bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dust settling instability in protoplanetary discs
Authors: Krapp Leonardo , Youdin Andrew N , Kratter Kaitlin M , Benítez-Llambay Pablo 
Published: June 2020

ABSTRACT
The streaming instability (SI) has been extensively studied in the linear and non-linear regimes as a mechanism to concentrate solids and trigger planetesimal formation in the mid-plane of protoplanetary discs. A related dust settling instability (DSI) applies to particles while settling towards the mid-plane. The DSI has previously been studied in the linear regime, with predictions that it could trigger particle clumping away from the mid-plane. This work presents a range of linear calculations and non-linear simulations, performed with fargo3d, to assess conditions for DSI growth. We expand on previous linear analyses by including particle size distributions and performing a detailed study of the amount of background turbulence needed to stabilize the DSI. When including binned size distributions, the DSI often produces converged growth rates with fewer bins than the standard SI. With background turbulence, we find that the most favourable conditions for DSI growth are weak turbulence, characterized by α ≲ 10−6 with intermediate-sized grains that settle from one gas scale height. These conditions could arise during a sudden decrease in disc turbulence following an accretion outburst. Ignoring background turbulence, we performed a parameter survey of local 2D DSI simulations. Particle clumping was either weak or occurred slower than particles settle. Clumping was reduced by a factor of 2 in a comparison 3D simulation. Overall, our results strongly disfavour the hypothesis that the DSI significantly promotes planetesimal formation. Non-linear simulations of the DSI with different numerical methods could support or challenge these findings.
What binary systems are the most likely sources for periodically repeating FRBs?
Authors: Zhang Xianfei , Gao He 
Published: June 2020

ABSTRACT
The newly discovered 16.35-d period for repeating FRB 180916.J0158+65 provides an essential clue for understanding the sources and emission mechanism of repeating fast radio bursts (FRBs). Many models propose that the periodically repeating FRBs might be related to binary star systems that contain at least one neutron star (NSC-FRB system). It has been suggested that the neutron star ‘combed’ by the strong wind from a companion star might provide a solution. Following the binary comb model, we use the population synthesis method to study in detail the properties of the companion stars and the nature of NSC-FRB systems. Our main findings are as follows: (1) the companion star is most likely to be a B-type star; (2) the period of 16 d of FRB 180916 happens to fall in the most probable period range, which may explain why FRB 180916 was the first detected periodically repeating FRB, and we expect to observe more periodically repeating FRBs with periods around 10–30 d; and (3) the birth rate for the NSC-FRB system is large enough to fulfill the event rate requirement set by the observation of FRB 180916, which supports the proposal that the NSC-FRB can provide one significant channel for producing periodically repeating FRBs.
Analysis of methanol maser flares in G107.298+5.63 and S255-NIRS3
Authors: Gray M D , Etoka S , Pimpanuwat B 
Published: June 2020

ABSTRACT
A 3D maser model has been used to perform an inverse problem on the light curves from three high-amplitude maser flares, selected on the basis of contemporaneous infrared observations. Plots derived from the model recover the size of the maser cloud, and two parameters linked to saturation, from three observational properties of the light curve. Recovered sizes are consistent with independent interferometric measurements. Maser objects transition between weak and moderate saturation during a flare.
Electric field manipulation enhanced by strong spin-orbit coupling: promoting rare-earth ions as qubits
Authors: Liu Zheng , Wang Ye-Xin , Fang Yu-Hui , Qin Si-Xue , Wang Zhe-Ming , Jiang Shang-Da , Gao Song 
Published: June 2020

Abstract
Quantum information processing based on magnetic ions has potential for applications as the ions can be modified in their electronic properties and assembled by a variety of chemical methods. For these systems to achieve individual spin addressability and high energy efficiency, we exploited the electric field as a tool to manipulate the quantum behaviours of the rare-earth ion which has strong spin-orbit coupling. A Ce:YAG single crystal was employed with considerations to the dynamics and the symmetry requirements. The Stark effect of the Ce3+ ion was observed and measured. When demonstrated as a quantum phase gate, the electric field manipulation exhibited high efficiency which allowed up to 57 π/2 operations before decoherence with optimized field direction. It was also utilized to carry out quantum bang-bang control, as a method of dynamic decoupling, and the refined Deutsch-Jozsa algorithm. Our experiments highlighted rare-earth ions as potentially applicable qubits because they offer enhanced spin-electric coupling which enables high-efficiency quantum manipulation.
A Methionine Sulfoxide Reductase B Is Required for the Establishment of Astragalus sinicus–Mesorhizobium Symbiosis
Authors: Si Zaiyong , Guan Ning , Zhou Yuan , Mei Lingli , Li Yixing , Li Youguo 
Published: June 2020

AbstractMethionine sulfoxide reductase B (MsrB) is involved in oxidative stress or defense responses in plants. However, little is known about its role in legume–rhizobium symbiosis. In this study, an MsrB gene was identified from Astragalus sinicus and its function in symbiosis was characterized. AsMsrB was induced under phosphorus starvation and displayed different expression patterns under symbiotic and nonsymbiotic conditions. Hydrogen peroxide or methyl viologen treatment enhanced the transcript level of AsMsrB in roots and nodules. Subcellular localization showed that AsMsrB was localized in the cytoplasm of onion epidermal cells and co-localized with rhizobia in nodules. Plants with AsMsrB-RNAi hairy roots exhibited significant decreases in nodule number, nodule nitrogenase activity and fresh weight of the aerial part, as well as an abnormal nodule and symbiosome development. Statistical analysis of infection events showed that plants with AsMsrB-RNAi hairy roots had significant decreases in the number of root hair curling events, infection threads and nodule primordia compared with the control. The content of hydrogen peroxide increased in AsMsrB-RNAi roots but decreased in AsMsrB overexpression roots at the early stage of infection. The transcriptome analysis showed synergistic modulations of the expression of genes involved in reactive oxygen species generation and scavenging, defense and pathogenesis and early nodulation. In addition, a candidate protein interacting with AsMsrB was identified and confirmed by bimolecular fluorescence complementation. Taken together, our results indicate that AsMsrB plays an essential role in nodule development and symbiotic nitrogen fixation by affecting the redox homeostasis in roots and nodules.
New Boxed Warning for Singulair
Authors: Aschenbrenner Diane S. 
Published: June 2020

The labeling of the asthma drug montelukast (Singulair) now includes a boxed warning regarding the risk of serious behavior and mood changes, as well as suicide, associated with its use.NPs should avoid prescribing montelukast as a first-line drug for asthma and allergic rhinitis. Nurses and NPs should provide education on potential mental health adverse effects to patients and their families.
Ahmed Versus Baerveldt Glaucoma Drainage Device in Uveitic Glaucoma: A Retrospective Comparative Study
Authors: Sinha Sapna , Ganjei Allen Y. , McWatters Zoe , Lee Daniel , Moster Marlene R. , Myers Jonathan S. , Kolomeyer Natasha , Mantravadi Anand V. , Pro Michael J. , Razeghinejad Reza 
Published: June 2020

Precis:
Baerveldt glaucoma drainage device demonstrated a greater reduction in intraocular pressure (IOP) than Ahmed in patients with uveitic glaucoma. The most common cause of failure was uncontrolled IOP in Ahmed and hypotony in the Baerveldt group.

Purpose:
To compare the efficacy and safety of Ahmed and Baerveldt glaucoma drainage devices in uveitic glaucoma.

Materials and Methods:
The retrospective comparative study included patients with uveitic glaucoma who underwent Ahmed or Baerveldt glaucoma drainage device implantation with a minimum follow-up of 3 months. Success was defined as IOP ≥6 and ≤21 mm Hg and >20% reduction on 2 consecutive visits after the third month with (qualified success) or without (complete success) medications and no further glaucoma surgery or loss of vision. IOP, number of medications, visual acuity, complications, and interventions were compared between groups.

Results:
In total, 137 eyes of 122 patients (67 Ahmed, 70 Baerveldt) were included. The preoperative IOP and number of medications in the Ahmed group (32.7±10.3 mm Hg; 4.1±1.3) were similar to Baerveldt (32.1±10.2 mm Hg; 4.3±1.3; P=0.73, 0.35). These at the last follow-up were (18.1±9.8 mm Hg; 2.1±1) in Ahmed and (12.7±6.9 mm Hg; 1.3±1.3) in Baerveldt groups (P=0.04, 0.01). The Baerveldt had greater IOP reduction (60.3% vs. 44.5%) and complete success rate (30% vs. 9%) with higher complication rate (51.4% vs. 20.9%) (all P≤0.05). The de novo glaucoma reoperation rate was 19% in the Ahmed group and 4% in the Baerveldt group (P=0.006). Hypotony resulted in failure in 7 eyes (10%) in the Baerveldt group and none in the Ahmed group (P=0.013).

Conclusions:
Higher complete success rate and significantly greater reduction in mean IOP and number of medications were observed in the Baerveldt group, but with a higher rate of complications including hypotony.
Tissue-Resident Macrophages in the Control of Infection and Resolution of Inflammation
Authors: Mu Xingjiang , Li Yutian , Fan Guo-Chang 
Published: June 2020

ABSTRACT
Macrophage, as an integral component of the immune system and the first responder to local damage, is on the front line of defense against infection. Over the past century, the prevailing view of macrophage origin states that all macrophage populations resided in tissues are terminally differentiated and replenished by monocytes from bone-marrow progenitors. Nonetheless, this theory has been reformed by ground-breaking discoveries from the past decades. It is now believed that tissue-resident macrophages (TRMs) are originated from the embryonic precursors and seeded in tissue prenatally. They can replenish via self-renewal throughout the lifespan. Indeed, recent studies have demonstrated that tissue-resident macrophages should not be classified by the over-simplified macrophage polarization (M1/M2) dogma during inflammation. Moreover, multiple lines of evidence have indicated that tissue-resident macrophages play critical roles in maintaining tissue homeostasis and facilitating tissue repair through controlling infection and resolving inflammation. In this review, we summarize the properties of resident macrophages in the lung, spleen, and heart, and further highlight the impact of TRM populations on inflammation control and tissue repair. We also discuss the potential role of local proliferation in maintaining a physiologically stable TRM pool in response to acute inflammation.
Impact of public health interventions on the COVID-19 epidemic: a stochastic model based on data from an African island
Authors: Nuckchady D. C. 
Published: June 2020

AbstractA stochastic model was created to simulate the impact of various healthcare measures on the COVID-19 epidemic. Travel restrictions and point of entry or exit screening help to delay the onset of the outbreak by a few weeks. Population surveillance is critical to detect the start of community transmission early and to avoid a surge in cases. Contact reduction and contact tracing are key interventions that can help to control the outbreak. To promptly curb the number of new cases, countries should diagnose patients using a highly sensitive test.
Timeline from receipt to online publication of COVID-19 original research articles
Authors: Barakat Amr F. , Shokr Mohamed , Ibrahim Joseph , Mandrola John , Elgendy Islam Y. 
Published: June 2020

AbstractObjectiveTo examine the timeline from submission of Coronavirus Disease 2019 (COVID)-related original articles compared with non-COVID-related original articles.BackgroundThere have been growing concerns about the speed and rigor of the review process for COVID-related articles by journals.MethodsUsing Dimensions, an online searchable platform, we identified PubMed-indexed journals that published >50 COVID-related articles (regardless of article type) between 1/1/2020 and 5/16/2020 and had available data on the date of article receipt. For the control group, we included consecutive full-length original investigations with available receipt date (regardless of topic) published in these journals starting from 3/1/2019 until a 1:2 ratio of COVID to non-COVID-related articles per journal was achieved.ResultsThe final number included 294 COVID-related full-length original investigations with available article receipt dates published in 16 journals with corresponding 588 control articles from the same journals. The median time from article receipt to online publication was 20 (11-32) days for COVID-articles vs. 119 (62-182) days for controls (P<0.001). The median time to final acceptance (available for 97% of the articles) was 13 (5-23) days for COVID vs. 102 (55-161) days for controls (P<0.001). These observations were seen across all the included journals in the analysis.ConclusionsIn this analysis of full-length original investigations published in 16 medical journals, the median time from receipt to final acceptance of COVID-related articles was 8 times faster compared to non-COVID-related articles published in a similar time frame in the previous year. Online publication was 6 times faster for COVID-related articles compared to controls.
Treatment of ARDS and hyperinflammation in COVID-19 with IL-6 antagonist Tocilizumab: a tertiary care experience from Pakistan
Authors: Nasir Nosheen , Mahmood Syed Faisal , Habib Kiren , Khanum Iffat , Jamil Bushra 
Published: June 2020

ABSTRACTCytokine release syndrome in COVID-19 is characterized by hyperinflammation which manifests as ARDS, multi-organ failure, and high inflammatory parameters. Tocilizumab, an IL-6 antagonist has been used in COVID-19 acute respiratory distress syndrome (ARDS) with conflicting results from different parts of the world. We conducted a retrospective descriptive study from Feb 2020 to May 2020 on COVID-19 patients with ARDS and hyperinflammation characterized by raised CRP and/or ferritin. A total of 244 patients with COVID-19 were admitted out of which 107 had ARDS. Thirty patients had both ARDS and hyperinflammation and received tocilizumab. The mean age was 62.5 years (SD: 13.5) and the majority were male (83%). The mean CRP pre-treatment was 217.5 mg/L and post 48 to 72 hours of tocilizumab treatment was 98.5 mg/L. Twenty-one patients (70%) also received concomitant intravenous methylprednisolone. Of the 30 patients, 7 died and 20 recovered. Ten patients required intensive care unit admission and nine developed nosocomial infections. COVID-19 associated aspergillosis was diagnosed in three patients post tocilizumab treatment. Mortality was significantly higher in patients who developed a nosocomial infection and who required intermittent positive pressure ventilation (IPPV). Our study is the first to describe the treatment outcomes with tocilizumab from a low-middle income country. The availability and cost of tocilizumab in our region which makes it imperative to understand its potential for use in our setting. Our study supports the use of tocilizumab in a select patient population with COVID-19 and recommends monitoring of nosocomial infections and opportunistic infections.
Intense bitterness of molecules: machine learning for expediting drug discovery
Authors: Margulis Eitan , Dagan-Wiener Ayana , Ives Robert S. , Jaffari Sara , Siems Karsten , Niv Masha Y. 
Published: June 2020

AbstractDrug development is a long, expensive and multistage process geared to achieving safe drugs with high efficacy. A crucial prerequisite for completing the medication regimen for oral drugs, particularly for pediatric and geriatric populations, is achieving taste that does not hinder compliance. Currently, the aversive taste of drugs is tested in late stages of clinical trials. This can result in the need to reformulate, potentially resulting in the use of more animals for additional toxicity trials, increased financial costs and a delay in release to the market. Here we present BitterIntense, a machine learning tool that classifies molecules into “very bitter” or “not very bitter”, based on their chemical structure. The model, trained on chemically diverse compounds, has above 80% accuracy on several test sets. BitterIntense suggests that intense bitterness does not correlate with toxicity and hepatotoxicity of drugs and that the prevalence of very bitter compounds among drugs is lower than among microbial compounds. BitterIntense allows quick and easy prediction of strong bitterness of compounds of interest for food and pharma industries. We estimate that implementation of BitterIntense or similar tools early in drug discovery and development process may lead to reduction in delays, in animal use and in overall financial burden.Significance StatementDrug development integrates increasingly sophisticated technologies, but extreme bitterness of drugs remains a poorly addressed cause of medicine regimen incompletion. Reformulating the drug can result in delays in the development of a potential medicine, increasing the lead time to the patients. It might also require the use of extra animals in toxicity trials and lead to increased costs for pharma companies. We have developed a computational predictor for intense bitterness, that has above 80% accuracy. Applying the classifier to annotated datasets suggests that intense bitterness does not correlate with toxicity and hepatotoxicity of drugs. BitterIntense can be used in the early stages of drug development to identify drug candidates that require bitterness masking, and thus reduce animal use, time and monetary loss.
Learning feedback loops in transcriptome network during cell fate transition
Authors: Xiong Lingyun , Schoenberg William A. , Swartz Jeremy D. 
Published: June 2020

AbstractEmbryonic development is characterized by series of cell fate transitions, during which non-linear feedback of signaling events and network dynamics in the transcriptome are instrumental to determine differentiation outcomes. Changes in selected genes or pathways have been described extensively, but a system-level understanding of gene regulatory network regulation is still lacking. Leveraging time-series data from single-cell transcriptome profiling of developing mouse embryos, we collapsed dynamic gene expressions into changes in 14 core biological processes, and constructed an ordinary differential equation-based machine learning model of the transcriptomic network to capture its feedback structure. We evaluated the polarity and magnitude of direct pairwise causal relationships between biological processes and identified higher-order feedback loops that dominate system behavior. Despite heterogeneous expressions at the gene level, we find that the transcriptome at the macroscale level has a feedback structure that is intrinsically stable and robust. We show the pivotal role of intracellular signaling in driving systemic changes and uncover the importance of homeostatic process and establishment of localization in regulating network dynamics. Local regulatory structures represent domain-specific regulations that are essential to cell fate transition, especially lipid metabolic process. Together, this study provides a holistic picture of transcriptomic network dynamics during mouse organogenesis, offering insight into key aspects of information flow in the transcriptome that control cell fate transition.Conflict of interest statementThe authors declare no potential conflicts of interest.FundingThe authors received no funding for this study.Author contributionsConceptualization: LX; Methodology: LX, WAS, and JDS; Data Curation: LX; Investigation: LX and WAS; Formal Analysis: LX and WAS; Visualization: WAS and LX;Writing – review & editing: LX and WAS.
Adaptation of STARR-seq method to be used with 3rdgeneration integrase-deficient promoterless lentiviral vectors
Authors: Matjusaitis Mantas , Tedesco Donato , Ciukas Azuolas 
Published: June 2020

ABSTRACTAbility to functionally screen gene regulatory sequences, such as promoters and enhancers, in high throughput manner is an important prerequisite for many basic and translational research programs. One of the methods that allow such screening is STARR-seq, or self-transcribing active regulatory region sequencing. It allows to quickly screen millions of candidate sequences in the cell type of interest. However, it does rely on transfection as a delivery method which can be a limiting-step for some hard-to-transfect cells such as senescent cells. Here we show that integration-deficient and integration-competent promoterless lentiviral particles can be used to deliver STARR-seq constructs into cells. These constructs reported CMV enhancer activity both at protein and mRNA level. While further validations are necessary, ability to deliver STARR-seq libraries using lentiviral particles will significantly improve the versatility and usability of such a method.
Systematic evaluation of parameters for genome-scale metabolic models of cultured mammalian cells
Authors: Schinn Song-Min , Morrison Carly , Wei Wei , Zhang Lin , Lewis Nathan E. 
Published: June 2020

AbstractGenome-scale metabolic models describe cellular metabolism with mechanistic detail. Given their high complexity, such models need to be parameterized correctly to yield accurate predictions and avoid overfitting. Effective parameterization has been well-studied for microbial models, but it remains unclear for higher eukaryotes, including mammalian cells. To address this, we enumerated model parameters that describe key features of cultured mammalian cells – including cellular composition, bioprocess performance metrics, mammalian-specific pathways, and biological assumptions behind model formulation approaches. We tested these parameters by building thousands of metabolic models and evaluating their ability to predict the growth rates of a panel of phenotypically diverse Chinese Hamster Ovary cell clones. We found the following considerations to be most critical for accurate parameterization: (1) cells limit metabolic activity to maintain homeostasis, (2) cell morphology and viability change dynamically during a growth curve, and (3) cellular biomass has a particular macromolecular composition. Depending on parameterization, models predicted different metabolic phenotypes, including contrasting mechanisms of nutrient utilization and energy generation, leading to varying accuracies of growth rate predictions. Notably, accurate parameter values broadly agreed with experimental measurements. These insights will guide future investigations of mammalian metabolism.