bluuebunny/crossref_metadata_2025_split huggingface dataset:
Myoelectric digit action decoding with multi-label, multi-class classification: an offline analysis
Authors: Krasoulis Agamemnon , Nazarpour Kianoush 
Published: March 2020

ABSTRACTThe ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are typically used to reconstruct position/velocity trajectories from surface electromyogram (EMG) signals. Although such methods have produced highly-accurate results in offline analyses, their success in real-time prosthesis control settings has been rather limited. In this work, we propose action decoding, a paradigm-shifting approach for independent, multi-digit movement intent decoding based on multi-label, multi-class classification. At each moment in time, our algorithm classifies movement action for each available DOF into one of three categories: open, close, or stall (i.e., no movement). Despite using a classifier as the decoder, arbitrary hand postures are possible with our approach. We analyse a public dataset previously recorded and published by us, comprising measurements from 10 able-bodied and two transradial amputee participants. We demonstrate the feasibility of using our proposed action decoding paradigm to predict movement action for all five digits as well as rotation of the thumb. We perform a systematic offline analysis by investigating the effect of various algorithmic parameters on decoding performance, such as feature selection and choice of classification algorithm and multi-output strategy. The outcomes of the offline analysis presented in this study will be used to inform the real-time implementation of our algorithm. In the future, we will further evaluate its efficacy with real-time control experiments involving upper-limb amputees.
Loss of Hem1 disrupts macrophage function and impacts on migration, phagocytosis and integrin-mediated adhesion
Authors: Stahnke Stephanie , Döring Hermann , Kusch Charly , de Gorter David J.J. , Dütting Sebastian , Guledani Aleks , Pleines Irina , Schnoor Michael , Sixt Michael , Geffers Robert , Rohde Manfred , Müsken Mathias , Kage Frieda , Steffen Anika , Faix Jan , Nieswandt Bernhard , Rottner Klemens , Stradal T.E.B. 
Published: March 2020

ABSTRACTThe hematopoietic-specific protein 1 (Hem1) comprises an essential subunit of the WAVE Regulatory Complex (WRC) in immune cells. WRC has a fundamental role in Arp2/3 complex activation and the protrusion of branched actin networks in motile cells.Hem1 deficiency leads to suppression of the entire WRC in immune cells. Defective WRC function in macrophages results in loss of lamellipodia and migration defects. Moreover, phagocytosis, commonly accompanied by lamellipodium protrusion during cup formation, is altered in Hem1 null cells concerning frequency and efficacy. When analyzing cell spreading, adhesion and podosome formation, we found that Hem1 null cells are capable, in principle, of podosome formation and consequently, do not show any quantitative differences in extracellular matrix degradation. Their adhesive behavior, however, was significantly altered. Specifically, adhesion as well as de-adhesion of Hem1 null cells was strongly compromised, likely contributing to the observed reduced efficiency of phagocytosis. In line with this, phosphorylation of the prominent adhesion component paxillin was diminished. Non-hematopoietic somatic cells disrupted in expression for both Hem1 and its ubiquitous orthologue Nck-associated protein 1 (Nap1) or the essential WRC components Sra-1/PIR121 did not only confirm defective paxillin phosphorylation, but also revealed that paxillin turnover in focal adhesions is accelerated in the absence of WRC. Finally, adhesion assays using platelets lacking functional WRC as model system unmasked radically decreased αIIbβ3 integrin activation.Our results thus demonstrate that WRC-driven actin networks impact on integrin-dependent processes controlling formation and dismantling of different types of cell-substratum adhesion.One sentence summaryInterference of Hem1 function in mice and cells uncovers a hitherto unrecognized role in integrin-mediated cell adhesion that is crucial for macrophage function and connects to recently discovered immunodeficiencies in patients carrying Hem1 mutations.
Activation of p21 limits acute lung injury and induces early senescence after acid aspiration and mechanical ventilation
Authors: Blázquez-Prieto Jorge , Huidobro Covadonga , López-Alonso Inés , Amado-Rodriguez Laura , Martín-Vicente Paula , López-Martínez Cecilia , Crespo Irene , Pantoja Cristina , Fernandez-Marcos Pablo J , Serrano Manuel , Sznajder Jacob I , Albaiceta Guillermo M 
Published: March 2020

AbstractThe p53/p21 pathway is activated in response to cell stress. However, its role in acute lung injury has not been elucidated. Acute lung injury is associated with disruption of the alveolo-capillary barrier leading to acute respiratory distress syndrome (ARDS). Mechanical ventilation may be necessary to support gas exchange in patients with ARDS, however, high positive airway pressures can cause regional overdistension of alveolar units and aggravate lung injury. Here, we report that acute lung injury and alveolar overstretching activate the p53/p21 pathway to maintain homeostasis and avoid massive cell apoptosis. A systematic pooling of transcriptomic data from animal models of lung injury demonstrates the enrichment of specific p53- and p21-dependent gene signatures and a validated senescence profile. In a clinically relevant, murine model of acid aspiration and mechanical ventilation, we observed changes in the nuclear envelope and the underlying chromatin, DNA damage and activation of theTp53/p21 pathway. Absence ofCdkn1adecreased the senescent response, but worsened lung injury due to increased cell apoptosis. Conversely, treatment with lopinavir/ritonavir led toCdkn1aoverexpression and ameliorated cell apoptosis and lung injury. The activation of these mechanisms was associated with early markers of senescence, including expression of senescence-related genes and increases in senescence-associated heterochromatin foci in alveolar cells. Autopsy samples from lungs of patients with ARDS revealed increased senescence-associated heterochromatin foci. Collectively, these results suggest that acute lung injury activates p53/p21 as an anti-apoptotic mechanism to ameliorate damage, but with the side effect of induction of senescence.
Fibrinolytic niche is requested for alveolar type 2 cell-mediated alveologenesis and injury repair
Authors: Gibran Ali , Zhao Runzhen , Zhang Mo , Jain Krishan G. , Chang Jianjun , Komatsu Satoshi , Fang Xiaohui , Zhou Beiyun , Liang Jiurong , Jiang Dianhua , Ikebe Mistuo , Matthay Michael A , Ji Hong-Long 
Published: March 2020

ABSTRACTCOVID-19, SARS, and MERS are featured by fibrinolytic dysfunction. To test the role of the fibrinolytic niche in the regeneration of alveolar epithelium, we compared the self-renewing capacity of alveolar epithelial type 2 (AT2) cells and its differentiation to AT1 cells between wild type (wt) and fibrinolytic niche deficient mice (Plau−/−andSerpine1Tg). A significant reduction in both proliferation and differentiation of deficient AT2 cells was observedin vivoand in 3D organoid cultures. This decrease was mainly restored by uPA derived A6 peptide, a binding fragment to CD44 receptors. The proliferative and differential rate of CD44+AT2 cells was greater than that of CD44−controls. There was a reduction in transepithelial ion transport in deficient monolayers compared to wt cells. Moreover, we found a marked suppression in total AT2 cells and CD44+subpopulation in lungs from brain dead patients with acute respiratory distress syndrome (ARDS) and a mouse model infected by influenza viruses. Thus, we demonstrate that the fibrinolytic niche can regulate AT2-mediated homeostasis and regeneration via a novel uPA-A6-CD44+-ENaC cascade.
Differential alphavirus defective RNA diversity between intracellular and encapsidated compartments is driven by subgenomic recombination events
Authors: Langsjoen RM , Muruato AE , Kunkel SR , Jaworski E , Routh A 
Published: March 2020

ABSTRACTAlphaviruses are positive-sense RNA arboviruses that can cause either a chronic arthritis or a potentially lethal encephalitis. Like other RNA viruses, alphaviruses produce truncated, defective genomes featuring large deletions during replication. Defective RNAs (D-RNAs) have primarily been isolated from virions after high-multiplicity of infection passaging. Here, we aimed to characterize both intracellular and packaged viral D-RNA populations during early passage infections under the hypothesis that D-RNAs arisede novointracellularly that may not be packaged and thus have remained undetected. To this end, we generated NGS libraries using RNA derived from passage 1 (P1) stock chikungunya virus (CHIKV) 181/clone 25, intracellular virus, and encapsidated P2 virus and analyzed samples for D-RNA expression, followed by diversity and differential expression analyses. We found that the diversity of D-RNA species is significantly higher for intracellular D-RNA populations than encapsidated and specific populations of D-RNAs are differentially expressed between intracellular and encapsidated compartments. Importantly, these trends were likewise observed in a murine model of CHIKV 15561 infection, as well asin vitrostudies using related Mayaro, Sindbis, and Aura viruses. Additionally, we identified a novel subtype of subgenomic D-RNA that are conserved across arthritogenic alphaviruses. D-RNAs specific to intracellular populations were defined by recombination events specifically in the subgenomic region, which was confirmed by direct RNA nanopore sequencing of intracellular CHIKV RNAs. Together, these studies show that only a portion of D-RNAs generated intracellularly are packaged and D-RNAs readily arisede novoin the absence of transmitted template.IMPORTANCEOur understanding of viral defective RNAs (D-RNAs), or truncated viral genomes, comes largely from passaging studies in tissue culture under artificial conditions and/or packaged viral RNAs. Here, we show that specific populations of alphavirus D-RNAs arisede novoand that they are not packaged into virions, thus imposing a transmission bottleneck and impeding their prior detection. This raises important questions about the roles of D-RNAs, both in nature and in tissue culture, during viral infection and whether their influence is constrained by packaging requirements. Further, during the course of these studies, we found a novel type of alphavirus D-RNA that is enriched intracellularly; dubbed subgenomic D-RNAs (sgD-RNAs), they are defined by deletion boundaries between capsid/E3 and E1/3’UTR regions and are common to chikungunya, Mayaro, Sindbis, and Aura viruses. These sgD-RNAs are enriched intracellularly and do not appear to be selectively packaged, and additionally may exist as subgenome-derived transcripts.
Epigenetic downregulation of HER2 during EMT leads to tumor resistance to HER2-targeted therapies in breast cancer
Authors: Nami Babak , Ghanaeian Avrin , Wang Zhixiang 
Published: March 2020

ABSTRACTHER2 receptor tyrosine kinase (encoded byERBB2gene) is overexpressed in approximately 25% of all breast cancer tumors (known as HER2-positive breast cancers). Overexpression of HER2 causes overactivation of downstream receptor tyrosine kinase pathways including PI3K/Akt and MAPK pathways and is a poor prognosis factor in breast cancer. Tyrosine kinase inhibitor lapatinib and anti-HER2 monoclonal antibodies trastuzumab and pertuzumab are FDA-approved HER2-targeted drugs for treatment of HER2-positive breast cancers. However, development of de novo resistance to HER2 blockade occurs in majority of patients after treatment started. Resistance to HER2 targeting therapies partially due to the loss of HER2 expression on their tumor cells during the treatment. But little is known about the exact mechanism of loss of HER2 on originally HER2-positive tumor cells. Downregulation of extracellular HER2 by metalloproteinases during epithelial-mesenchymal transition (EMT) in trastuzumab-resistant/lapatinib-sensitive cells has been shown by limited studies, however, the mechanism of ERBB2 gene silencing during EMT and in the mesenchymal-like cells derived from trastuzumab-resistant/lapatinib-resistant HER2-positive breast tumors was entirely unknown. In this study, hypothesized that EMT abrogates HER2 expression by chromatin-based epigenetic silencing ofERBB2gene as a mechanism of acquired resistance to HER2-targeted therapies. we found that HER2 expression is positively and negatively correlated with the expression of epithelial and mesenchymal phenotype marker genes respectively in breast cancer tumors. We also found that chromatin ofERBB2gene in HER2-high epithelial-like breast cancer cells is active, while, the chromatin is inactive in HER2-low mesenchymal-like cells. HER2-low breast cancer cell line also revealed less promoter-enhancer interaction and small chromatin loops compared to the HER2-high cell lines. The lower HER2 expression, the higher EMT phenotype, and inactivated chromatin all were found correlated with a lower response to lapatinib. The higher EMT phenotype was found correlated with a lower response to lapatinib. We also found that induction of EMT of HER2-positive breast cancer BT474 cells results in downregulated HER2 expression and lower binding rate of trastuzumab to the cells. These results show that the downregulation of HER2 in mesenchymal-like cells in the culture of HER2-positive breast cancer cell lines was due toERBB2gene silencing by epigenetic reprogramming of the cells during EMT. These results indicate thatERBB2gene silencing by epigenetic regulation during EMT is the main mechanism of resistance of HER2-positive breast cancer cells to trastuzumab and lapatinib.
Chromosome-scale genome assemblies of aphids reveal extensively rearranged autosomes and long-term conservation of the X chromosome
Authors: Mathers Thomas C. , Wouters Roland H. M. , Mugford Sam T. , Swarbreck David , Van Oosterhout Cock , Hogenhout Saskia A. 
Published: March 2020

AbstractLarge-scale chromosome rearrangements are arguably the most dramatic type of mutations, often leading to rapid evolution and speciation. However, chromosome dynamics have only been studied at the sequence level in a small number of model systems. In insects, Diptera (flies and mosquitoes) and Lepidoptera (butterflies and moths) have high levels of chromosome conservation. Whether this truly reflects the diversity of insect genome evolution is questionable given that many species exhibit rapid karyotype evolution. Here, we investigate chromosome evolution in aphids – an important group of hemipteran plant pests – using newly generated chromosome-scale genome assemblies of the green peach aphid (Myzus persicae) and the pea aphid (Acyrthosiphon pisum), and a previously published chromosome-scale assembly of the corn-leaf aphid (Rhopalosiphum maidis). We find that aphid autosomes have undergone dramatic reorganisation over the last 30 million years, to the extent that chromosome homology cannot be determined between aphids from the tribes Macrosiphini (M. persicaeandA. pisum) and Aphidini (R. maidis). In contrast, gene content of the aphid sex (X) chromosome remained unchanged despite rapid sequence evolution, low gene expression and high transposable element load. To test whether rapid evolution of genome structure is a hallmark of Hemiptera, we compared our aphid assemblies to chromosome-level assemblies of two blood-feeding Hemiptera (Rhodnius prolixusandTriatoma rubrofasciata). Despite being more diverged, the blood-feeding hemipterans have conserved synteny and we detect only two chromosome fusion or fission events. The exceptional rate of structural evolution of aphid autosomes renders them an important emerging model system for studying the role of large-scale genome rearrangements in evolution.
A model to estimate bed demand for COVID-19 related hospitalization
Authors: Zhang Teng , McFarlane Kelly , Vallon Jacqueline , Yang Linying , Xie Jin , Blanchet Jose , Glynn Peter , Staudenmayer Kristan , Schulman Kevin , Scheinker David 
Published: March 2020

AbstractAs of March 23, 2020 there have been over 354,000 confirmed cases of coronavirus disease 2019 (COVID-19) in over 180 countries, the World Health Organization characterized COVID-19 as a pandemic, and the United States (US) announced a national state of emergency.1, 2, 3 In parts of China and Italy the demand for intensive care (IC) beds was higher than the number of available beds.4, 5 We sought to build an accessible interactive model that could facilitate hospital capacity planning in the presence of significant uncertainty about the proportion of the population that is COVID-19+ and the rate at which COVID-19 is spreading in the population. Our approach was to design a tool with parameters that hospital leaders could adjust to reflect their local data and easily modify to conduct sensitivity analyses.We developed a model to facilitate hospital planning with estimates of the number of Intensive Care (IC) beds, Acute Care (AC) beds, and ventilators necessary to accommodate patients who require hospitalization for COVID-19 and how these compare to the available resources. Inputs to the model include estimates of the characteristics of the patient population and hospital capacity. We deployed this model as an interactive online tool.6 The model is implemented in R 3.5, RStudio, RShiny 1.4.0 and Python 3.7. The parameters used may be modified as data become available, for use at other institutions, and to generate sensitivity analyses.We illustrate the use of the model by estimating the demand generated by COVID-19+ arrivals for a hypothetical acute care medical center. The model calculated that the number of patients requiring an IC bed would equal the number of IC beds on Day 23, the number of patients requiring a ventilator would equal the number of ventilators available on Day 27, and the number of patients requiring an AC bed and coverage by the Medicine Service would equal the capacity of the Medicine service on Day 21.In response to the COVID-19 epidemic, hospitals must understand their current and future capacity to care for patients with severe illness. While there is significant uncertainty around the parameters used to develop this model, the analysis is based on transparent logic and starts from observed data to provide a robust basis of projections for hospital managers. The model demonstrates the need and provides an approach to address critical questions about staffing patterns for IC and AC, and equipment capacity such as ventilators.
Prediction of coronary disease incidence in the general population by circulating RNY(YRNA)-derived small RNA
Authors: Costa Vera L. , Ruidavet Jean-Bernard , Bongard Vanina , Perret Bertrand , Repetto Emanuela , Stathopoulou Maria G. , Serra Fabrizio , Benahmed Mohamed , Claire Mauduit , Grandjean Valerie , Ferrières Jean , Martinez Laurent O. , Trabucchi Michele 
Published: March 2020

ABSTRACTDuring the development of atherosclerotic lesion, s-RNYs (small RNAs of about 24/34 nucleotides) are derived by the processing of long Ro-associated non-coding RNAs (RNYs) in macrophages. The levels of serum s-RNYs have been found significantly upregulated in patients with coronary heart disease (CHD) compared to age-matched healthy individuals. The present study aimed to examine the predictive value of serum s-RNYs for CHD events in the general population.Within the frame of nested-case-control study, the GENES study, we measured the absolute expression of a RNY-derived small RNA, the s-RNY1-5p, in the serum of healthy individuals who encountered a CHD event within 12 years of follow-up (n = 31) (Cases) and compared them to individuals who remained event-free (Controls) (n = 30).The expression of s-RNY1-5p in serum was significantly upregulated in Cases compared to Controls (p = 0.027). The proportion of CHD event-free was significantly higher among individuals with serum s-RNY1-5p below the median value (631 molecule / mL). In a multivariate model adjusted for age, smoking and treatment for hypertension, diabetes and dyslipidemia, the risk of CHD events increased more than 4-fold in individuals with serum s-RNY1-5p above the median value (HR, 4.36; 95%CI, 1.22-15.60). Significant association with CHD events was also observed when considering s-RNY1-5p as a continuous variable (p = 0.022). Serum s-RNY1-5p is an independent predictor of CHD in healthy individuals and could be considered as a biomarker in primary prevention of cardiovascular diseases.TRANSLATIONAL PERSPECTIVESHere, we reported that s-RNY1-5p was significantly upregulated in the serum of individuals who underwent CHD and was positively associated with CHD events. Those results argue in favor of s-RNY1-5p being a novel predictive molecular biomarker for cardiovascular events. In the future, measurement of s-RNY1-5p expression levels and other 5’ s-RNYs, such as s-RNY4-5p, could be used in clinical practice in addition to classical risk factors to identify those high-risk individuals who might benefit from prevention medicine.
Whole GenomeDe NovoVariant Identification with FreeBayes and Neural Network Approaches
Authors: Richter Felix , Morton Sarah U. , Qi Hongjian , Kitaygorodsky Alexander , Wang Jiayao , Homsy Jason , DePalma Steven , Patel Nihir , Gelb Bruce D. , Seidman Jonathan G. , Seidman Christine E. , Shen Yufeng 
Published: March 2020

AbstractMotivationDe novovariant (DNV) calling typically relies on heuristic filters intrinsic to specific platforms and variant calling algorithms. FreeBayes and neural network approaches have overcome this limitation for variant calling, and we implemented a similar approach for DNV identification.ResultsWe developed a DNV calling framework that uses Genome Analysis Toolkit (GATK), FreeBayes and a neural network trained on Integrative Genomics Viewer pile-up plots (IGV-bot). We identified DNVs in 2,390 WGS trios and benchmarked results against heuristics based on GATK parameters. Results were validatedin silicoand with Sanger sequencing, with the latter showing true positive rates of 98.4% and 97.3% for SNVs and indels, respectively. Taken together we describe a scalable framework for DNV identification based on both FreeBayes and neural network methods.AvailabilitySource code and documentation are available athttps://github.com/ShenLab/igv-classifierandhttps://github.com/frichter/dnv_pipelineunder the MIT license.Contactys2411@cumc.columbia.edu