bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of dialysis, tracheostomy, and extracorporeal membrane oxygenation among 842,928 patients hospitalized with COVID-19 in the United States
Authors: Burn Edward , Sena Anthony G. , Prats-Uribe Albert , Spotnitz Matthew , DuVall Scott , Lynch Kristine E. , Matheny Michael E. , Nyberg Fredrik , Ahmed Waheed-Ul-Rahman , Alser Osaid , Alghoul Heba , Alshammari Thamir , Zhang Lin , Casajust Paula , Areia Carlos , Shah Karishma , Reich Christian , Blacketer Clair , Andryc Alan , Fortin Stephen , Natarajan Karthik , Gong Mengchun , Golozar Asieh , Morales Daniel , Rijnbeek Peter , Subbian Vignesh , Roel Elena , Recalde Martina , Lane Jennifer C.E. , Vizcaya David , Posada Jose D. , Shah Nigam H. , Jonnagaddala Jitendra , Lai Lana Yin Hui , Avilés-Jurado Francesc Xavier , Hripcsak George , Suchard Marc A. , Ranzani Otavio T. , Ryan Patrick , Prieto-Alhambra Daniel , Kostka Kristin , Duarte-Salles Talita 
Published: November 2020

AbstractObjectiveTo estimate the proportion of patients hospitalized with COVID-19 who undergo dialysis, tracheostomy, and extracorporeal membrane oxygenation (ECMO).DesignA network cohort study.SettingSeven databases from the United States containing routinely-collected patient data: HealthVerity, Premier, IQVIA Hospital CDM, IQVIA Open Claims, Optum EHR, Optum SES, and VA-OMOP.PatientsPatients hospitalized with a clinical diagnosis or a positive test result for COVID-19.InterventionsDialysis, tracheostomy, and ECMO.Measurements and Main Results842,928 patients hospitalized with COVID-19 were included (22,887 from HealthVerity, 77,853 from IQVIA Hospital CDM, 533,997 from IQVIA Open Claims, 36,717 from Optum EHR, 4,336 from OPTUM SES, 156,187 from Premier, and 10,951 from VA-OMOP). Across the six databases, 35,192 (4.17% [95% CI: 4.13% to 4.22%]) patients received dialysis, 6,950 (0.82% [0.81% to 0.84%]) had a tracheostomy, and 1,568 (0.19% [95% CI: 0.18% to 0.20%]) patients underwent ECMO over the 30 days following hospitalization. Use of ECMO was more common among patients who were younger, male, and with fewer comorbidities. Tracheostomy was broadly used for a similar proportion of patients regardless of age, sex, or comorbidity. While dialysis was generally used for a similar proportion among younger and older patients, it was more frequent among male patients and among those with chronic kidney disease.ConclusionUse of dialysis among those hospitalized with COVID-19 is high at around 4%. Although less than one percent of patients undergo tracheostomy and ECMO, the absolute numbers of patients who have undergone these interventions is substantial.
Transcranial Focused Ultrasound Alters Conflict and Emotional Processing, Physiology, and Performance I: Dorsal Anterior Cingulate Cortex Targeting
Authors: Fini Maria , Tyler William J. 
Published: November 2020

ABSTRACTThe dorsal anterior cingulate cortex (dACC) operates as an integrator of bottom-up and top-down signals and is implicated in both cognitive control and emotional processing. The dACC is believed to be causally involved in switching between attention networks, and previous work has linked it to cognitive performance, concentration, relaxation, and emotional distraction. The present study was designed to evaluate the feasibility of influencing default mode network (DMN) activity and emotional attention by targeting and modulating the dACC with transcranial focused ultrasound (tFUS). Subjects were divided into two groups, one receiving MR-neuronavigated tFUS to the dACC and the other an identical, but inactive tFUS sham. Subjects performed a modified version of the Erikson flanker paradigm using fear and neutral faces as emotional background distractors. Our observations demonstrate that tFUS can be targeted to the human dACC to produce effects consistent with those expected from relaxed contention, including significantly reduced reaction time slowing due to emotional distractors, and an increase in parasympathetic markers of the HRV. These results suggest that tFUS altered emotional processing and enhanced sustained attention, perhaps by facilitating reduced attentional engagement with emotional distractors and reduced need for attention switching evidenced by significant effects on event related potentials (ERPs), reduced alpha suppression, and modulation of delta and theta EEG activity. We conclude that the dACC represents a viable neuroanatomical target for tFUS in order to modulate DMN activity, including emotional attention, conflict resolution, and cognitive control. These effects of dACC-targeted tFUS may prove useful for treating certain mental health disorders known to involve perturbed DMN activity, such as depression and anxiety.
Serum Metabolites Associated with Brain Amyloid Beta Deposition, Cognitive Dysfunction, and Alzheimer’s Disease Progression
Authors: Nho Kwangsik , Kueider-Paisley Alexandra , Arnold Matthias , MahmoudianDehkordi Siamak , Risacher Shannon L. , Louie Gregory , Blach Colette , Baillie Rebecca , Han Xianlin , Kastenmüeller Gabi , Doraiswamy P. Murali , Kaddurah-Daouk Rima , Saykin Andrew J. ,   for the Alzheimer’s Disease Neuroimaging Initiative and the Alzheimer Disease Metabolomics Consortium
Published: November 2020

AbstractRATIONALEMetabolomics in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort provides a powerful tool for mapping biochemical changes in AD, and a unique opportunity to learn about the association between circulating blood metabolites and brain amyloid-β deposition in AD.OBJECTIVESWe examined 140 serum metabolites and their associations with brain amyloid-β deposition, cognition, and conversion from mild cognitive impairment (MCI) to AD.FINDINGSSerum-based targeted metabolite levels were measured in 1,531 ADNI participants. We performed association analysis of metabolites with brain amyloid-β deposition measured from [18F] Florbetapir PET scans. We identified nine metabolites as significantly associated with amyloid-β deposition after FDR-based multiple comparison correction. Higher levels of one acylcarnitine (C3; propionylcarnitine) and one biogenic amine (kynurenine) were associated with decreased amyloid-β accumulation. However, higher levels of seven phosphatidylcholines (PC) were associated with increased amyloid deposition. In addition, PC ae C44:4 was significantly associated with cognition and conversion from MCI to AD dementia.CONCLUSIONPerturbations in PC and acylcarnitine metabolism may play a role in features intrinsic to AD including amyloid-β deposition and cognitive performance.
Finding metabolic pathways in large networks through atom-conserving substrate-product pairs
Authors: Hafner Jasmin , Hatzimanikatis Vassily 
Published: November 2020

AbstractFinding biosynthetic pathways is essential for metabolic engineering of organisms to produce chemicals, biodegradation prediction of pollutants and drugs, and for the elucidation of bioproduction pathways of secondary metabolites. A key step in biosynthetic pathway design is the extraction of novel metabolic pathways from big networks that integrate known biological, as well as novel, predicted biotransformations. However, especially with the integration of big data, the efficient analysis and navigation of metabolic networks remains a challenge. Here, we propose the construction of searchable graph representations of metabolic networks. Éach reaction is decomposed into pairs of reactants and products, and each pair is assigned a weight, which is calculated from the number of conserved atoms between the reactant and the product molecule. We test our method on a biochemical network that spans 6,546 known enzymatic reactions to show how our approach elegantly extracts biologically relevant metabolic pathways from biochemical networks, and how the proposed network structure enables the application of efficient graph search algorithms that improve navigation and pathway identification in big metabolic networks. The weighted reactant-product pairs of an example network and the corresponding graph search algorithm are available online. The proposed method extracts metabolic pathways fast and reliably from big biochemical networks, which is inherently important for all applications involving the engineering of metabolic networks.
Discovery of Small-Molecule Antagonists of the PWWP Domain of NSD2
Authors: de Freitas Renato Ferreira , Liu Yanli , Szewczyk Magdalena M. , Mehta Naimee , Li Fengling , McLeod David , Zepeda-Velázquez Carlos , Dilworth David , Hanley Ronan P. , Gibson Elisa , Brown Peter J. , Al-Awar Rima , James Lindsey Ingerman , Arrowsmith Cheryl H. , Barsyte-Lovejoy Dalia , Min Jinrong , Vedadi Masoud , Schapira Matthieu , Allali-Hassani Abdellah 
Published: November 2020

ABSTRACTIncreased activity of the lysine methyltrans-ferase NSD2 driven by translocation and activating mutations is associated with multiple myeloma and acute lymphoblastic leukemia, but no NSD2-targeting chemical probe has been reported to date. Here, we present the first antagonists that block the protein-protein interaction between the N-terminal PWWP domain of NSD2 and H3K36me2. Using virtual screening and experimental validation, we identified the small-molecule antagonist3f, which binds to the NSD2-PWWP1 domain with a Kdof 3.4 μM and abrogates histone H3K36me2 binding in cells. This study establishes an alternative approach to targeting NSD2 and provides a small-molecule antagonist that can be further optimized into a chemical probe to better understand the cellular function of this protein.
An evolutionary algorithm for designing microbial communities via environmental modification
Authors: Pacheco Alan R. , Segrè Daniel 
Published: November 2020

AbstractDespite a growing understanding of how environmental composition affects microbial community properties, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbor thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and dynamic flux balance analysis (dFBA) that selects optimal environmental compositions to produce target community phenotypes. In this framework, dFBA is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behavior of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to more closely approach this target. We apply this iterative process toin silicocommunities of varying sizes, showing how it can rapidly identify environments that yield desired phenotypes. Moreover, this novel combination of approaches produces testable predictions for thein vivoassembly of microbial communities with specific properties, and can facilitate rational environmental design processes for complex microbiomes.
ArabidopsisbZIP11 is a susceptibility factor duringPseudomonas syringaeinfection
Authors: Prior Matthew J. , Selvanayagam Jebasingh , Kim Jung-Gun , Tomar Monika , Jonikas Martin , Mudgett Mary Beth , Smeekens Sjef , Hanson Johannes , Frommer Wolf B. 
Published: November 2020

AbstractThe induction of plant nutrient secretion systems is critical for successful pathogen infection. Some bacterial pathogens,e.g. Xanthomonasspecies, use TAL (transcription activator-like) effectors to induce transcription of SWEET sucrose efflux transporters.Pseudomonas syringaepathovar (pv.)tomatostrain DC3000 lacks TAL effectors, yet is able to induce multiple SWEETs inArabidopsis thalianaby unknown mechanisms. Since bacteria require other nutrients besides sugars for efficient reproduction, we hypothesized thatPseudomonasmay depend on host transcription factors involved in secretory programs to increase access to essential nutrients. Bioinformatic analyses identified theArabidopsisbasic-leucine zipper transcription factor bZIP11 as a potential regulator of nutrient transporters, including SWEETs and UmamiT amino acid transporters. Inducible downregulation ofbZIP11expression inArabidopsisresulted in reduced growth ofP. syringaepv.tomatostrain DC3000, whereas inducible overexpression ofbZIP11resulted in increased bacterial growth, supporting the hypothesis that bZIP11 regulated transcription programs are essential for maximal pathogen titer in leaves. Our data are consistent with a model in which a pathogen alters host transcription factor expression upstream of secretory transcription networks to promote nutrient efflux from host cells.
Cyber-yeast: Automatic synchronisation of the cell cycle in budding yeast through closed-loop feedback control
Authors: Perrino Giansimone , Napolitano Sara , Galdi Francesca , La Regina Antonella , Fiore Davide , Giuliano Teresa , di Bernardo Mario , di Bernardo Diego 
Published: November 2020

ABSTRACTThe cell cycle is the process by which eukaryotic cells replicate. Yeast cells cycle asynchronously with each cell in the population budding at a different time. Although there are several experimental approaches to “synchronise” cells, these work only in the short-term. Here, we built a cyber-genetic system to achieve long-term synchronisation of the cell population, by interfacing genetically modified yeast cells with a computer by means of microfluidics to dynamically change medium, and a microscope to estimate cell cycle phases of individual cells. The computer implements a “controller” algorithm to decide when, and for how long, to change the growth medium to synchronise the cell-cycle across the population. Our work builds upon solid theoretical foundations provided by Control Engineering. In addition to providing a new avenue for yeast cell cycle synchronisation, our work shows that computers can automatically steer complex biological processes towards desired behaviours similarly to what is currently done with robots and autonomous vehicles.
Pharmacologic profiling reveals lapatinib as a novel antiviral against SARS-CoV-2 in vitro
Authors: Raymonda M. H. , Ciesla J. H. , Monaghan M. , Leach J. , Asantewaa G. , Smorodintsev-Schiller L.A. , Lutz M. M. , Schafer X. L. , Takimoto T. , Dewhurst S. , Munger J. , Harris I. S. 
Published: November 2020

SUMMARYThe emergence of SARS-CoV-2 virus has resulted in a worldwide pandemic, but an effective antiviral therapy has yet to be discovered. To improve treatment options, we conducted a high-throughput drug repurposing screen to uncover compounds that block the viral activity of SARS-CoV-2. A minimally pathogenic human betacoronavirus (OC43) was used to infect physiologically-relevant human pulmonary fibroblasts (MRC5) to facilitate rapid antiviral discovery in a preclinical model. Comprehensive profiling was conducted on more than 600 compounds, with each compound arrayed at 10 dose points (ranging from 20 μM to 1 nM). Our screening revealed several FDA-approved agents that act as novel antivirals that block both OC43 and SARS-CoV-2 viral replication, including lapatinib, doramapimod, and 17-AAG. Importantly, lapatinib inhibited SARS-CoV-2 replication by over 50,000-fold without any toxicity and at doses readily achievable in human tissues. Further, both lapatinib and doramapimod could be combined with remdesivir to dramatically improve antiviral activity in cells. These findings reveal novel treatment options for people infected with SARS-CoV-2 that can be readily implemented during the pandemic.
Hybrid Hyperalignment: A single high-dimensional model of shared information embedded in cortical patterns of response and functional connectivity
Authors: Busch Erica L. , Slipski Lukas , Feilong Ma , Swaroop Guntupalli J. , di Oleggio Castello Matteo Visconti , Huckins Jeremy F. , Nastase Samuel A. , Ida Gobbini M. , Wager Tor D. , Haxby James V. 
Published: November 2020

AbstractShared information content is represented across brains in idiosyncratic functional topographies. Hyperalignment addresses these idiosyncrasies by using neural responses to project individuals’ brain data into a common model space while maintaining the geometric relationships between distinct activity patterns. The dimensions of this common model can encode any kind of functional profiles shared across individuals, such as cortical response profiles collected during a common time-locked stimulus presentation (e.g. movie viewing) or functional connectivity profiles. Performing hyperalignment with either response-based or connectivity-based input data derives transformations to project individuals’ neural data from anatomical space into the common model such that functional information is optimally aligned across brains. Previously, only response or connectivity profiles were used in the derivation of these transformations. In this study, we used three separate data sets collected while participants watched feature films to derive transformations representing both response-based and connectivity-based information with a single algorithm. Our new method, hybrid hyperalignment, aligns response-based information as well as or better than response hyperalignment while simultaneously aligning connectivity-based information better than connectivity hyperalignment, all in one information space. These results suggest that a single common information space could encode both shared cortical response and functional connectivity profiles across individuals.
A quantitative view of strategies to engineer cell-selective ligand binding
Authors: Tan Zhixin Cyrillus , Orcutt-Jahns Brian , Meyer Aaron S. 
Published: November 2020

AbstractA critical property of many therapies is their selective binding to specific target populations. Exceptional specificity can arise from high-affinity binding to unique cell surface targets. In many cases, however, therapeutic targets are only expressed at subtly different levels relative to off-target cells. More complex binding strategies have been developed to overcome this limitation, including multi-specific and multi-valent molecules, but these create a combinatorial explosion of design possibilities. Therefore, guiding strategies for developing cell-specific binding are critical to employ these tools. Here, we extend a multi-valent binding model to multi-ligand and multi-receptor interactions. Using this model, we explore a series of mechanisms to engineer cell selectivity, including mixtures of molecules, affinity adjustments, and valency changes. Each of these strategies maximizes selectivity in distinct cases, leading to synergistic improvements when used in combination. Finally, we identify situations in which selectivity cannot be derived through passive binding alone to highlight areas in need of new developments. In total, this work uses a quantitative model to unify a comprehensive set of design guidelines for engineering cell-specific therapies.Summary pointsAffinity, valency, and other alterations to target cell binding provide enhanced selectivity in specific situations.Evidence for the effectiveness and limitations of each strategy are abundant within the drug development literature.Combining strategies can offer enhanced selectivity.A simple, multivalent ligand-receptor binding model can help to direct therapeutic engineering.
Triple Combination Nitazoxanide, Ribavirin, and Hydroxychloroquine results in the multiplicative reduction of in vitro SARS-CoV-2 viral replication
Authors: Lian Elena , McAlister Carley , Ramirez Gabriela , Chernoff David N. , Went Gregory , Hoopes Justin , Perera Rushika 
Published: November 2020

AbstractBackgroundAn immediate unmet medical need exists to test and develop existing approved drugs against SARS-COV-2. Despite many efforts, very little progress has been made regarding finding low-cost oral medicines that can be made widely available worldwide to address the global pandemic.MethodsWe sought to examine if a triple combination of nitazoxanide (using its active metabolite tizoxanide), ribavirin, and hydroxychloroquine would lead to a multiplicative effects on viral replication of SARS-COV-2 resulting in a significant reduction of virus yield using VERO E6 cells as a model of viral replication.ResultsVirus yield measured in PFU/ml was ~ 2 logs lower with triple combination versus either drug alone, resulting in the prolongation of time to peak cytopathic effects (CPE). The time to produce 50% CPE increased from 2.8 days for viral controls versus 5.3 days for triple combination therapy. Finally, for each 1-log reduction in virus yield 24 hours post-infection, there was an additional 0.7-day delay in onset of CPE.ConclusionsA triple combination of tizoxanide, ribavirin, and hydroxychloroquine produced a reduction in SARS-COV-2 viral replication in Vero E6 cells, warranting exploration in additional cell lines as well as human clinical trials.
Cell-Free Biosynthesis to Evaluate Lasso Peptide Formation and Enzyme-Substrate Tolerance
Authors: Si Yuanyuan , Kretsch Ashley M. , Daigh Laura M. , Burk Mark J. , Mitchell Douglas A. 
Published: November 2020

AbstractLasso peptides are ribosomally synthesized and post-translationally modified peptide (RiPP) natural products that display a unique lariat-like structure. Owing to a rigid topology, lasso peptides are unusually stable towards heat and proteolytic degradation. Some lasso peptides have been shown to bind human cell-surface receptors and exhibit anticancer properties, while others display antibacterial or antiviral activities. Known lasso peptides are produced by bacteria and genome-mining studies indicate that lasso peptides are a relatively prevalent RiPP class; however, the discovery, isolation, and characterization of lasso peptides are constrained by the lack of an efficient production system. In this study, we employ a cell-free biosynthesis (CFB) strategy to address the longstanding challenges associated with lasso peptide production. We report the successful formation of a diverse array of lasso peptides that include known examples as well as a new predicted lasso peptide from Thermobifida halotolerans. We further demonstrate the utility of CFB to rapidly generate and characterize multisite precursor peptide variants in order to evaluate the substrate tolerance of the biosynthetic pathway. We show that the lasso-forming cyclase from the fusilassin pathway can produce millions of sequence-diverse lasso peptides via CFB with an extraordinary level of sequence permissiveness within the ring region of the lasso peptide. These data lay a firm foundation for the creation of large lasso peptide libraries using CFB to identify new variants with unique properties.