bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning does not outperform classical machine learning for cell-type annotation
Authors: Köhler Niklas D. , Büttner Maren , Andriamanga Niry , Theis Fabian J. 
Published: May 2019

AbstractDeep learning has revolutionized image analysis and natural language processing with remarkable accuracies in prediction tasks, such as image labeling and semantic segmentation or named-entity recognition and semantic role labeling. Specifically, the combination of algorithmic and hardware advances with the appearance of large and well-labeled datasets has led up to seminal contributions in these fields.The emergence of large amounts of data from single-cell RNA-seq and the recent global effort to chart all cell types in the Human Cell Atlas has attracted an interest in deep-learning applications. However, all current approaches are unsupervised,i.e., learning of latent spaces without using any cell labels, even though supervised learning approaches are often more powerful in feature learning and the most popular approach in the current AI revolution by far. Here, we ask why this is the case. In particular we ask whether supervised deep learning can be used for cell annotation,i.e.to predict cell-type labels from single-cell gene expression profiles. After evaluating 10 classification methods across 14 datasets, we notably find that deep learning does not outperform classical machine-learning methods in the task. Thus, cell-type prediction based on gene-signature derived cell-type labels is potentially too simplistic a task for complex non-linear methods, which demands better labels of functional single-cell readouts.
Rapid learning and unlearning of predicted sensory delays in self-generated touch
Authors: Kilteni Konstantina , Houborg Christian , Ehrsson H. Henrik 
Published: May 2019

AbstractSelf-generated touch feels less intense and less ticklish than identical externally generated touch. This somatosensory attenuation occurs because the brain predicts the tactile consequences of our self-generated movements. To produce attenuation, the tactile predictions need to be time-locked to the movement, but how the brain maintains this temporal tuning remains unknown. Using a bimanual self-touch paradigm, we demonstrate that people can rapidly unlearn to attenuate touch immediately after their movement and learn to attenuate delayed touch instead, after repeated exposure to a systematic delay between the movement and the resulting touch. The magnitudes of the unlearning and learning effects are correlated and dependent on the number of trials that participants have been exposed to. We further show that delayed touches feel less ticklish and non-delayed touches more ticklish after exposure to the systematic delay. These findings demonstrate that the attenuation of self-generated touch is adaptive.
Immune disease variants modulate gene expression in regulatory CD4+ T cells and inform drug targets
Authors: Bossini-Castillo Lara , Glinos Dafni A. , Kunowska Natalia , Golda Gosia , Lamikanra Abigail , Spitzer Michaela , Soskic Blagoje , Cano-Gamez Eddie , Smyth Deborah J. , Cattermole Claire , Alasoo Kaur , Mann Alice , Kundu Kousik , Soranzo Nicole , Dunham Ian , Roberts David , Trynka Gosia 
Published: May 2019

AbstractIdentifying cellular functions dysregulated by disease associated variants could implicate novel pathways for drug targeting or modulation in cell therapies. Variants associated with immune diseases point towards the role of CD4+ regulatory T cells (Tregs), cell type critical for immune homeostasis. To translate the effects of immune disease alleles on Treg function we mapped genetic regulation (QTL) of gene expression and chromatin activity in Tregs. We identified 123 loci where Treg QTLs colocalized with immune disease variants. These colocalizations indicated that dysregulation of key Treg pathways, including cell activation via CD28 and IL-2 signalling mediated by STAT5A contribute to the shared pathobiology of immune diseases. Finally, using disease GWAS signals colocalizing with Treg QTLs, we identified 34 known drug targets and 270 targets with drug tractability evidence. Our study is the first in-depth characterization of immune disease variant effects on Treg gene expression modulation and dysregulation of Treg function.
Human Auditory Ossicles as an Alternative Optimal Source of Ancient DNA
Authors: Sirak Kendra , Fernandes Daniel , Cheronet Olivia , Harney Eadaoin , Mah Matthew , Mallick Swapan , Rohland Nadin , Adamski Nicole , Broomandkhoshbacht Nasreen , Callan Kimberly , Candilio Francesca , Lawson Ann Marie , Mandl Kirsten , Oppenheimer Jonas , Stewardson Kristin , Zalzala Fatma , Anders Alexandra , Bartík Juraj , Coppa Alfredo , Tumen Dashtseveg , Évinger Sándor , Farkaš Zdeněk , Hajdu Tamás , Bayarsaikhan Jamsranjav , McIntyre Lauren , Moiseyev Vyacheslav , Pap Ildikó , Pietrusewsky Michael , Raczky Pál , Šefčáková Alena , Soficaru Andrei , Szeniczey Tamás , Szőke Béla Miklós , Tuvshinjargal Tumurbaatar , Van Gerven Dennis , Vasilyev Sergey , Bell Lynne , Reich David , Pinhasi Ron 
Published: May 2019

ABSTRACTDNA recovery from ancient human remains has revolutionized our ability to reconstruct the genetic landscape of the past. Ancient DNA research has benefited from the identification of skeletal elements, such as the cochlear part of the osseous inner ear, that provide optimal contexts for DNA preservation; however, the rich genetic information obtained from the cochlea must be counterbalanced against the loss of valuable morphological information caused by its sampling. Motivated by similarities in developmental processes and histological properties between the cochlea and auditory ossicles, we evaluated the efficacy of ossicles as an alternative source of ancient DNA. We demonstrate that ossicles perform comparably to the cochlea in terms of DNA recovery, finding no substantial reduction in data quality, quantity, or authenticity across a range of preservation conditions. Ossicles can be sampled from intact skulls or disarticulated petrous bones without damage to surrounding bone, and we argue that, when available, they should be selected over the cochlea to reduce damage to skeletal integrity. These results identify a second optimal skeletal element for ancient DNA analysis and add to a growing toolkit of sampling methods that help to better preserve skeletal remains for future research while maximizing the likelihood that ancient DNA analysis will produce useable results.
Structural characterization of covalently stabilized human cystatin C oligomers
Authors: Chrabąszczewska Magdalena , Sieradzan Adam K. , Rodziewicz-Motowidło Sylwia , Grubb Anders , Dobson Christopher M. , Kumita Janet R. , Kozak Maciej 
Published: May 2019

AbstractHuman cystatin C (HCC), a cysteine-protease inhibitor, exists as a folded monomer under physiological conditions but has the ability to self-assemble via domain swapping into multimeric states, including oligomers with a doughnut-like structure. The structure of the monomeric HCC has been solved by X-ray crystallography, and a covalently linked version of HCC (stab-1 HCC) is able to form stable oligomeric species containing 10-12 monomeric subunits. We have performed molecular modeling, and in conjunction with experimental parameters obtained from AFM, TEM and SAXS measurements, we observe that the structures are essentially flat, with a height of about 2 nm, and the distance between the outer edge of the ring and the edge of the central cavity is ~5.1 nm. These dimensions correspond to the height and diameter of one stab-1 HCC subunit and we present a dodecamer model for stabilized cystatin C oligomers using molecular dynamics simulations and experimentally measured parameters. Given that oligomeric species in protein aggregation reactions are often transient and very highly heterogeneous, the structural information presented here on these isolated stab-1 HCC oligomers may provide useful to further explore the physiological relevance of different structural species of cystatin C in relationship to protein misfolding disease
GATA3 mutation disrupts a functional network governed by estrogen receptor, FOXA1 and GATA3
Authors: Takaku Motoki , Grimm Sara A. , Kumar Bony De , Bennett Brian D. , Wade Paul A. 
Published: May 2019

AbstractEstrogen receptors (ER) are part of the nuclear receptor superfamily of transcription factors and are activated by the steroid hormone 17β-estradiol. ER forms a regulatory network in conjunction with other transcription factors, such as FOXA1 and GATA3. GATA3 has been identified as one of the most frequently mutated genes in breast cancer and is capable of specifying chromatin localization of FOXA1 and ER. How GATA3 mutations impact this transcriptional network is unknown. Here we investigate the function of one of the recurrent patient-derived GATA3 mutations (R330fs) on this regulatory network. Genomic analysis indicates that the R330fs mutant can disrupt the cooperative action of ER, FOXA1, and GATA3, and induce a change in chromatin localization of these factors. Relocalization of ER and FOXA1 is associated with altered chromatin architecture, which leads to differential gene expression in GATA3 mutant cells. These results suggest an active role for GATA3 mutants in ER positive breast tumors.
Defects in mating behavior are the primary cause of sterility inC. elegansmales at elevated temperature
Authors: Nett Emily M. , Sepulveda Nicholas B. , Petrella Lisa N. 
Published: May 2019

AbstractReproduction is a fundamental imperative of all forms of life. For all the advantages sexual reproduction confers, it has a deeply conserved flaw: it is temperature sensitive. As temperatures rise, fertility decreases. Across species male fertility is particularly sensitive to elevated temperature. Previously we have shown in the model nematode wormC. elegans, that all males are fertile at 20°C but almost all males have lost fertility at 27°C. Male fertility is dependent on the production functional sperm, successful mating and transfer of sperm, and successful fertilization post-mating. To determine how male fertility is impacted by elevated temperature we analyzed these aspects of male reproduction at 27°C in three wild-type strains ofC. elegans: JU1171, LKC34, and N2. We found no effect of elevated temperature on the number of immature non-motile spermatids formed. There was a weak effect of elevated temperature on sperm activation that may negatively impact sperm function. In stark contrast, there was a strong effect of elevated temperature on male mating behavior and sperm transfer such that males very rarely successfully completed mating when exposed to 27°C. Therefore, we propose a model where elevated temperature reduces male fertility due to the negative impacts of temperature on the somatic tissues necessary for mating. Loss of successful mating at elevated temperature overrides any effects that temperature may have on the germline or sperm cells.
Optimizing functional groups in ecosystem models: Case study of the Great Barrier Reef
Authors: Haller-Bull Vanessa , Rovenskaya Elena 
Published: May 2019

AbstractUncertainty is inherent in ecosystem modelling, however its effects on modelling results are often poorly understood or ignored. This study addresses the issue of structural uncertainty or, more specifically, model resolution and its impact on the analysis of ecosystem vulnerability to threats. While guidelines for node assignments exist, they are not underlined with quantitative analysis. Different resolutions of a coral reef network are investigated by comparing the simulated network dynamics over time in various threat scenarios. We demonstrate that the error between a higher-resolution and a lower-resolution models increases, first slowly then rapidly with increased degree of node aggregation. This informs the choice of an optimal model resolution whereby a finer level of a food web representation yields only minimal additional accuracy, while increasing computational cost substantially. Furthermore, our analysis shows that species biomass ratio and the production ratio are important parameters to guide node aggregation to minimize the error.
Neural pathways linking hypoxia with pectoral fin movements in Danio rerio
Authors: Rosales Kaila , Yeh Chen-Min , How Javier J. , Villa-Real Reginno , DePasquale Elizabeth , Groisman Alex , Chalasani Sreekanth H. 
Published: May 2019

AbstractZebrafish larvae respond to hypoxia by increasing a number of ventilatory behaviors. During development, these animals switch from skin-resident to gill-resident neuroendocrine cells around 7 days post fertilization (d.p.f.) to detect hypoxia and drive adaptive behaviors. Here, we probe the neural pathways that receive inputs from skin-resident neuroendocrine cells and alter pectoral fin movements. We first show that a 5 d.p.f. larva increases its pectoral fin movements and heart activity upon hypoxia exposure. Next, we map the downstream neural circuitry and show that individual vagal sensory neurons receive inputs from multiple oxygen-sensing neuroendocrine cells. We then use calcium imaging to show that neurons in the second, but not third, vagal sensory ganglia show increases in the magnitude of their hypoxia-evoked responses. Finally, we link purinergic signaling between neuroendocrine cells and second vagal sensory neurons to increases in pectoral fin movements. Collectively, we suggest that vagal sensory neurons transform hypoxic stimuli into respiratory behaviors.
An Automated 3D Analysis Framework for Optical Coherence Tomography Angiography
Authors: Sarabi Mona Sharifi , Gahm Jin Kyu , Khansari Maziyar M. , Zhang Jiong , Kashani Amir H. , Shi Yonggang 
Published: May 2019

AbstractOptical Coherence Tomography Angiography (OCTA) is a novel, non-invasive imaging modality of retinal capillaries at micron resolution. While OCTA generates 3D image volumes, current analytic methods rely on 2Den faceprojection images for quantitative analysis. This obscures the 3D vascular geometry and prevents accurate characterization of retinal vessel networks. In this paper, we have developed an automated analysis framework that preserves the 3D geometry of OCTA data. This framework uses curvelet-based denoising, optimally oriented flux (OOF) vessel enhancement and projection artifact removal, as well as the generation of 3D vessel length from the Hamilton-Jacobi skeleton. We implement this method on a dataset of 338 OCTA scans from human subjects with diabetic retinopathy (DR) which is known to cause decrease in capillary density and compare them to healthy controls. Our results indicate that 3D vessel-skeleton-length (3D-VSL) captures differences in both superficial and deep capillary density that are not apparent in 2D vessel skeleton analyses. In statistical analysis, we show that the 3D small-vessel-skeleton-length (3D-SVSL), which is computed after the removal of the large vessels and associated projection artifacts, provides a novel metric to detect group differences between healthy controls and progressive stages of DR.This work was supported in part by NIH grants UH3NS100614, R21EY027879, U01EY025864, K08EY027006, P41EB015922, P30EY029220, Research to Prevent Blindness, and UL1TR001855 and UL1TR000130 from the National Center for Advancing Translational Science (NCATS) of the U.S. National Institutes of Health.
The Role of Premature Evidence Accumulation in Making Difficult Perceptual Decisions under Temporal Uncertainty
Authors: Devine Ciara A. , Gaffney Christine , Loughnane Gerard , Kelly Simon P. , O’Connell Redmond G. 
Published: May 2019

AbstractThe computations and neural processes underpinning decision making have primarily been investigated using highly simplified tasks in which stimulus onsets cue observers to start accumulating choice-relevant information. Yet, in daily life we are rarely afforded the luxury of knowing precisely when choice-relevant information will appear. Here, we examined neural indices of decision formation while subjects discriminated subtle stimulus feature changes whose timing relative to stimulus onset (‘foreperiod’) was uncertain. Joint analysis of behavioral error patterns and neural decision signal dynamics indicated that subjects systematically began the accumulation process before any informative evidence was presented, and further, that accumulation onset timing varied systematically as a function of the foreperiod of the preceding trial. These results suggest that the brain can adjust to temporal uncertainty by strategically modulating accumulation onset timing according to statistical regularities in the temporal structure of the sensory environment with particular emphasis on recent experience.
Understanding Cognitive Impairment in Mood Disorders: Mediation Analyses in the UK Biobank Cohort
Authors: Cullen Breda , Smith Daniel J. , Deary Ian J. , Pell Jill P. , Keyes Katherine M. , Evans Jonathan J. 
Published: May 2019

AbstractBackgroundCognitive impairment is strongly linked with persistent disability in people with mood disorders, but the factors that explain cognitive impairment in this population are unclear.AimsWe aimed to estimate the total effect of (i) bipolar disorder (BD) and (ii) major depression on cognitive function, and the magnitude of the effect that was explained by potentially modifiable intermediate factors.MethodCross-sectional study using baseline data from the UK Biobank cohort. Participants were categorised as BD (N=2,709), major depression (N=50,975), or no mood disorder (N=102,931 to 105,284). The outcomes were computerised tests of reasoning, reaction time and memory. The potential mediators were cardiometabolic disease and psychotropic medication. Analyses were informed by graphical methods, and controlled for confounding using regression, propensity score-based methods, and G-computation.ResultsGroup differences of small magnitude were found on a visuospatial memory test. Z-score differences for BD were in the range −0.23 to −0.17 (95% CI range −0.39 to −0.03) across different estimation methods, and approximately −0.07 (95% CI −0.10 to −0.03) for major depression. One-quarter of the effect was mediated via psychotropic medication in the BD group (−0.05; 95% CI −0.09 to −0.01). No evidence was found for mediation via cardiometabolic disease.ConclusionsIn a large community-based sample in middle to early old age, BD and depression were associated with lower visuospatial memory performance, in part potentially due to psychotropic medication use. Mood disorders and their treatments will have increasing importance for population cognitive health as the proportion of older adults continues to grow.
Biogeographical patterns in soil bacterial communities across the Arctic region
Authors: Malard Lucie A , Anwar Muhammad Zohaib , Jacobsen Carsten S , Pearce David A 
Published: May 2019

AbstractThe considerable microbial diversity of soils, their variety and key role in biogeochemical cycling has led to growing interest in their global distribution and the impact that environmental change might have at the regional level. In the broadest study of Arctic soil bacterial communities to date, we used high-throughput DNA sequencing to investigate the bacterial diversity from 200 independent Arctic soil samples from 43 sites. We quantified the impact of spatial and environmental factors on bacterial community structure using variation partitioning analysis, illustrating a non-random distribution across the region. pH was confirmed as the key environmental driver structuring Arctic soil bacterial communities, while total organic carbon, moisture and conductivity were shown to have little effect. Specialist taxa were more abundant in acidic and alkaline soils while generalist taxa were more abundant in acidoneutral soils. Of 48,147 bacterial taxa, a core microbiome composed of only 13 taxa that were ubiquitously distributed and present within 95% of samples was identified, illustrating the high potential for endemism in the region. Overall, our results demonstrate the importance of spatial and edaphic factors on the structure of Arctic soil bacterial communities.
Using a collaborative data collection method to update life-history values for snapper and grouper in Indonesia’s deep-slope demersal fishery
Authors: Wibisono Elle , Mous Peter , Humphries Austin 
Published: May 2019

AbstractThe deep-slope demersal fishery that targets snapper and grouper species is an important fishery in Indonesia. Boats operate at depths between 50-500 m using drop lines and bottom long lines. There are few data, however, on the basic characteristics of the fishery which impedes accurate stock assessments and the establishment of harvest control rules. To address this gap, we developed a collaborative data collection and recording system for species and length composition of commercial catches. The Crew-Operated Data Recording System (CODRS) involves fishers who take photos of each individual fish in the catch along with a low-cost vessel tracking system. As it relies on fisher’s collaboration and willingness to share data, CODRS is comparable with a logbook system but enables verification of species identification with greater spatial resolution. We implemented this system from 2015 to 2018 and gathered data from 251 captains and 2,707 fishing trips, which yielded more than one million individual fish, or 2,680 tons. While there were over 100 species in the fishery, we found that the top five species accounted for approximately half of the total catch. We also unveiled fifteen species previously not associated with the fishery due to the fish being eaten on-board, used as bait, or sold prior to being recorded by traders. Using these data, we updated life-history parameters (length at maturity, optimum fishing length, asymptotic length, and maximum length) of the top 50 species in the fishery based on the maximum observed length; this study resulted in higher estimates for maximum length, most likely due to the high sampling size. For some species, the discrepancies between different sources were large, whereas others were not. This collaborative data collection method and findings are useful for scientists and managers interested in conducting length-based stock assessments to establish harvest control rules for data-poor fisheries.
Fully Interpretable Deep Learning Model of Transcriptional Control
Authors: Liu Yi , Barr Kenneth , Reinitz John 
Published: May 2019

AbstractThe universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent work in the system biology community to employ DNNs to solve important problems in functional genomics and molecular genetics. Because of the black box nature of DNNs, such assumptions, while useful in practice, are unsatisfactory for scientific analysis. In this paper, we give an example of a DNN in which every layer is interpretable. Moreover, this DNN is biologically validated and predictive. We derive our DNN from a systems biology model that was not previously recognized as having a DNN structure. This DNN is concerned with a key unsolved biological problem, which is to understand the DNA regulatory code which controls how genes in multicellular organisms are turned on and off. Although we apply our DNN to data from the early embryo of the fruit flyDrosophila,this system serves as a testbed for analysis of much larger data sets obtained by systems biology studies on a genomic scale.