehicle = +0.32±0.12 mg/cm2/min); again no differences were observed with B2R antagonism. Lastly, 5 additional subjects were recruited for various control experiments which identified that a functional dose of HOE-140 was utilized and it was not sudorific during normothermic conditions. These data indicate B2R antagonists do not modulate physiologically-or pharmacologically-induced eccrine secretion volumes. Thus, B2R agonist/antagonist development as a potential therapeutic target for hypo- and hyperhidrosis appears unwarranted.