bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of live breast cancer cells in brightfield microscopy images containing white blood cells by image analysis and deep learning
Authors: Moallem Golnaz , Pore Adity A. , Gangadhar Anirudh , Sari-Sarraf Hamed , Vanapalli Siva A. 
Published: November 2021

AbstractSignificanceCirculating tumor cells (CTCs) are important biomarkers for cancer management. Isolated CTCs from blood are stained to detect and enumerate CTCs. However, the staining process is laborious and moreover makes CTCs unsuitable for drug testing and molecular characterization.AimThe goal is to develop and test deep learning (DL) approaches to detect unstained breast cancer cells in bright field microscopy images that contain white blood cells (WBCs).ApproachWe tested two convolutional neural network (CNN) approaches. The first approach allows investigation of the prominent features extracted by CNN to discriminate cancer cells from WBCs. The second approach is based on Faster Region-based Convolutional Neural Network (Faster R-CNN).ResultsBoth approaches detected cancer cells with high sensitivity and specificity with the Faster R-CNN being more efficient and suitable for deployment. The distinctive feature used by the CNN used to discriminate is cell size, however in the absence of size difference, the CNN was found to be capable of learning other features. The Faster R-CNN was found to be robust with respect to intensity and contrast image transformations.ConclusionsCNN-based deep learning approaches could be potentially applied to detect patient-derived CTCs from images of blood samples.
Simultaneous identification of viruses and viral variants with programmable DNA nanobait
Authors: Bošković Filip , Zhu Jinbo , Tivony Ran , Ohmann Alexander , Chen Kaikai , Alawami Mohammed F. , Đorđević Milan , Ermann Niklas , Dias Joana Pereira , Fairhead Michael , Howarth Mark , Baker Stephen , Keyser Ulrich F. 
Published: November 2021

AbstractRespiratory infections are the major cause of death from infectious disease worldwide. Multiplexed diagnostic approaches are essential as many respiratory viruses have indistinguishable symptoms. We created self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid read-out via nanopore sensing. Here, we show this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from multiple viruses. Our nanobait can be easily reprogrammed to discriminate viral variants, as we demonstrated for several key SARS-CoV-2 variants with single-nucleotide resolution. Lastly, we show that nanobait discriminates between samples extracted from oropharyngeal swabs from negative and positive SARS-CoV-2 patients without pre-amplification. Our system allows for multiplexed identification of native RNA molecules, providing a new scalable approach for diagnostics of multiple respiratory viruses in a single assay.
ColocQuiaL: A QTL-GWAS colocalization pipeline
Authors: Chen Brian Y. , Bone William P. , Lorenz Kimberly , Levin Michael , Ritchie Marylyn D. , Voight Benjamin F. 
Published: November 2021

AbstractSummaryIdentifying genomic features responsible for genome-wide association study (GWAS) signals has proven to be a difficult challenge; many researchers have turned to colocalization analysis of GWAS signals with expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) to connect GWAS signals to candidate causal genes. The ColocQuiaL pipeline provides a framework to perform these colocalization analyses at scale across the genome and returns summary files and locus visualization plots to allow for detailed review of the results. As an example, we used ColocQuiaL to perform colocalization between the latest type 2 diabetes GWAS data and Genotype-Tissue Expression (GTEx) v8 single-tissue eQTL and sQTL data.Availability and ImplementationColocQuiaL is primarily written in R and is freely available at github: https://github.com/bychen9/eQTL_colocalizer.Contactbvoight@pennmedicine.upenn.edu
Cohort Profile: Genetic data in the German Socio-Economic Panel Innovation Sample (Gene-SOEP)
Authors: Koellinger Philipp D. , Okbay Aysu , Kweon Hyeokmoon , Schweinert Annemarie , Karlsson Linnér Richard , Goebel Jan , Richter David , Reiber Lisa , Zweck Bettina Maria , Belsky Daniel W. , Biroli Pietro , Mata Rui , Tucker-Drob Elliot M. , Harden K. Paige , Wagner Gert , Hertwig Ralph 
Published: November 2021

AbstractThe German Socio-Economic Panel (SOEP) serves a global research community by providing representative annual longitudinal data of private households in Germany. The sample provides a detailed life course perspective based on a rich collection of information about living conditions, socio-economic status, family relationships, personality, values, preferences, and health. We collected genetic data from 2,598 individuals in the SOEP Innovation Sample, yielding the first genotyped sample that is representative of the entire German population (Gene-SOEP). The Gene-SOEP sample is a longitudinal study that includes 107 full-sibling pairs, 501 parent-offspring pairs, and 152 parent-offspring trios that are overlapping with the parent-offspring pairs. We constructed a repository of 66 polygenic indices in the Gene-SOEP sample based on results from well-powered genome-wide association studies. The Gene-SOEP data provides a valuable resource to study individual differences, inequalities, life-course development, health, and interactions between genetic predispositions and environment.
How and why do Quality Circles work for General Practitioners - a realist approach
Authors: Rohrbasser Adrian , Wong Geoff , Mickan Sharon , Harris Janet 
Published: November 2021

AbstractObjectivesTo understand how and why general practitioners in quality circles (QC) reflect on and improve routine practice over time. To provide practical guidance for participants and facilitators to implement and for policy makers to organise this complex social intervention.DesignA theory-driven mixed methodSettingPrimary health careMethodWe collected data in four stages to develop and refine the programme theory of QCs: 1) co-inquiry with Swiss and European stakeholders to develop a preliminary programme theory; 2) realist review with systematic searches in MEDLINE, Embase, PsycINFO, and CINHAL (1980-2020) to extend the preliminary programme theory; 3) programme refinement through interviews with participants, facilitators, tutors and managers of quality circles; 4) consolidation through interviews and iterative searches for theories enabling us to strengthen the programme theory.Sources of dataThe co-inquiry comprised 3 interviews and 3 focus groups with 50 European experts. From the literature search we included 108 papers to develop the literature-based programme theory. In stage 3, we used data from 40 participants gathered in 6 interviews and 2 focus groups to refine the programme theory. In stage 4, five interviewees from different health care systems consolidated our programme theory.ResultRequirements for successful QCs are governmental trust in GPs’ abilities to deliver quality improvement, training, access to educational material and performance data, protected time, and financial resources. Group dynamics strongly influence success; facilitators should ensure participants exchange knowledge and generate new concepts in a safe environment. Peer interaction promotes professional development and psychological well-being. With repetition, participants gain confidence to put their new concepts into practice.ConclusionQCs can improve practice, promote professional development, and psychological well-being given adequate professional and administrative support.Strengths and limitations of this studyTo our knowledge, this is the first published research that explains how and why general practitioners participating in quality circles may improve standard practice and their psychological well-being over time.The findings can be used to inform practice and policy decisions.The resulting theory relies on the detail and depth of the reports in the literature and the veracity and adequacy of the information participants revealed in interviews and focus groups.To mitigate the risk of selection bias if researchers choose underlying theories and synthesise them ad hoc, we used stakeholders’ mental model and programme documentation as our framework for analysis.
Calcium and strontium contractile activation properties of single skinned skeletal muscle fibres from elderly women 66-90 years of age
Authors: Ronaldson Susan M. , Stephenson D. George , Head Stewart I. 
Published: November 2021

ABSTRACTThe single skinned muscle fibre technique was used to investigate Ca2+- and Sr2+- activation properties of skeletal muscle fibres from elderly women (66-90 years). Muscle biopsies were obtained from the vastus lateralis muscle. Three populations of muscle fibres were identified according to their specific Sr2+- activation properties: slow-twitch (type I), fast-twitch (type II) and hybrid (type I/II) fibres. All three fibre types were sampled from the biopsies of 66 to 72 years old women, but the muscle biopsies of women older than 80 years yielded only slow-twitch (type I) fibres. The proportion of hybrid fibres in the vastus lateralis muscle of women of circa 70 years of age (24%) was several-fold greater than in the same muscle of adults (<10%), suggesting that muscle remodelling occurs around this age. There were no differences between the Ca2+- and Sr2+- activation properties of slow-twitch fibres from the two groups of elderly women, but there were differences compared with muscle fibres from adults with respect to sensitivity to Ca2+, steepness of the activation curves, and characteristics of the fibre-type dependent phenomenon of spontaneous force oscillations (SOMO) occurring at submaximal levels of activation. The maximal Ca2+ activated specific force from all the fibres collected from the seven old women use in the present study was significantly lower by 20% than in the same muscle of adults. Taken together these results show there are qualitative and quantitative changes in the activation properties of the contractile apparatus of muscle fibres from the vastus lateralis muscle of women with advancing age, and that these changes need to be considered when explaining observed changes in women’s mobility with aging.
The Open Perimetry Initiative: a framework for cross-platform development for the new generation of portable perimeters
Authors: Marín-Franch Iván , Turpin Andrew , Artes Paul H , Chong Luke X , McKendrick Allison M , Alawa Karam A , Wall Michael 
Published: November 2021

AbstractThe Open Perimetry Initiative is fully open source and consists of the Open Perimetry Interface (OPI) and an accompanying package (visualFields) with analytical tools. The OPI package contains an ever-growing number of drivers for commercially available perimeters, head-mounted devices, and virtual reality headsets. The visualFields package contains tools for the analysis and visualization of visual field data, including methods to compute deviation values and probability maps. The use of the OPI and visualFields is shown through a custom static automated perimetry test for the full visual field (up to 50° nasally and 80° temporally) developed with the OPI driver for the Octopus 900 and using visualFields for statistical analysis. Its potential for the development of cross-platform apps for driving and testing portable devices is demonstrated with an OPI driver for an Android-based headset. With more than 55 citations in clinical and translational science as listed in Scopus, this initiative has contributed significantly to expanding the knowledge base in perimetry and clinical vision research at large, and with clinical translation. The continued support of researchers, clinicians, industry, and public institutions are key in transforming perimetry research from closed to open science. The Open Perimetry Initiative provides framework to achieve this.
CX3CL1 action on microglia protects from diet-induced obesity by restoring POMC neuronal excitability and melanocortin system activity impaired by high-fat diet feeding
Authors: Banerjee Jineta , Dorfman Mauricio D. , Fasnacht Rachael , Douglass John D. , Wyse-Jackson Alice C. , Barria Andres , Thaler Joshua P. 
Published: November 2021

AbstractObjectiveDiet-induced obesity (DIO) is associated with hypothalamic microglial activation and dysfunction of the melanocortin pathway, but the molecular mechanisms linking the two remain unclear. Previous studies have hypothesized that microglial inflammatory signaling is linked with impaired pro-opiomelanocortin (POMC) neuron function, but this mechanism has never been directly tested in vivo. We addressed this hypothesis using the specific microglial silencing molecule, CX3CL1 (fractalkine), to determine whether reducing hypothalamic microglial activation can restore POMC/melanocortin signaling in the brain to protect against DIO.MethodsWe performed metabolic analyses in mice with targeted viral overexpression of CX3CL1 in the hypothalamus exposed to high fat diet (HFD). Electrophysiologic recording in hypothalamic slices from POMC-MAPT-GFP mice was used to determine the effects of HFD feeding and microglial silencing via minocycline or CX3CL1 on GFP-labeled POMC neurons. Finally, mice with hypothalamic overexpression of CX3CL1 received central treatment with the melanocortin receptor antagonist SHU-9119 to determine whether melanocortin signaling is required for the metabolic benefits of CX3CL1.ResultsWe found that targeted expression of both soluble and membrane-bound forms of CX3CL1 in the mediobasal hypothalamus potently reduced weight gain and increased leptin sensitivity in animals exposed to high fat diet. The protective effect of CX3CL1 rescued diet-induced changes in POMC neuron excitability and required intact melanocortin receptor signaling in vivo.ConclusionOur results provide the first evidence that HFD-induced POMC neuron dysfunction involves microglial activation. Furthermore, our study suggests that the anti-obesity action of CX3CL1 is mediated through the restoration of POMC neuron excitability and melanocortin signaling.
WATLAS: high throughput and real-time tracking of many small birds in the Dutch Wadden Sea
Authors: Bijleveld Allert I. , van Maarseveen Frank , Denissen Bas , Dekinga Anne , Penning Emma , Ersoy Selin , Gupte Pratik , de Monte Luc , Horn Job ten , Bom Roeland A. , Toledo Sivan , Nathan Ran , Beardsworth Christine E. 
Published: November 2021

AbstractBackgroundTracking animal movement is important for understanding how animals interact with their (changing) environment, and crucial for predicting and explaining how animals are affected by anthropogenic effects. The Wadden Sea is a UNESCO World Heritage Site and a region of global importance for millions of small shorebirds. Due to climate change and anthropogenic activity, understanding and predicting movement and space-use in areas like the Wadden Sea is increasingly important. Monitoring and predicting animal movement, however, requires high-resolution tracking of many individuals. While high-resolution tracking has been made possible through GPS, trade-offs between tag weight and battery life limit its use to larger species.MethodsHere, we introduce WATLAS (the Wadden Sea deployment of the ATLAS tracking system) capable of monitoring the movements of hundreds of (small) birds simultaneously in the Dutch Wadden Sea. WATLAS employs an array of receiver stations that can detect and localise small, low-cost tags at fine spatial (meters) and temporal resolution (seconds). From 2017-2021, we tracked red knots, sanderlings, bar-tailed godwits, and common terns. We use parts of these data to give four examples on its performance and how WATLAS can be used to study numerous aspects of animal behaviour, such as, space-use (both intra- and inter-specific), among-individual variation, and social networks.ResultsAfter describing the WATLAS system, we first illustrate space-use of red knots across the study area and how the tidal environment affects their movement. Secondly, we show large among-individual differences in distances travelled per day, and thirdly illustrate how high-throughput WATLAS data allows calculating a proximity-based social network. Finally, we demonstrate that using WATLAS to monitor multiple species can reveal differential space use. For example, despite sanderlings and red knots roosting together, they foraged in different areas of the mudflats.ConclusionsThe high-resolution tracking data collected by WATLAS offers many possibilities for research into the drivers of bird movement in the Wadden Sea. WATLAS could provide a tool for impact assessment, and thus aid nature conservation and management of the globally important Wadden Sea ecosystem.
ICOR: Improving codon optimization with recurrent neural networks
Authors: Jain Rishab , Jain Aditya , Mauro Elizabeth , LeShane Kevin , Densmore Douglas 
Published: November 2021

AbstractBackgroundIn protein sequences—as there are 61 sense codons but only 20 standard amino acids— most amino acids are encoded by more than one codon. Although such synonymous codons do not alter the encoded amino acid sequence, their selection can dramatically affect the expression of the resulting protein. Codon optimization of synthetic DNA sequences is important for heterologous expression. However, existing solutions are primarily based on choosing high-frequency codons only, neglecting the important effects of rare codons. In this paper, we propose a novel recurrent-neural-network based codon optimization tool, ICOR, that aims to learn codon usage bias on a genomic dataset ofEscherichia coli. We compile a dataset of over 7,000 non-redundant, high-expression, robust genes which are used for deep learning. The model uses a bidirectional long short-term memory-based architecture, allowing for the sequential context of codon usage in genes to be learned. Our tool can predict synonymous codons for synthetic genes toward optimal expression inEscherichia coli.ResultsWe demonstrate that sequential context achieved via RNN may yield codon selection that is more similar to the host genome. Based on computational metrics that predict protein expression, ICOR theoretically optimizes protein expression more than frequency-based approaches. ICOR is evaluated on 1,481Escherichia coligenes as well as a benchmark set of 40 select DNA sequences whose heterologous expression has been previously characterized. ICOR’s performance is measured across five metrics: the Codon Adaptation Index, GC-content, negative repeat elements, negative cis-regulatory elements, and codon frequency distribution.ConclusionsThe results, based on in silico metrics, indicate that ICOR codon optimization is theoretically more effective in enhancing recombinant expression of proteins over other established codon optimization techniques. Our tool is provided as an open-source software package that includes the benchmark set of sequences used in this study.
Two different adaptive speciation mechanisms operate during adaptation to a novel hot environment
Authors: Hsu Sheng-Kai , Lai Wei-Yun , Novak Johannes , Lehner Felix , Jakšić Ana Marija , Versace Elisabetta , Schlötterer Christian 
Published: November 2021

AbstractBackgroundEcological speciation and mutation-order speciation are two different mechanisms of adaptation-driven speciation. Both mechanisms predict different patterns of reproductive isolation for replicate populations adapting to the same environment. With ecological speciation, barriers to gene flow emerge between populations from different environments, but not among replicate populations from the same environment. Mutation-order speciation predicts reproductive isolation among populations adapted to the same environment.ResultsWe demonstrate that both speciation processes occurred within about 100 generations when replicateDrosophila simulanspopulations adapted to a novel, hot environment. Gene expression analysis identified the underlying molecular mechanisms. Premating ecological speciation is the byproduct of an altered lipid metabolism, which also changed the cuticular hydrocarbon (CHC) composition in hot-evolved flies. Postmating reproductive isolation supports mutation-order speciation most likely driven by co-evolution of reproduction-associated genes.ConclusionAdaptation processes can rapidly induce incipient speciation and different speciation mechanisms affect pre- and postmating reproductive isolation. We propose that the definition of mutation-order speciation should be expanded to account for polygenic processes from standing genetic variation.
TreeSearch: morphological phylogenetic analysis in R
Authors: Smith Martin R. 
Published: November 2021

AbstractTreeSearch is an R package for phylogenetic analysis, optimized for morphological datasets. Tree search may be conducted using equal or implied step weights with an explicit (albeit inexact) allowance for inapplicable character entries, avoiding some of the pitfalls inherent in standard parsimony methods. Profile parsimony and user-specified optimality criteria are supported.A graphical interface, which requires no familiarity with R, is designed to help a user to improve the quality of datasets through critical review of underpinning character codings; and to obtain additional information from results by identifying and summarizing clusters of similar trees, mapping the distribution of trees, and removing ‘rogue’ taxa that obscure underlying relationships.Taken together, the package aims to support methodological rigour at each step of data collection, analysis, and the exploration of phylogenetic results.
scGate: marker-based purification of cell types from heterogeneous single-cell RNA-seq datasets
Authors: Andreatta Massimo , Berenstein Ariel J. , Carmona Santiago J. 
Published: November 2021

AbstractA common bioinformatics task in single-cell data analysis is to purify a cell type or cell population of interest from heterogeneous datasets. Here we present scGate, an algorithm that automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. scGate purifies a cell population of interest using a set of markers organized in a hierarchical structure, akin to gating strategies employed in flow cytometry. In our benchmark for blood-derived and tumor-infiltrating immune cells, scGate outperforms SingleR, a state-of-the-art classifier for single-cell data. scGate is implemented as an R package and integrated with the Seurat framework, providing an intuitive tool to isolate cell populations of interest from complex scRNA-seq datasets.AvailabilityR package source code and reproducible tutorials are available at https://github.com/carmonalab/scGate