bluuebunny/crossref_metadata_2025_split huggingface dataset:
Polygenic Prediction of Substance Use Disorders in Clinical and Population Samples
Authors: Barr Peter B. , Ksinan Albert , Su Jinni , Johnson Emma C. , Meyers Jacquelyn L. , Wetherill Leah , Latvala Antti , Aliev Fazil , Chan Grace , Kuperman Samuel , Nurnberger John , Kamarajan Chella , Anokhin Andrey , Agrawal Arpana , Rose Richard J. , Edenberg Howard J. , Schuckit Marc , Kaprio Jaakko , Dick Danielle M. 
Published: August 2019

AbstractGenome-wide, polygenic risk scores (PRS) have emerged as a useful way to characterize genetic liability using genotypic data. There is growing evidence that PRS may prove useful to identify those at increased risk for developing certain diseases. The current utility of PRS in relation to alcohol use disorders (AUD) remains an open question. Using data from both a population-based sample [the FinnTwin12 (FT12) study] and a high risk sample [the Collaborative Study on the Genetics of Alcoholism (COGA)], we examined the association between PRSs derived from genome-wide association studies (GWASs) of 1) alcohol dependence/alcohol problems, 2) alcohol consumption, and 3) risky behaviors with AUD and other substance use disorder (SUD) symptoms. Individuals in the top 20%, 10%, and 5% of PRSs had increasingly greater odds of having an AUD compared to the lower end of the continuum in both COGA (80th% OR = 1.95; 90th% OR = 2.03; 95th% OR = 2.13) and FT12 (80th% OR = 1.77; 90th% OR = 2.27; 95th% OR = 2.39). Those in the top 5% reported greater levels of licit (alcohol and nicotine) and illicit (cannabis) SUD symptoms. PRSs can predict elevated risk for SUD in independent samples. However, clinical utility of these scores in their current form is modest. As these scores become more predictive of SUD, they may become useful to practitioners. Improvement in predictive ability will likely be dependent on increasing the size of well-phenotyped discovery samples.
Isometric exercise facilitates attention to salient events in women via the noradrenergic system
Authors: Mather Mara , Huang Ringo , Clewett David , Nielsen Shawn E. , Velasco Ricardo , Tu Kristie , Han Sophia , Kennedy Briana 
Published: August 2019

AbstractThe locus coeruleus (LC) plays a critical role in regulating attention via the release of norepinephrine (NE), with levels of tonic LC activity constraining the intensity of phasic LC responses. However, the effects of manipulating tonic LC-NE activity on phasic activity have yet to be demonstrated in humans. In the current fMRI study, we used isometric handgrip to modulate tonic LC-NE activity in the time period immediately afterwards. During this post-handgrip time, an oddball detection task was used to probe how changes in tonic arousal influenced functional coordination between the LC and a right frontoparietal network that supports attentional selectivity. As expected, the frontoparietal network responded more to infrequent target and novel sounds than to frequent sounds. Across participants, greater LC-frontoparietal functional connectivity, pupil dilation, and faster oddball detection were all positively associated with LC MRI contrast from a neuromelanin-sensitive structural scan. Thus, LC structural integrity was related to LC functional dynamics and attentional performance during the oddball task. We also found that handgrip led to larger phasic pupil responses to oddball sounds, faster oddball detection speed, and greater frontoparietal network activation, suggesting that something that induces strong LC activity benefits attentional performance for at least the next few minutes. In addition, older women showed a similar benefit of handgrip on frontoparietal network activation as younger women, despite showing lower frontoparietal network activation overall. Together these findings suggest that a simple exercise may improve selective attention in healthy aging, at least for several minutes afterwards.HighlightsWe examined how handgrip affects arousal-attention dynamics during an oddball taskSalient stimuli enhanced pupil dilation and were detected faster post-handgripA decrease in tonic pupil size after handgrip suggests norepinephrine depletionMRI-assessed LC integrity was related to oddball detection and pupil dilationLC integrity also associated with LC-frontoparietal network functional connectivity
The molecular anatomy of mouse skin during hair growth and rest
Authors: Joost Simon , Annusver Karl , Jacob Tina , Sun Xiaoyan , Sivan Unnikrishnan , Dalessandri Tim , Sequeira Inês , Sandberg Rickard , Kasper Maria 
Published: August 2019

SUMMARYSkin homeostasis is orchestrated by dozens of cell types that together direct stem cell renewal, lineage commitment and differentiation. However, a systematic molecular atlas of full-thickness skin is lacking. Here, we used single-cell RNA-sequencing and mRNA-FISH to determine gene-expression identity and spatial location of skin cells during hair growth and rest. We defined 55 cell populations and made striking discoveries about the outer root sheath (ORS) and inner hair follicle layers that together coordinate hair production. The ORS is composed of two distinct cell types, companion layer cells resemble ORS and not inner layer cells, and we identified an asymmetric inner-layer structure with ORS cell identity. Moreover, the inner layers branch from transcriptionally uncommitted progenitors, and each lineage differentiation passes through an intermediate state. Altogether, we generated a comprehensive atlas with molecular and spatial information on epithelial and stromal cells, including fibroblasts, vascular and immune cells, that will spur new discoveries in skin biology.HIGHLIGHTS-Comprehensive single-cell transcriptome atlas of full-thickness skin-Outer root sheath (ORS) is composed of two distinct cell types-Companion layer transcriptionally resembles ORS-Transcriptional reconstruction of the internal hair follicle (HF) lineages-Molecular identification of an asymmetric HF-bulb structure-Spatial map of fibroblast subtypes in the skin-Online tool.http://kasperlab.org/tools
A deep neural network approach to predicting clinical outcomes of neuroblastoma patients
Authors: Tranchevent Léon-Charles , Azuaje Francisco , Rajapakse Jagath C. 
Published: August 2019

AbstractThe availability of high-throughput omics datasets from large patient cohorts has allowed the development of methods that aim at predicting patient clinical outcomes, such as survival and disease recurrence. Such methods are also important to better understand the biological mechanisms underlying disease etiology and development, as well as treatment responses. Recently, different predictive models, relying on distinct algorithms (including Support Vector Machines and Random Forests) have been investigated. In this context, deep learning strategies are of special interest due to their demonstrated superior performance over a wide range of problems and datasets. One of the main challenges of such strategies is the “small n large p” problem. Indeed, omics datasets typically consist of small numbers of samples and large numbers of features relative to typical deep learning datasets. Neural networks usually tackle this problem through feature selection or by including additional constraints during the learning process.We propose to tackle this problem with a novel strategy that relies on a graph-based method for feature extraction, coupled with a deep neural network for clinical outcome prediction. The omics data are first represented as graphs whose nodes represent patients, and edges represent correlations between the patients’ omics profiles. Topological features, such as centralities, are then extracted from these graphs for every node. Lastly, these features are used as input to train and test various classifiers.We apply this strategy to four neuroblastoma datasets and observe that models based on neural networks are more accurate than state of the art models (DNN: 85%-87%, SVM/RF: 75%-82%). We explore how different parameters and configurations are selected in order to overcome the effects of the small data problem as well as the curse of dimensionality. Our results indicate that the deep neural networks capture complex features in the data that help predicting patient clinical outcomes.
Assessing the potential of environmental DNA metabarcoding for monitoring Neotropical mammals: a case study in the Amazon and Atlantic Forest, Brazil
Authors: Sales Naiara Guimarães , da Cruz Kaizer Mariane , Coscia Ilaria , Perkins Joseph C. , Highlands Andrew , Boubli Jean P. , Magnusson William E. , da Silva Maria Nazareth Ferreira , Benvenuto Chiara , McDevitt Allan D. 
Published: August 2019

AbstractThe application of environmental DNA (eDNA) metabarcoding as a biomonitoring tool has greatly increased in the last decade. However, most studies have focused on aquatic macro-organisms in temperate areas (e.g., fishes). We apply eDNA metabarcoding to detect the mammalian community in two high-biodiversity regions of Brazil, the Amazon and Atlantic Forest. We identified critically endangered and endangered mammalian species in the Atlantic Forest and Amazon respectively and found congruence with species identified via camera trapping in the Atlantic Forest. In light of our results, we highlight the potential and challenges of eDNA monitoring for mammals in these high biodiverse areas.
Catastrophes, connectivity, and Allee effects in the design of marine reserve networks
Authors: White Easton R. , Baskett Marissa L. , Hastings Alan 
Published: August 2019

AbstractCatastrophic events, like oil spills and hurricanes, occur in many marine systems. One potential role of marine reserves is buffering populations against disturbances, including the potential for disturbance-driven population collapses under Allee effects. This buffering capacity depends on reserves in a network providing rescue effects, with a potential trade-off in spacing between individual reserves to balance rescue via connectivity and independence of disturbances experienced. We use a set of population models to examine how dispersal ability and the disturbance regime interact to determine the optimal reserve spacing. We incorporate fishing in a spatially-explicit model to understand the consequences of objective choice (i.e. conservation versus fisheries yield) on the optimal reserve spacing. We show that the optimal spacing between reserves increases when accounting for catastrophes. This result is accentuated when Allee effects interact with catastrophes to increase the probability of extinction. We also show that classic tradeoffs between conservation and fishing objectives disappear in the presence of catastrophes. Specifically, we found that at intermediate levels of disturbance, it is optimal to spread out reserves in order to increase population persistence and to maximize spillover into non-reserve areas.
Mix & Match: Phenotypic coexistence as a key facilitator of solid tumour invasion
Authors: Strobl Maximilian A. R. , Krause Andrew L. , Damaghi Mehdi , Gillies Robert , Anderson Alexander R. A. , Maini Philip K. 
Published: August 2019

AbstractInvasion of healthy tissue is a defining feature of malignant tumours. Traditionally, invasion is thought to be driven by cells that have acquired all the necessary traits to overcome the range of biological and physical defences employed by the body. However, in light of the ever-increasing evidence for geno- and phenotypic intra-tumour heterogeneity an alternative hypothesis presents itself: Could invasion be driven by a collection of cells with distinct traits that together facilitate the invasion process? In this paper, we use a mathematical model to assess the feasibility of this hypothesis in the context of acid-mediated invasion. We assume tumour expansion is obstructed by stroma which inhibits growth, and extra-cellular matrix (ECM) which blocks cancer cell movement. Further, we assume that there are two types of cancer cells: i) a glycolytic phenotype which produces acid that kills stromal cells, and ii) a matrix-degrading phenotype that locally remodels the ECM. We extend the Gatenby-Gawlinski reaction-diffusion model to derive a system of five coupled reaction-diffusion equations to describe the resulting invasion process. We characterise the spatially homogeneous steady states and carry out a simulation study in one spatial dimension to determine how the tumour develops as we vary the strength of competition between the two phenotypes. We find that overall tumour growth is most extensive when both cell types can stably coexist, since this allows the cells to locally mix and benefit most from the combination of traits. In contrast, when inter-species competition exceeds intra-species competition the populations spatially separate and invasion arrests either: i) rapidly (matrix-degraders dominate), or ii) slowly (acid-producers dominate). Overall, our work demonstrates that the spatial and ecological relationship between a heterogeneous population of tumour cells is a key factor in determining their ability to cooperate. Specifically, we predict that tumours in which different phenotypes coexist stably are more invasive than tumours in which phenotypes are spatially separated.
Topological Data Analysis reveals robust alterations in the whole-brain and frontal lobe functional connectomes in Attention-Deficit/Hyperactivity Disorder
Authors: Gracia-Tabuenca Zeus , Díaz-Patiño Juan Carlos , Arelio Isaac , Alcauter Sarael 
Published: August 2019

AbstractThe functional organization of the brain network (connectome) has been widely studied as a graph; however, methodological issues may affect the results, such as the brain parcellation scheme or the selection of a proper threshold value. Instead of exploring the brain in terms of a static connectivity threshold, this work explores its algebraic topology as a function of the filtration value (i.e., the connectivity threshold), a process termed the Rips filtration in Topological Data Analysis. Specifically, we characterized the transition from all nodes being isolated to being connected into a single component as a function of the filtration value, in a public dataset of children with attention-deficit/hyperactivity disorder (ADHD) and typically developing children. Results were highly congruent when using four different brain segmentations (atlases), and exhibited significant differences for the brain topology of children with ADHD, both at the whole brain network and at the functional sub-network levels, particularly involving the frontal lobe and the default mode network. Therefore, this approach may contribute to identify the neurophysio-pathology of ADHD, reducing the bias of connectomics-related methods.HighlightsTopological Data Analysis was implemented in functional connectomes.Betti curves were assessed based on the area under the curve, slope and kurtosis.The explored variables were robust along four different brain atlases.ADHD showed lower areas, suggesting decreased functional segregation.Frontal and default mode networks showed the greatest differences between groups.Graphical Abstract
Laocoön: a tool for high-throughput automated cell counting
Authors: Lim Kaitlin , Louie Mikaela , La Torre Anne , Fairchild Corinne , Korf Ian 
Published: August 2019

STRUCTURED ABSTRACTMotivationThere are current programs and plugins that automatically count the number of cells in a given image. However, many of these processes are not entirely automatic, as they require user input to specify a region of interest and are also frequently inaccurate.ResultsThis project presents laocoön, a Python package specifically designed to automatically and efficiently count the number of fluorescently-labelled cells in images. This package not only allows for reliable cell counting, but returns the proportion of cells in each cell cycle relative to all the cells in the DAPI channel, which is currently used for research purposes, but could ultimately be utilized for clinical purposes.Availability and ImplementationThis package, its corresponding execution instructions, and further information about the underlying algorithms, are currently available in the GitHub repository https://github.com/edukait/laocoon under the MIT license and can be run on the command terminal of any operating system. Alternatively, laocoön is available in the Python Package Index (PyPi), so the user can use the pip command to immediately download the package.Contactkaitlin.y.lim@gmail.com
Toward standards in clinical microbiome studies: comparison of three DNA extraction methods and two bioinformatic pipelines
Authors: Ducarmon Q.R. , Hornung B.V.H. , Geelen A.R. , Kuijper E.J. , Zwittink R.D. 
Published: August 2019

ABSTRACTWhen studying the microbiome using next generation sequencing, DNA extraction method, sequencing procedures and bioinformatic processing are crucial to obtain reliable data. Method choice has been demonstrated to strongly affect the final biological interpretation. We assessed the performance of three DNA extraction methods and two bioinformatic pipelines for bacterial microbiota profiling through 16S rRNA gene amplicon sequencing, using positive and negative controls for DNA extraction and sequencing, and eight different types of high- or low-biomass samples. Performance was evaluated based on quality control passing, DNA yield, richness, diversity and compositional profiles. All DNA extraction methods retrieved the theoretical relative bacterial abundance with maximum three-fold change, although differences were seen between methods, and library preparation and sequencing induced little variation. Bioinformatic pipelines showed different results for estimating richness, but diversity and compositional profiles were comparable. DNA extraction methods were successful for feces and oral swabs and variation induced by DNA extraction methods was lower than inter-subject (biological) variation. For low-biomass samples, a mixture of genera present in negative controls and sample-specific genera, possibly representing biological signal, were observed. We conclude that the tested bioinformatic pipelines perform equally with pipeline-specific advantages and disadvantages. Two out of three extraction methods performed equally well, while one method was less accurate regarding retrieval of compositional profiles. Lastly, we demonstrate the importance of including negative controls when analyzing low bacterial biomass samples.IMPORTANCEMethod choice throughout the workflow of a microbiome study, from sample collection to DNA extraction and sequencing procedures, can greatly affect results. This study evaluated three different DNA extraction methods and two bioinformatic pipelines by including positive and negative controls, and various biological specimens. By identifying an optimal combination of DNA extraction method and bioinformatic pipeline use, we hope to contribute to increased methodological consistency in microbiome studies. Our methods were not only applied to commonly studied samples for microbiota analysis, e.g. feces, but also for more rarely studied, low-biomass samples. Microbiota composition profiles of low-biomass samples (e.g. urine and tumor biopsies) were not always distinguishable from negative controls, or showed partial overlap, confirming the importance of including negative controls in microbiome studies, especially when low bacterial biomass is expected.
A genome-wide genetic pleiotropy approach identified shared loci between multiple system atrophy and inflammatory bowel disease
Authors: Shadrin Alexey A , Mucha Sören , Ellinghaus David , Makarious Mary B , Blauwendraat Cornelis , Sreelatha Ashwin A , Heras-Garvin Antonio , Ding Jinhui , Hammer Monia , Foubert-Samier Alexandra , Meissner Wassilios G , Rascol Olivier , Traon Anne Pavy-Le , Frei Oleksandr , O’Connell Kevin S , Bahrami Shahram , Schreiber Stefan , Lieb Wolfgang , Müller-Nurasyid Martina , Arnold Andreas , Homuth Georg , Schmidt Carsten O. , Nöthen Markus M. , Hoffmann Per , Gieger Christian ,   European Multiple System Atrophy Study Group, Gibbs J Raphael , Franke Andre , Hardy John , Wenning Gregor , Stefanova Nadia , Gasser Thomas , Singleton Andrew , Houlden Henry , Scholz Sonja W , Andreassen Ole A. , Sharma Manu 
Published: August 2019

ABSTRACTWe aimed to identify shared genetic background between multiple system atrophy (MSA) and autoimmune diseases by using the conjFDR approach. Our study showed significant genetic overlap between MSA and inflammatory bowel disease and identified DENND1B, C7, and RSP04 loci, which are linked to significant changes in methylation or expression levels of adjacent genes. We obtained evidence of enriched heritability involving immune/digestive categories. Finally, an MSA mouse model showed dysregulation of the C7 gene in the degenerating midbrain compared to wildtype mice. The results identify novel molecular mechanisms and implicate immune and gut dysfunction in MSA pathophysiology.
A homozygous hypomorphic BRCA2 variant causes primary ovarian insufficiency without cancer or Fanconi anemia traits
Authors: Caburet Sandrine , Heddar Abdelkader , Dardillac Elodie , Creux Helene , Lambert Marie , Messiaen Sébastien , Tourpin Sophie , Livera Gabriel , Lopez Bernard S. , Misrahi Micheline 
Published: August 2019

ABSTRACTPrimary Ovarian insufficiency (POI) affects 1% of women under forty. We studied a patient with a non-syndromic POI, from a consanguineous Turkish family. Exome sequencing identified a homozygous missense variant c.8524C>T/p.R2842C in BRCA2. BRCA2 is a major player in homologous recombination (HR). BRCA2 deficiency induces cancer predisposition and Fanconi Anemia (FA). Remarkably, neither the patient nor her family exhibit somatic pathologies. The patient’s somatic cells presented intermediate levels of chromosomal breaks, cell proliferation and radiation-induced RAD51 foci formation when compared to controls, the heterozygous mother’s and FA cells. R2842C-BRCA2 partially complemented BRCA2 depletion for double-strand break-induced HR. The residual HR function in patient’s cells could explain the absence of somatic pathology. BRCA2 is expressed in human fetal ovaries in pachytene stage oocytes, when meiotic HR occurs. This study has a major impact on the understanding of genome maintenance in somatic and meiotic cells and on the management of POI patients.