bluuebunny/crossref_metadata_2025_split huggingface dataset:
Telacebec for ultra-short treatment of Buruli ulcer in a mouse model
Authors: Almeida Deepak V. , Converse Paul J. , Omansen Till F. , Tyagi Sandeep , Tasneen Rokeya , Kim Jeongjun , Nuermberger Eric L. 
Published: February 2020

ABSTRACTTelacebec (Q203) is a new anti-tubercular drug with extremely potent activity againstMycobacterium ulcerans. Here, we explored the treatment-shortening potential of Q203 alone or in combination with rifampin (RIF) in a mouse footpad infection model. The first study compared Q203 at 5 and 10 mg/kg doses alone and with rifampin. Q203 alone rendered most mouse footpads culture-negative in 2 weeks. Combining Q203 with rifampin resulted in relapse-free cure 24 weeks after completing 2 weeks of treatment, compared to a 25% relapse rate in mice receiving RIF+clarithromycin, the current standard of care, for 4 weeks.The second study explored the dose-ranging activity of Q203 alone and with RIF, including the extended activity of Q203 after treatment discontinuation. The bactericidal activity of Q203 persisted for ≥ 4 weeks beyond the last dose. All mice receiving just 1 week of Q203 at 2-10 mg/kg were culture-negative 4 weeks after stopping treatment. Mice receiving 2 weeks of Q203 at 0.5, 2 and 10 mg/kg were culture-negative 4 weeks after treatment. RIF did not increase the efficacy of Q203. A pharmacokinetics sub-study revealed that Q203 doses of 2-10 mg/kg in mice produce plasma concentrations similar to those produced by 100-300 mg doses in humans, with no adverse effect of RIF on Q203 concentrations.These results indicate the extraordinary potential of Q203 to reduce the duration of treatment necessary for cure to ≤ 1 week (or 5 doses of 2-10 mg/kg) in our mouse footpad infection model and warrant further evaluation of Q203 in clinical trials.
Differential activation of P-TEFb complexes in the development of cardiomyocyte hypertrophy following activation of distinct GPCRs
Authors: Martin Ryan D. , Sun Yalin , MacKinnon Sarah , Cuccia Luca , Pagé Viviane , Hébert Terence E. , Tanny Jason C. 
Published: February 2020

AbstractPathological cardiac hypertrophy is driven by neurohormonal activation of specific G protein-coupled receptors (GPCRs) in cardiomyocytes and is accompanied by large-scale changes in cardiomyocyte gene expression. These transcriptional changes require activity of positive transcription elongation factor b (P-TEFb), which is recruited to target genes by the bromodomain protein Brd4 or theSuperElongationComplex (SEC). Here we describe GPCR-specific regulation of these P-TEFb complexes and a novel mechanism for activating Brd4 in primary neonatal rat cardiomyocytes. The SEC was required for the hypertrophic response downstream of either the α1-adrenergic receptor (α1-AR) or the endothelin receptor (ETR). In contrast, Brd4 inhibition selectively impaired the α1-AR response. This was corroborated by the finding that activation of α1-AR, but not ETR, increased Brd4 occupancy at promoters and super enhancers of hypertrophic genes. Transcriptome analysis demonstrated that activation of both receptors initiated similar gene expression programs, but that Brd4 inhibition attenuated hypertrophic genes more robustly following α1-AR activation. Finally, we show that protein kinase A (PKA) is required for α1-AR stimulation of Brd4 chromatin occupancy. The differential role of the Brd4/P-TEFb complex in response to distinct GPCR pathways has potential clinical implications as therapies targeting this complex are currently being explored for heart failure.
Nasal high-frequency percussive ventilation versus nasal continuous positive airway pressure in term and preterm neonates exhibiting respiratory distress: a randomized controlled trial (TONIPEP; NCT 02030691)
Authors: Laurent Renesme , Eric Dumas de la Roque , Christine Germain , Agnès Chevrier , Muriel Rebola , Sophie Cramaregeas , Antoine Benard , Christophe Elleau , Olivier Tandonnet 
Published: February 2020

AbstractObjectiveTo determine whether the use of nasal, high-frequency percussive ventilation (nHFPV) to manage neonatal respiratory distress decreases the regional cerebral oxygen saturation (rScO2) below that afforded by nasal continuous positive airway pressure (nCPAP).DesignMonocentric, prospective, randomized, monocentric, open-label, non-inferiority crossover trial.PatientsNewborns of gestational age (GA) ≥ 33 weeks exhibiting persistent respiratory distress after 10 min of life (Silverman score ≥ 4).InterventionnHFPV and nCPAP, in succession and in random order.Main outcome measureMean rScO2, as revealed by near-infrared spectroscopy (NIRS) performed over the last 5 min of each ventilation mode. To show that nHFPV was not inferior to nCPAP, our a priori calculations required that the lower boundary of the bilateral 95% confidence interval (CI) of the difference between the mean rScO2 values of each ventilation mode should exceed –5.ResultsForty-nine newborns were randomized and 46 were analyzed. The mean (± standard deviation [SD]) GA and birth weight were 36.4 ± 1.9 weeks and 2,718 ± 497 g. The diagnosis was transient tachypnea in 65% of cases and respiratory distress syndrome in 35%. The mean rScO2 difference during the last 5 min of each ventilation mode (nHFPV minus nCPAP) was – 0.7 ± 5.4% (95% CI –2.25; 0.95). Neither a period effect nor a period-treatment interaction was evident. The mean transcutaneous carbon dioxide values (n = 26) for nCPAP and nHFPV were 7.1 ± 4.8 and 7.9 ± 5.1 kPa, respectively. No harmful or unintentional effect was observed.ConclusionIn our study on newborns of GA ≥ 33 weeks treated for respiratory distress, cerebral oxygenation via nHFPV was not inferior to nCPAP.What is already known on the topicNon-invasive high-frequency ventilation is feasible in preterm newborns and seems to improve ventilation compared to nasal CPAP.We previously showed that nasal high-frequency percussive ventilation (nHFPV) was more efficient that nCPAP for respiratory distress management in newborns of gestational age (GA) ≥ 35 weeks.The impact of mechanical ventilation, especially high-frequency modes, on cerebral blood flow in neonates is of concern.What this study addsnHFPV was well-tolerated and non-inferior to nasal CPAP as measured by rScO2 levels when used to manage respiratory distress at birth in newborns of GA ≥ 33 weeks.
Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCoV, in the nasal tissue
Authors: Wu Chao , Zheng Shufa , Chen Yu , Zheng Min 
Published: February 2020

AbstractA novel coronavirus (2019-nCoV) was first identified in Wuhan, Hubei Province, and then spreads to the other Provinces of China. WHO decides to determine a Public Health Emergency of International Concern (PHEIC) of 2019-nCoV. 2019-nCov was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-Cov. Here based on the public single-cell RNA-Seq datasets, we analyzed the ACE2 RNA expression profile in the tissues at different locations of the respiratory tract. The result indicates that the ACE2 expression appears in nasal epithelial cells. We found that the size of this population of ACE2-expressing nasal epithelial cells is comparable with the size of the population of ACE2-expression type II alveolar cells (AT2) in the Asian sample reported by Yu Zhao et al. We further detected 2019-nCoV by polymerase chain reaction (PCR) from the nasal-swab and throat-swab of seven suspected cases. We found that 2019-nCoV tends to have a higher concentration in the nasal-swab comparing to the throat-swab, which could attribute to the ACE2-expressing nasal epithelial cells. We hope this study could be informative for virus-prevention strategy development, especially the treatment of nasal mucus.
Graph neural representational learning of RNA secondary structures for predicting RNA-protein interactions
Authors: Yan Zichao , Hamilton William L. , Blanchette Mathieu 
Published: February 2020

AbstractMotivationRNA-protein interactions are key effectors of post-transcriptional regulation. Significant experimental and bioinformatics efforts have been expended on characterizing protein binding mechanisms on the molecular level, and on highlighting the sequence and structural traits of RNA that impact the binding specificity for different proteins. Yet our ability to predict these interactionsin silicoremains relatively poor.ResultsIn this study, we introduce RPI-Net, a graph neural network approach for RNA-protein interaction prediction. RPI-Net learns and exploits a graph representation of RNA molecules, yielding significant performance gains over existing state-of-the-art approaches. We also introduce an approach to rectify particular type of sequence bias present in many CLIP-Seq data sets, and we show that correcting this bias is essential in order to learn meaningful predictors and properly evaluate their accuracy. Finally, we provide new approaches to interpret the trained models and extract simple, biologically-interpretable representations of the learned sequence and structural motifs.AvailabilitySource code can be accessed athttps://www.github.com/HarveyYan/RNAonGraph.Contactwlh@cs.mcgill.ca,blanchem@cs.mcgill.ca
PHF3 regulates neuronal gene expression through the new Pol II CTD reader domain SPOC
Authors: Appel Lisa-Marie , Franke Vedran , Bruno Melania , Grishkovskaya Irina , Kasiliauskaite Aiste , Schoeberl Ursula E. , Puchinger Martin G. , Kostrhon Sebastian , Beltzung Etienne , Mechtler Karl , Lin Gen , Vlasova Anna , Leeb Martin , Pavri Rushad , Stark Alexander , Akalin Altuna , Stefl Richard , Bernecky Carrie , Djinovic-Carugo Kristina , Slade Dea 
Published: February 2020

SUMMARYThe C-terminal domain (CTD) of the largest subunit of RNA polymerase II (Pol II) is a regulatory hub for transcription and RNA processing. Here, we identify PHD-finger protein 3 (PHF3) as a new CTD-binding factor that negatively regulates transcription and mRNA stability. The PHF3 SPOC domain preferentially binds to CTD repeats phosphorylated on Serine-2 and PHF3 tracks with Pol II across the length of genes. PHF3 competes with TFIIS for Pol II binding through its TFIIS-like domain (TLD), thus inhibiting TFIIS-mediated rescue of backtracked Pol II. PHF3 knock-out or PHF3 SPOC deletion in human cells result in gene upregulation and a global increase in mRNA stability, with marked derepression of neuronal genes. Key neuronal genes are aberrantly expressed in Phf3 knock-out mouse embryonic stem cells, resulting in impaired neuronal differentiation. Our data suggest that PHF3 is a prominent effector of neuronal gene regulation at the interface of transcription elongation and mRNA decay.
A Comprehensive Survey of Genomic Mutations in Breast Cancer Reveals Recurrent Neoantigens as Potential Therapeutic Targets
Authors: Liu Songming , Chen Chao , Zhang Xiuqing 
Published: February 2020

AbstractNeoantigens are newly formed antigens generated by cancer cells but absent in normal cells. With their high specificity and immunogenicity characteristic, neoantigens are considered as an ideal target for immunotherapy. This study was aimed to investigate the signature of neoantigens in breast cancer. Somatic mutations, including SNVs and indels, were obtained from cBioPortal of 5991 breast cancer patients. For neoantigen prediction, 738 non-silent somatic variants present in at least 3 patients were selected., PIK3CA (38%), the highly mutated gene in breast cancer, can produce the highest number of neoantigens per gene. Some pan-cancer hotspot mutations, such as PIK3CA E545K (6.93%), can be recognized by at least one HLA molecule. Since there are more SNVs than indels in breast cancer, SNVs are the major source of neoantigens. Patients with hormone receptor positive or HER2 positive are more competent to produce neoantigens. Age, but not clinical stage, is a significant contributory factor of neoantigens production. We believe a detailed description of breast cancer neoantigens signatures could contribute to neoantigens based immunotherapy development.
Ant guards influence the mating system of their plant hosts by altering pollinator behaviour
Authors: Villamil Nora , Boege Karina , Stone Graham N. 
Published: February 2020

AbstractAnt guards can increase plant fitness by deterring herbivores but may also reduce it by interfering with pollination, hence ant-plant interactions are ideal systems in which to study costs and benefits of mutualisms. While ant impacts on herbivory are well-studied, much less is known about impacts on pollinators and associated consequences for plant mating systems and fitness. We used field experiments to quantify the effect of ant guards on pollinator community composition, frequency and duration of flower visits, and cascading effects on plant mating system and plant fitness inTurnera velutina(Passifloraceae). Although ant patrolling did not affect pollinator community composition or visitation frequency, it decreased pollinator foraging time and flower visit duration. Such behavioural changes resulted in reduced pollen deposition on stigmas, decreasing male fitness whilst increasing outcrossing rates. This study contributes to understanding how non-pollinators, such as these defensive mutualists, can shape plant mating systems.
Identification of key proteins involved in stickleback environmental adaption with system-level analysis
Authors: Hall Martina , Kültz Dietmar , Almaas Eivind 
Published: February 2020

ABSTRACTUsing abundance measurements of 1,490 proteins from four separate populations of three-spined sticklebacks, we implemented a system-level approach to correlate proteome dynamics with environmental salinity and temperature and the fish’s population and morphotype. We identified sets of robust and accurate fingerprints that predict environmental salinity, temperature, morphotype and the population sample origin, observing that proteins with specific functions are enriched in these fingerprints. Highly apparent functions represented in all fingerprints include ion transport, proteostasis, growth, and immunity, suggesting that these functions are most diversified in populations inhabiting different environments.Applying a differential network approach, we analyzed the network of protein interactions that differs between populations. Looking at specific population combinations of differential interaction, we identify sets of connected proteins. We find that these sets and their corresponding enriched functions reflect key processes that have diverged between the four populations. Moreover, the extent of divergence, i.e. the number of enriched functions that differ between populations, is highest when all three environmental parameters are different between two populations. Key nodes in the differential interaction network signify functions that are also inherent in the fingerprints, most prominently proteostasis-related functions. However, the differential interaction network also reveals additional functions that have diverged between populations, notably cytoskeletal organization and morphogenesis.Having such a large proteomic dataset, the strength of these analyses is that the results are purely data-driven, not based on previous findings and hypotheses about adaptation. With such an unbiased approach applied on a large proteomic dataset, we find the strongest signals given by the data, making it possible to develop more discriminatory and complex biomarkers for specific contexts of interest.
Large-scale sequence similarity analysis reveals the scope of sequence and function divergence in PilZ domain proteins
Authors: Cheang Qing Wei , Sheng Shuo , Xu Linghui , Liang Zhao-Xun 
Published: February 2020

AbstractPilZ domain-containing proteins constitute a superfamily of widely distributed bacterial signalling proteins. Although studies have established the canonical PilZ domain as an adaptor protein domain evolved to specifically bind the second messenger c-di-GMP, mounting evidence suggest that the PilZ domain has undergone enormous divergent evolution to generate a superfamily of proteins that are characterized by a wide range of c-di-GMP-binding affinity, binding partners and cellular functions. The divergent evolution has even generated families of non-canonical PilZ domains that completely lack c-di-GMP binding ability. In this study, we performed a large-scale sequence analysis on more than 28,000 single- and di-domain PilZ proteins using the sequence similarity networking tool created originally to analyse functionally diverse enzyme superfamilies. The sequence similarity networks (SSN) generated by the analysis feature a large number of putative isofunctional protein clusters, and thus, provide an unprecedented panoramic view of the sequence-function relationship and function diversification in PilZ proteins. Some of the protein clusters in the networks are considered as unexplored clusters that contain proteins with completely unknown biological function; whereas others contain one, two or a few functionally known proteins, and therefore, enabling us to infer the cellular function of uncharacterized homologs or orthologs. With the ultimate goal of elucidating the diverse roles played by PilZ proteins in bacterial signal transduction, the work described here will facilitate the annotation of the vast number of PilZ proteins encoded by bacterial genome and help to prioritize functionally unknown PilZ proteins for future studies.ImportanceAlthough PilZ domain is best known as the protein domain evolved specifically for the binding of the second messenger c-di-GMP, divergent evolution has generated a superfamily of PilZ proteins with a diversity of ligand or protein-binding properties and cellular functions. We analysed the sequences of more than 28,000 PilZ proteins using the sequence similarity networking (SSN) tool to yield a global view of the sequence-function relationship and function diversification in PilZ proteins. The results will facilitate the annotation of the vast number of PilZ proteins encoded by bacterial genomes and help us prioritize PilZ proteins for future studies.
Integration of Brain and Behavior Measures for Identification of Data-Driven Groups Cutting Across Children with ASD, ADHD, or OCD
Authors: Jacobs Grace R. , Voineskos Aristotle N. , Hawco Colin , Stefanik Laura , Forde Natalie J. , Dickie Erin W. , Lai Meng-Chuan , Szatmari Peter , Schachar Russell , Crosbie Jennifer , Arnold Paul D. , Goldenberg Anna , Erdman Lauren , Lerch Jason P. , Anagnostou Evdokia , Ameis Stephanie H. 
Published: February 2020

AbstractAutism spectrum disorder (ASD), obsessive-compulsive disorder (OCD) and attention-deficit/hyperactivity disorder (ADHD) are clinically and biologically heterogeneous neurodevelopmental disorders (NDDs). The objective of the present study was to integrate brain imaging and behavioral measures to identify new brain-behavior subgroups cutting across these disorders. A subset of the data from the Province of Ontario Neurodevelopmental Disorder (POND) Network including participants with different NDDs (aged 6-16 years) that underwent cross-sectional T1-weighted and diffusion-weighted magnetic resonance imaging (MRI) scanning on the same 3T scanner, and behavioral/cognitive assessments was used. Similarity Network Fusion was applied to integrate cortical thickness, subcortical volume, white matter fractional anisotropy (FA), and behavioral measures in 176 children with ASD, ADHD or OCD with complete data that passed quality control. Normalized mutual information (NMI) was used to determine top contributing model features. Bootstrapping, out-of-model outcome measures and supervised machine learning were each used to examine stability and evaluate the new groups. Cortical thickness in socio-emotional and attention/executive networks and inattention symptoms comprised the top ten features driving participant similarity and differences between four transdiagnostic groups. Subcortical volumes (pallidum, nucleus accumbens, thalamus) were also different among groups, although white matter FA showed limited differences. Features driving participant similarity remained stable across resampling, and the new groups showed significantly different scores on everyday adaptive functioning. Our findings open the possibility of studying new data-driven groups that represent children with NDDs more similar to each other than others within their own diagnostic group. Such new groups can be evaluated longitudinally for prognostic utility and could be stratified for clinical trials targeted toward each group’s unique brain and behavioral profiles.
Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks
Authors: Kim Robert , Sejnowski Terrence J. 
Published: February 2020

AbstractCortical neurons process information on multiple timescales, and areas important for working memory (WM) contain neurons capable of integrating information over a long timescale. However, the underlying mechanisms for the emergence of neuronal timescales stable enough to support WM are unclear. By analyzing a spiking recurrent neural network (RNN) model trained on a WM task and activity of single neurons in the primate prefrontal cortex, we show that the temporal properties of our model and the neural data are remarkably similar. Dissecting our RNN model revealed strong inhibitory-to-inhibitory connections underlying a disinhibitory microcircuit as a critical component for long neuronal timescales and WM maintenance. We also found that enhancing inhibitory-to-inhibitory connections led to more stable temporal dynamics and improved task performance. Finally, we show that a network with such microcircuitry can perform other tasks without disrupting its pre-existing timescale architecture, suggesting that strong inhibitory signaling underlies a flexible WM network.
Differential response to cytotoxic therapy explains treatment dynamics of AML patients: insights from a mathematical modelling approach
Authors: Hoffmann H. , Thiede C. , Glauche I. , Bornhaeuser M. , Roeder I. 
Published: February 2020

AbstractDisease response and durability of remission are very heterogeneous in patients with acute myeloid leukaemia (AML) patients. There is increasing evidence that the individual risk of early relapse can be predicted based on the initial treatment response. However, it is unclear how such a correlation is linked to functional aspects of AML progression and treatment. We suggest a mathematical model in which leukaemia-initiating cells and normal/healthy hematopoietic stem and progenitor cells reversibly change between an active state characterized by proliferation and chemosensitivity and a quiescent state, in which the cells do not divide, but are also insensitive to chemotherapy. Applying this model to 275 molecular time courses of NPM1-mutated patients, we conclude that the differential chemosensitivity of the leukaemia-initiating cells together with the cells’ intrinsic proliferative capacity is sufficient to reproduce both, early relapse as well as long-lasting remission. We can, furthermore, show that the model parameters associated with individual chemosensitivity and proliferative advantage of the leukemic cells are closely linked to the patients’ time to relapse. They can, therefore, be used as a measure of the aggressiveness of the disease. Early assessment of these measures and incorporation into risk stratification schemes will improve risk assessment and individual treatment in AML.