bluuebunny/crossref_metadata_2025_split huggingface dataset:
Not seeing the forest for the trees: a systematic review of comprehensive distress management programs and implementation strategies
Authors: McCarter Kristen , Fradgley Elizabeth A. , Britton Ben , Tait Jordan , Paul Christine 
Published: July 2020

Purpose of review
Clinically significant distress is common in patients with cancer and if untreated can be associated with adverse outcomes. This article offers a review of current approaches to implementing and reporting the minimum components of distress screening and management interventions in cancer services.

Recent findings
Twenty-two relevant published articles were identified from January 2018 to February 2020. The reporting of recommended minimum components of distress screening and management interventions in these articles was not consistent. The majority of studies used validated tools to conduct initial screening. However, recommendations were either not reported or not followed regarding subsequent pathway components, secondary assessment, referral pathways linked to screening results and rescreening. The majority of studies did not include a description of the implementation of the distress screening program. A small number of studies described a comprehensive set of implementation strategies.

Summary
Distress screening and management interventions in cancer are an important component of comprehensive cancer care. To improve patient outcomes and guide researchers and services to identify effective models, studies must include and evaluate minimum recommended components and implementation strategies. Addressing these limitations with high-quality, robust interventions is vital for advancing the implementation of effective distress management.
Maternal blood lipidomics analyses link critical metabolic pathways associated with severe preeclampsia
Authors: Liu Yu , He Bing , Maurya Mano R , Benny Paula , Lassiter Cameron , Li Hui , Subraminiam Shankar , Garmire Lana X. 
Published: July 2020

ABSTRACTPreeclampsia is a pregnancy specific syndrome characterized by hypertension and proteinuria after 20 weeks of gestation. To reveal the relationship between lipids and preeclampsia, we conduct lipidomic profiling of maternal serums of 44 severe preeclamptic and 20 healthy pregnancies from a multi-ethnic cohort in Hawaii. Correlation network analysis shows that oxidized phospholipids (OxPLs) have increased inter-correlations and connections in preeclampsia, while other lipids, including triacylglycerols (TAGs), have reduced network correlations and connections. Thirty-one lipid species from various lipid classes demonstrate predominantly reductions and causal relationships with preeclampsia. They include phosphatidylglycerol (PG), TAG, diacylglycerol (DAG), phosphatidylcholine (PC), cholesterol esters (CE), phosphatidylethanolamine (PE), sphingomyelin (SM), ceramides (Cer-NS), hexosyl ceramides (HexCer-NS), lysophosphatidylcholine (LPC), lysophosphatidylethanolamine (LPE), and free fatty acid (FFA). Many of these lipids are also selected as important features by a linear discriminant analysis (LDA) classifier with high predictive accuracy (F-1 statistic 0.941 and balanced accuracy 0.88), indicating their potential to serve as biomarkers for severe preeclampsia. Our study supports the hypothesis of a phospholipid (PL) centered, dysregulated lipidomic metabolic atlas. That is, severe preeclampsia may be originated from hypoxia, which induces the accumulation of OxPLs through oxidative stress whereas reduces many other lipids (eg. reduced PCs, TAGs and ceramides). These molecular changes coherently lead to dysregulated biological functions, such as insulin signaling and inflammation/infections. Moreover, the lipid changes may also be responsible for the comorbidity between preeclampsia and gestational diabetes, a clinically known risk factor for preeclampsia.
Adaptor Template Oligo-Mediated Sequencing (ATOM-Seq): A versatile and ultra-sensitive UMI-based NGS library preparation technology, for use with cfDNA and cfRNA
Authors: Dunwell Thomas L. , Dailey Simon C. , Yu Jihang , Becker Philipp W. , Scaife Sarah , Richman Susan D. , Wood Henry M. , Slaney Hayley , Bottomley Daniel , Yang Xiangsheng , Xiao Hui , Ottestad Anine L. , Wahl Sissel G. F. , Grønberg Bjørn H. , Dai Hong Yan , Fu Guoliang 
Published: July 2020

AbstractLiquid biopsy testing utilising Next Generation Sequencing (NGS) is rapidly moving towards clinical adoption for personalised oncology. However, before NGS can fulfil its potential any novel testing approach must identify ways of reducing errors, allowing for separating true low-frequency mutations from procedural artefacts, and be designed to improve upon current technologies while also avoiding their limitations. Popular NGS technologies typically utilise two approaches; PCR and ligation, which have known limitations and seem to have reached a development plateau with only small, stepwise improvements being made. To maximise the ultimate utility of liquid biopsy testing we have developed a highly versatile approach to NGS: Adaptor Template Oligo Mediated Sequencing (ATOM-Seq). ATOM-Seq’s strengths and versatility avoid the major limitations of both PCR- and ligation-based approaches. This technology is ligation free, simple, efficient, flexible, and streamlined, and offers novel advantages that make it perfectly suited for use on highly challenging clinical material. Using reference materials, we demonstrate detection of known SNVs at allele frequencies of 0.1% using as little as 20 ng of DNA, as well as the ability to detect fusions from RNA. We illustrate ATOM-Seq’s suitability for clinical testing by showing high concordance rates between paired cfDNA and FFPE clinical samples.
DNMT3A haploinsufficiency results in behavioral deficits and global epigenomic dysregulation shared across neurodevelopmental disorders
Authors: Christian Diana L. , Wu Dennis Y. , Martin Jenna R. , Moore J. Russell , Liu Yiran R. , Clemens Adam W. , Nettles Sabin A. , Kirkland Nicole M. , Hill Cheryl A. , Wozniak David F. , Dougherty Joseph D. , Gabel Harrison W. 
Published: July 2020

SummaryMutations in DNA methyltransferase 3A (DNMT3A) have been detected in autism and related disorders, but how these mutations disrupt nervous system function is unknown. Here we define the effects of neurodevelopmental disease-associated DNMT3A mutations. We show that diverse mutations affect different aspects of protein activity yet lead to shared deficiencies in neuronal DNA methylation. Heterozygous DNMT3A knockout mice mimicking DNMT3A disruption in disease display growth and behavioral alterations consistent with human phenotypes. Strikingly, in these mice we detect global disruption of neuron-enriched non-CG DNA methylation, a binding site for the Rett syndrome protein MeCP2. Loss of this methylation leads to enhancer and gene dysregulation that overlaps with models of Rett syndrome and autism. These findings define effects of DNMT3A haploinsufficiency in the brain and uncover disruption of the non-CG methylation pathway as a convergence point across neurodevelopmental disorders.
Geography is more important than life history in the recent diversification of the tiger salamander complex
Authors: Everson Kathryn M. , Gray Levi N. , Jones Angela G. , Lawrence Nicolette M. , Foley Mary E. , Sovacool Kelly L. , Kratovil Justin D. , Hotaling Scott , Hime Paul M. , Storfer Andrew , Parra-Olea Gabriela , Percino-Daniel Ruth , Aguilar-Miguel X. , O’Neill Eric M. , Zambrano Luis , Shaffer H. Bradley , Weisrock David W. 
Published: July 2020

AbstractThe North American tiger salamander species complex, including its best-known species, the Mexican axolotl, has long been a source of biological fascination. The complex exhibits a wide range of variation in developmental life history strategies, including populations and individuals that undergo metamorphosis, those able to forego metamorphosis and retain a larval, aquatic lifestyle (i.e., paedomorphosis), and those that do both. This life history variation has been assumed to lead to reproductive isolation and speciation, but the degree to which it has shaped population- and species-level divergence is poorly understood. Using a large multi-locus dataset from hundreds of samples across North America, we identified genetic clusters across the geographic range of the tiger salamander complex. These clusters often contain a mixture of paedomorphic and metamorphic taxa, indicating that geographic isolation has played a larger role in lineage divergence than paedomorphosis in this system. This conclusion is bolstered by geography-informed analyses indicating no effect of life history strategy on population genetic differentiation and by model-based analyses demonstrating gene flow between adjacent metamorphic and paedomorphic populations. This fine-scale genetic perspective on life-history variation establishes a framework for understanding how plasticity, local adaptation, and gene flow contribute to lineage divergence. Many members of the tiger salamander complex are endangered, and the Mexican axolotl is an important model system in regenerative and biomedical research. Our results chart a course for more informed use of these taxa in experimental, ecological, and conservation research.SignificanceStatementPopulation structure and speciation are shaped by a combination of biotic and abiotic factors. The tiger salamander complex has been considered to be a key group where life history variation has led to a rapid rate of speciation, driven in large part by the evolution of obligate paedomorphosis–a condition where adults maintain an aquatic, larval phenotype. Using a large multi-locus dataset, we present evidence of gene flow between taxa with different life history strategies, suggesting that obligate paedomorphosis is not a strong driver of speciation in the tiger salamander complex. Many of these nominal taxa are listed as critically endangered, and our genetic results provide information and guidance that will be useful for their conservation.
SITH: an R package for visualizing and analyzing a spatial model of intratumor heterogeneity
Authors: Nicol Phillip B. , Barabási Dániel L. , Asiaee Amir , Coombes Kevin R. 
Published: July 2020

AbstractMotivationCancer progression, including the development of intratumor heterogeneity, is inherently a spatial process. Mathematical models of tumor evolution can provide insights into patterns of heterogeneity that can emerge in the presence of spatial growth.SummaryWe develop SITH, an R package that implements a lattice-based stochastic model of tumor growth and mutation. SITH provides 3D interactive visualizations of the simulated tumor and highlights heavily mutated regions. SITH can produce synthetic bulk and single-cell sequencing data sets by sampling from the tumor. The streamlined API will make SITH a useful tool for investigating the relationship between spatial growth and intratumor heterogeneity.Availability and ImplementationSITH is a part of CRAN and can thus be installed by runninginstall.packages(“SITH”)from the R console. Seehttps://CRAN.R-project.org/package=SITHfor the user manual and package vignette.
Normalizing single-cell RNA sequencing data with internal spike-in-like genes
Authors: Lin Li , Song Minfang , Jiang Yong , Zhao Xiaojing , Wang Haopeng , Zhang Liye 
Published: July 2020

ABSTRACTNormalization with respect to sequencing depth is a crucial step in single-cell RNA sequencing preprocessing. Most methods normalize data using the whole transcriptome based on the assumption that the majority of transcriptome remains constant and are unable to detect drastic changes of the transcriptome. Here, we develop an algorithm based on a small fraction of constantly expressed genes as internal spike-ins to normalize single cell RNA sequencing data. We demonstrate that the transcriptome of single cells may undergo drastic changes in several case study datasets and accounting for such heterogeneity by ISnorm improves the performance of downstream analyzes.
A novel hypoxia gene signature indicates prognosis and reveals the multi-omics molecular landscape of tumour tissue in patients with hepatocellular carcinoma
Authors: Zhang Qiangnu , Liao Juan , Qiao Lijun , Liu Quan , Liu Pengyu , Xia Mengting , Huang Xiaotao , Liu Liping 
Published: July 2020

AbstractBackgroundPrevious studies on the impact of hypoxia on hepatocellular carcinoma (HCC) mostly focused on in vitro and animal models. The clinical value of assessing the degree of hypoxia in in vivo tissues and hypoxia-related molecular landscapes in HCC remain poorly defined.MethodsA novel hypoxia gene signature was extracted from hypoxia-treated HCC cells using microarray analysis and a robust rank aggregation algorithm and was verified using public data. Next, the relationships between the hypoxia gene signature and the clinical characteristics and prognoses of HCC patients were analysed. Based on the multi-omics data from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) and 10 independent HCC cohorts from the Gene Expression Omnibus (GEO), a comprehensive analysis was conducted using the hypoxia gene signature to describe hypoxia-associated multi-omic molecular landscapes and immune microenvironments in HCC tissues.ResultsA 21-gene hypoxia signature was constructed to effectively indicate the exposure of hypoxia in HCC tissues. This novel hypoxia signature and the hypoxia scores calculated based on this signature were closely correlated to some clinical characteristics of HCC patients and can be used to evaluate prognosis. HCC tissues with different hypoxia scores differed significantly in transcriptomic, genomic, epigenomic, and proteomic alterations and immune microenvironments, some of which were related to the clinical prognoses of patients.ConclusionThe 21-gene signature can effectively estimate hypoxia exposure of HCC tissues and has clinical value in the assessment and prediction of the prognosis of HCC patients. Using this 21-gene signature, hypoxia-associated molecular landscapes were described at the tissue level. This comprehensive molecular-level understanding can help to further elucidate the mechanism of hypoxia in tumours and guide clinical cancer therapy. The assessment of the degree of hypoxia is strongly recommended in the personalized treatment of HCC patients to benefit specific patient groups.
Collateral Sensitivity Associated with Antibiotic Resistance Plasmids
Authors: Herencias Cristina , Rodríguez-Beltrán Jerónimo , León-Sampedro Ricardo , Alonso-del Valle Aida , Palkovičová Jana , Cantón Rafael , Millán Álvaro San 
Published: July 2020

AbstractCollateral sensitivity (CS) is a promising alternative approach to counteract the rising problem of antibiotic resistance (ABR). CS occurs when the acquisition of resistance to one antibiotic produces increased susceptibility to a second antibiotic. For CS to be widely applicable in clinical practice, it would need to be effective against the different resistance mechanisms available to bacteria. Recent studies have focused on CS strategies designed against ABR mediated by chromosomal mutations. However, one of the main drivers of ABR in clinically relevant bacteria is the horizontal transfer of ABR genes mediated by plasmids. Here, we report the first analysis of CS associated with the acquisition of complete ABR plasmids, including the clinically important carbapenem-resistance conjugative plasmid pOXA-48. In addition, we describe the conservation of CS in clinicalE. coliisolates and its application to the selective elimination of plasmid-carrying bacteria. Our results provide new insights that establish the basis for developing CS-informed treatment strategies to combat plasmid-mediated ABR.
Template switching mechanism drives the tandem amplification of chromosome 20q11.21 in human pluripotent stem cells
Authors: Halliwell Jason A , Baker Duncan , Judge Kim , Quail Michael A , Oliver Karen , Betteridge Emma , Skelton Jason , Andrews Peter W , Barbaric Ivana 
Published: July 2020

AbstractCopy number variants (CNVs) are genomic rearrangements implicated in numerous congenital and acquired diseases, including cancer. In human pluripotent stem cells (PSC), the appearance of culture-acquired CNVs prompted concerns for their use in regenerative medicine applications. A particularly common problem in PSC is the occurrence of CNVs in the q11.21 region of chromosome 20. However, the exact mechanisms of origin of this amplicon remains elusive due to the difficulty in delineating its sequence and breakpoints. Here, we used long-range Nanopore sequencing on two examples of this CNV, present as a duplication in one and a triplication in another line. The CNVs were arranged in a head-to-tail orientation in both lines, with sequences of microhomologies flanking or overlapping both the proximal and distal breakpoints. These breakpoint signatures point to a specific mechanism of template switching in CNV formation, with surroundingAlusequences likely contributing to the instability of this genomic region.
Bayesian Decoder Models with a Discriminative Observation Process
Authors: Rezaei Mohammad R. , Hadjinicolaou Alex E. , Cash Sydney S. , Eden Uri T. , Yousefi Ali 
Published: July 2020

AbstractThe Bayesian state-space neural encoder-decoder modeling framework is an established solution to reveal how changes in brain dynamics encode physiological covariates like movement or cognition. Although the framework is increasingly being applied to progress the field of neuroscience, its application to modeling high-dimensional neural data continues to be a challenge. Here, we propose a novel solution that avoids the complexity of encoder models that characterize high-dimensional data as a function of the underlying state processes. We build a discriminative model to estimate state processes as a function of current and previous observations of neural activity. We then develop the filter and parameter estimation solutions for this new class of state-space modeling framework called the “direct decoder” model. We applied the model to decode movement trajectories of a rat in a W-shaped maze from the ensemble spiking activity of place cells and achieve comparable performance to modern decoding solutions, without needing an encoding step in the model development. We further demonstrate how a dynamical auto-encoder can be built using the direct decoder model; where the underlying state process links the high-dimensional neural activity to the behavioral readout. We applied the dynamical auto-encoder model in estimating the intention to verbally communicate of an epileptic participant and their companions. The result shows that the dynamical auto-encoder can optimally estimate the low-dimensional dynamical manifold which represents the relationship between the brain and behavior.
PhageAI - Bacteriophage Life Cycle Recognition with Machine Learning and Natural Language Processing
Authors: Tynecki Piotr , Guziński Arkadiusz , Kazimierczak Joanna , Jadczuk Michał , Dastych Jarosław , Onisko Agnieszka 
Published: July 2020

AbstractBackgroundAs antibiotic resistance is becoming a major problem nowadays in a treatment of infections, bacteriophages (also known as phages) seem to be an alternative. However, to be used in a therapy, their life cycle should be strictly lytic. With the growing popularity of Next Generation Sequencing (NGS) technology, it is possible to gain such information from the genome sequence. A number of tools are available which help to define phage life cycle. However, there is still no unanimous way to deal with this problem, especially in the absence of well-defined open reading frames. To overcome this limitation, a new tool is definitely needed.ResultsWe developed a novel tool, called PhageAI, that allows to access more than 10 000 publicly available bacteriophages and differentiate between their major types of life cycles: lytic and lysogenic. The tool included life cycle classifier which achieved 98.90% accuracy on a validation set and 97.18% average accuracy on a test set. We adopted nucleotide sequences embedding based on the Word2Vec with Ship-gram model and linear Support Vector Machine with 10-fold cross-validation for supervised classification. PhageAI is free of charge and it is available athttps://phage.ai/. PhageAI is a REST web service and available as Python package.ConclusionsMachine learning and Natural Language Processing allows to extract information from bacteriophages nucleotide sequences for lifecycle prediction tasks. The PhageAI tool classifies phages into either virulent or temperate with a higher accuracy than any existing methods and shares interactive 3D visualization to help interpreting model classification results.
Independence of Cued and Contextual Components of Fear Conditioning is Gated by the Lateral Habenula
Authors: Sachella Tomas E. , Ihidoype Marina R. , Proulx Christophe D. , Pafundo Diego E. , Medina Jorge H. , Mendez Pablo , Piriz Joaquin 
Published: July 2020

AbstractFear is an extreme form of aversion that, if inappropriately generalized, initiates pathological conditions such as panic or anxiety. Fear conditioning (FC) is the best understood model of fear learning. During FC two independent associations link the cue and the training context to fear expression. The lateral habenula (LHb) is a general encoder of aversion. However, its role in fear learning has not been intensively studied. Here we studied the role of the LHb in FC using optogenetics and pharmacological tools in rats. Disrupting the neuronal activity of the LHb during training abolishes the expression of fear to isolated presentation of the training context or the cue, yet the recall of both associations when the cue is played in the training context reveals a conserved memory. Our results demonstrate that the LHb is required for the formation of independently expressible contextual and cued memories, a previously uncharacterized role in FC.
Chemoproteomics-Enabled Ligand Screening Yields Covalent RNF114-Based Degraders that Mimic Natural Product Function
Authors: Luo Mai , Spradlin Jessica N. , Brittain Scott M. , McKenna Jeffery M. , Tallarico John A. , Schirle Markus , Maimone Thomas J. , Nomura Daniel K. 
Published: July 2020

AbstractThe translation of natural product function to fully synthetic small molecules has remained an important process in medicinal chemistry for decades resulting in numerous FDA-approved medicines. We recently discovered that the terpene natural product nimbolide can be utilized as a covalent recruiter of the E3 ubiquitin ligase RNF114 for use in targeted protein degradation (TPD) – a powerful therapeutic modality within modern day drug discovery. Using activity-based protein profiling-enabled covalent ligand screening approaches, we herein report the discovery of fully synthetic RNF114-based recruiter molecules that can also be exploited for PROTAC applications, and demonstrate their utility in degrading therapeutically relevant targets such as BRD4 and BCR-ABL in cells. The identification of simple and easily manipulated drug-like scaffolds that can mimic the function of a complex natural product is beneficial in further expanding the toolbox of E3 ligase recruiters, an area of great importance in drug discovery and chemical biology.