bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reovirus σ1 conformational flexibility modulates the efficiency of host cell attachment
Authors: Diller Julia R. , Halloran Sean R. , Koehler Melanie , dos Santos Natividade Rita , Alsteens David , Stehle Thilo , Dermody Terence S. , Ogden Kristen M. 
Published: June 2020

ABSTRACTReovirus attachment protein σ1 is a trimeric molecule containing tail, body, and head domains. During infection, σ1 engages sialylated glycans and junctional adhesion molecule-A (JAM-A), triggering uptake into the endocytic compartment, where virions are proteolytically converted to infectious subvirion particles (ISVPs). Further disassembly allows σ1 release and escape of transcriptionally active reovirus cores into the cytosol. Electron microscopy has revealed a distinct conformational change in σ1 from a compact form on virions to an extended form on ISVPs. To determine the importance of σ1 conformational mobility, we used reverse genetics to introduce cysteine mutations that can crosslink σ1 by establishing disulfide bonds between structurally adjacent sites in the tail, body, and head domains. We detected phenotypic differences among the engineered viruses. A mutant with a cysteine pair in the head domain replicates with enhanced kinetics, forms large plaques, and displays increased avidity for JAM-A relative to the parental virus, mimicking properties of ISVPs. However, unlike ISVPs, particles containing cysteine mutations that crosslink the head domain uncoat and transcribe viral positive-sense RNA with kinetics similar to the parental virus and are sensitive to ammonium chloride. Together, these data suggest that σ1 conformational flexibility modulates the efficiency of reovirus host cell attachment.IMPORTANCENonenveloped virus entry is an incompletely understood process. For reovirus, the functional significance of conformational rearrangements in the attachment protein, σ1, that occur during entry and particle uncoating are unknown. We engineered and characterized reoviruses containing cysteine mutations that crosslink σ1 monomers in non-reducing conditions. We found that the introduction of a cysteine pair in the receptor-binding domain of σ1 yielded a virus that replicates with faster kinetics than the parental virus and forms larger plaques. Using functional assays, we found that crosslinking the σ1 receptor-binding domain modulates reovirus attachment but not uncoating or transcription. These data suggest that σ1 conformational rearrangements mediate the efficiency of reovirus host cell attachment.
Prevalence and Predictors of General Psychiatric Disorders and Loneliness during COVID-19 in the United Kingdom: Results from the Understanding Society UKHLS
Authors: Li Lambert Zixin , Wang Senhu 
Published: June 2020

AbstractDespite ample research on the prevalence of specific psychiatric disorders during COVID-19, we know little about how the pandemic affects the general wellbeing of a wider population. The study investigates the prevalence and predictors of general psychiatric disorders measured by the 12-item General Health Questionnaire (GHQ-12) and frequency of loneliness during COVID-19 in the United Kingdom, a country heavily hit by the pandemic. We analyzed 15,530 respondents of the first large-scale, nationally representative survey of COVID-19 in a developed country, the first wave of Understanding Society COVID-19 Study. Results show that 29.2% of the respondents score 4 or more, the caseness threshold, on the general psychiatric disorder measure, and 35.86% of the respondents sometimes or often feel lonely. Regression analyses show that those who have or had COVID-19-related symptoms are more likely to develop general psychiatric disorders and are lonelier. Women and people in their 20s have higher risks of general psychiatric disorders and loneliness, while having a job and living with a partner are protective factors. This study showcases the general psychiatric disorders and loneliness of broader members of the society during COVID-19 and the underlying social disparities.
Cross-state variation in opioid use disorder among a privately insured nonelderly population in the United States
Authors: Jiang Bibo , Wang Li , Leslie Douglas 
Published: June 2020

AbstractBackgroundAlthough cross-state variation of the opioid epidemic in the United States are well documented in general, little are known about the epidemic in privately insured individuals.ObjectivesTo describe cross-state variation in Opioid Use Disorder (OUD) among privately insured individuals in the US for the years 2005-2015 and investigate demographic differences of OUD patients between a group of hard-hit states and the rest states.MethodsThe MarketScan® Commercial Claims and Encounters database was used to calculate prevalence of opioid use disorder for the 50 states in the US, respectively. We analyzed level and change of OUD prevalence in each state from 2005 to 2015 and identified the states which were affected most by the epidemic. One-sided exact fisher test was used to analyze demographic difference of the epidemic in the hard-hit states and the remaining states.ResultsCross-state variations of the opioid epidemic among privately insured population were substantial, both in terms of severity and acceleration of the epidemic. Demographic patterns of the epidemic were similar across states. The 18-34 age group was the most affected group with the highest prevalence. The 55-64 group experienced the most rapid increase of OUD prevalence, especially in states that suffered most in the epidemic.ConclusionsResults can assist policy makers to design better clinical and policy interventions on the opioid epidemic, especially on privately insured individuals. Drastic increase of OUD prevalence among the 55-64 group might indicate the need to improve prescription drug monitoring programs for chronic pain, especially in states more affected by the epidemic.
Group-level patterns emerge from individual speed as revealed by an extremely social robotic fish
Authors: Jolles Jolle W. , Weimar Nils , Landgraf Tim , Romanczuk Pawel , Krause Jens , Bierbach David 
Published: June 2020

AbstractUnderstanding the emergence of collective behaviour has long been a key research focus in the natural sciences. Besides the fundamental role of social interaction rules, a combination of theoretical and empirical work indicates individual speed may be a key process that drives the collective behaviour of animal groups. Socially-induced changes in speed by interacting animals make it difficult to isolate the effects of individual speed on group-level behaviours. Here we tackled this issue by pairing guppies with a biomimetic robot. We used a closed-loop tracking and feedback system to let a robotic fish naturally interact with a live partner in real time, and programmed it to strongly copy and follow its partner’s movements while lacking any preferred movement speed or directionality of its own. We show that individual differences in guppies’ movement speed were highly repeatable and shaped key collective patterns: higher individual speeds resulted in stronger leadership, lower cohesion, higher alignment, and better temporal coordination in the pairs. By combining the strengths of individual-based models and observational work with state-of-the-art robotics, we provide novel evidence that individual speed is a key, fundamental process in the emergence of collective behaviour.
Medial entorhinal spike clusters carry more finely tuned spatial information than single spikes
Authors: Quinlan Leo. Richard , Tyree Susan. Margot , Munn Robert. Gordon. Keith. 
Published: June 2020

AbstractMany cells within the entorhinal cortex (EC) fire relatively infrequently, with the majority of their spikes separated by many hundreds of milliseconds. However, most cells are seen to occasionally fire two, three, or more spikes in quick succession. Recent evidence has shown that, in EC grid cells, “burstier” cells; cells that fire more of their spikes in bursts, have more well defined spatial characteristics than cells that fire fewer bursts. However, there is evidence that the window for considering related spikes in MEC could be as long as 100ms. Here, we divide the spikes fired by single cells into single spikes and “clusters” of spikes occuring within 100ms. We show that these burst “clusters” of spikes fired by cells in MEC convey more finely tuned spatial and directional information than the numerically more common single spikes. In addition, we find that introducing environmental uncertainty decreases the ratio of clusters fired to single spikes. Most crucially, we find that although single spikes are less spatially precise than clusters, they are more temporally precise – these spikes are more closely entrained to LFP theta than clusters. These findings demonstrate that clusters of spikes in EC convey more specific information about space than single spikes, may reflect “certainty” about spatial position and direction, and may represent a different firing “mode” in which intraregional communication is less relevant than interregional traffic.
Intraspecific diversity loss in a predator species alters prey community structure and ecosystem functions
Authors: Raffard Allan , Cucherousset Julien , Montoya José M. , Richard Murielle , Acoca-Pidolle Samson , Poésy Camille , Garreau Alexandre , Santoul Frédéric , Blanchet Simon 
Published: June 2020

AbstractLoss in intraspecific diversity can alter ecosystem functions, but the underlying mechanisms are still elusive, and intraspecific biodiversity-ecosystem function relationships (iBEF) have been restrained to primary producers. Here, we manipulated genetic and functional richness of a fish consumer (Phoxinus phoxinus), to test whether iBEF relationships exist in consumer species, and whether they are more likely sustained by genetic or functional richness. We found that both genotypic and functional richness affected ecosystem functioning, either independently or in interaction. Loss in genotypic richness reduced benthic invertebrate diversity consistently across functional richness treatments, whereas it reduced zooplankton diversity only when functional richness was high. Finally, both losses in genotypic and functional richness altered essential functions (e.g. decomposition) through trophic cascades. We concluded that iBEF relationships lead to substantial top-down effects on entire food chains. The loss of genotypic richness impacted ecological properties as much as the loss of functional richness, probably because it sustains “cryptic” functional diversity.
Hijacking SARS-Cov-2/ACE2 receptor interaction by natural and semi-synthetic steroidal agents acting on functional pockets on receptor binding region
Authors: Carino Adriana , Moraca Federica , Fiorillo Bianca , Marchianò Silvia , Sepe Valentina , Biagioli Michele , Finamore Claudia , Bozza Silvia , Francisci Daniela , Distrutti Eleonora , Catalanotti Bruno , Zampella Angela , Fiorucci Stefano 
Published: June 2020

AbstractThe coronavirus disease 2019 (COVID-19) is a respiratory tract infection caused by the severe acute respiratory syndrome coronavirus (SARS)-CoV-2. In the light of the urgent need to identify novel approaches to be used in the emergency phase, a largely explored strategy has been the repurpose of clinically available drugs as new antivirals, by targeting different viral proteins. In this paper, we describe a drug repurposing strategy based on a virtual screening of druggable pockets located in the central β-sheet core of the SARS-CoV-2 Spike protein RBD supported by in vitro tests identifying several steroidal derivatives as SARS-CoV-2 entry inhibitors. Our results demonstrate that several potential binding sites exist in the SARS CoV-2 S protein, and that the occupancy of these pockets reduces the ability of the S protein RBD to bind to the ACE2 consensus in vitro. In particular, natural occurring and clinically available steroids as glycyrrhetinic and oleanolic acids, as well as the bile acids derivatives glyco-UDCA and obeticholic acid have been shown to be effective in preventing virus entry in the case of low viral load. All together, these results might help to define novel approaches to reduce the viral load by using SARS-CoV-2 entry inhibitors.
Evaluation of 30-day mortality for 500 patients undergoing non-emergency surgery in a COVID-19 cold site within a multicentre regional surgical network during the COVID-19 pandemic
Authors: Kasivisvanathan Veeru , Lindsay Jamie , Rakshani-Moghadam Sara , Elhamshary Ahmed , Kapriniotis Konstantinos , Kazantzis Georgios , Syed Bilal , Hines John , Bex Axel , Ho Daniel Heffernan , Hayward Martin , Bhan Chetan , MacDonald Nicola , Clarke Simon , Walker David , Bellingan Geoff , Moore James , Rohn Jennifer , Muneer Asif , Roberts Lois , Haddad Fares , Kelly John D ,   UCLH study group collaborators
Published: June 2020

AbstractBackgroundTwo million non-emergency surgeries are being cancelled globally every week due to the COVID-19 pandemic, which will have a major impact on patients and healthcare systems.ObjectiveTo determine whether it is feasible and safe to continue non-emergency surgery in the COVID-19 pandemicDesign, setting and participantsThis is a cohort study of 500 consecutive patients undergoing non-emergency surgery in a dedicated COVID-19 cold site following the first case of COVID-19 that was reported in the institution. The study was carried out during the peak of the pandemic in the United Kingdom, which currently has one of the highest number of cases and deaths from COVID-19 globally.We set up a hub-and-spoke surgical network amongst 14 National Health Service institutions during the pandemic. The hub was a cancer centre, which was converted into a COVID-19 cold site, performing urological, thoracic, gynaecological and general surgical operations.OutcomesThe primary outcome was 30-day mortality from COVID-19. Secondary outcomes included all-cause mortality and post-operative complications at 30-days.Results500 patients underwent surgery with median age 62.5 (IQR 51-71). 65% were male and 60% had a known diagnosis of cancer. 44% of surgeries were performed with robotic or laparoscopic assistance and 61% were considered complex or major operations.None of the 500 patients undergoing surgery died from COVID-19 at 30-days. 30-day allcause mortality was 3/500 (1%). 10 (2%) patients were diagnosed with COVID-19, 4 (1%) with confirmed laboratory diagnosis and 6 (1%) with probable COVID-19. 33/500 (7%) of patients developed Clavien-Dindo grade 3 or higher complications, with 1/33 (3%) occurring in a patient with COVID-19.ConclusionIt is safe to continue non-emergency surgery during the COVID-19 pandemic with appropriate service reconfiguration.Patient summaryNo patients died from COVID-19 when undergoing non-emergency surgery during the pandemic in one of the worst affected world regions.
Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns
Authors: Coleman Thomas S. 
Published: June 2020

AbstractFor COVID-19 the Infection Fatality Rate or IFR – a crucial variable in epidemiological modeling – is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.
A Sleep Disorder Detection Model based on EEG Cross-Frequency Coupling and Random Forest
Authors: Dimitriadis Stavros I. , Salis Christos I. , Liparas Dimitris 
Published: June 2020

AbstractSleep disorders are medical disorders of a subject’s sleep architecture and based on their severity, they can interfere with mental, emotional and physical functioning. The most common ones are insomnia, narcolepsy, sleep apnea, bruxism, etc. There is an increased risk of developing sleep disorders in elderly like insomnia, periodic leg movements, rapid eye movement (REM) behaviour disorders, sleep disorder breathing, etc. Consequently, their accurate diagnosis and classification are important steps towards an early stage treatment that could save the life of a patient. The Electroencephalographic (EEG) signal is the most sensitive and important biosignal, which is able to capture the brain sleep activity that is sensitive to sleep. In this study, we attempt to analyse EEG sleep activity via complementary cross-frequency coupling (CFC) estimates, which further feed a classifier, aiming to discriminate sleep disorders. We adopted an open EEG Database with recordings that were grouped into seven sleep disorders and a healthy control. The EEG brain activity from common sensors has been analysed with two basic types of cross-frequency coupling (CFC). Finally, a Random Forest (RF) classification model was built on CFC patterns, which were extracted from non-cyclic alternating pattern (CAP) epochs. Our RFCFC model achieved a 74% multiclass accuracy. Both types of CFC, phase-to-amplitude (PAC) and amplitude-amplitude coupling (AAC) patterns contribute to the accuracy of the RF model, thus supporting their complementary information. CFC patterns, in conjunction with the RF classifier proved a valuable biomarker for the classification of sleep disorders.
Meso-scale modeling of COVID-19 spatio-temporal outbreak dynamics in Germany
Authors: Kergaßner A. , Burkhardt C. , Lippold D. , Nistler S. , Kergaßner M. , Steinmann P. , Budday D. , Budday S. 
Published: June 2020

AbstractThe COVID-19 pandemic has kept the world in suspense for the past months. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions. However, this requires a deep understanding of the meso-scale outbreak dynamics between micro-scale agent models and macro-scale global models. Here, we introduce a reparameterized SIQRD network model that accounts for local political decisions to predict the spatio-temporal evolution of the pandemic in Germany at county and city resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert-Koch Institute, and predicts development for individual counties at convincing accuracy. We demonstrate the dominating effect of local infection seeds, and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward.
Identifying and Ranking Common COVID-19 Symptoms from Arabic Twitter
Authors: Alanazi Eisa , Alashaikh Abdulaziz , Alqurashi Sarah , Alanazi Aued 
Published: June 2020

AbstractBackgroundMassive amount of covid-19 related data is generated everyday by Twitter users. Self-reports of covid-19 symptoms on Twitter can reveal a great deal about the disease and its prevalence in the community. In particular, self-reports can be used as a valuable resource to learn more about the common symptoms and whether their order of appearance differs among different groups in the community. With sufficient available data, this has the potential of developing a covid-19 risk-assessment system that is tailored toward specific group of people.ObjectiveThe aim of this study is to identify the most common symptoms reported by covid-19 patients in the Arabic language and order the symptoms appearance based on the collected data.MethodsWe search the Arabic content of Twitter for personal reports of covid-19 symptoms from March 1st to May 27th, 2020. We identify 463 Arabic users who tweeted testing positive for covid-19 and extract the symptoms they publicly associate with covid-19. Furthermore, we ask them directly through personal messages to opt in and rank the appearance of the first three symptoms they experienced right before (or after) diagnosed with covid-19. Finally, we track their Twitter timeline to identify additional symptoms that were mentioned within ±5 days from the day of tweeting having covid-19. In summary, a list of 270 covid-19 reports were collected and symptoms were (at least partially) ranked from early to late.ResultsThe collected reports contained roughly 900 symptoms originated from 74% (n=201) male and 26% (n=69) female Twitter users. The majority (82%) of the tracked users were living in Saudi Arabia (46%) and Kuwait (36%). Furthermore, 13% (n=36) of the collected reports were asymptomatic. Out of the users with symptoms (n=234), 66% (n=180) provided a chronological order of appearance for at least three symptoms.Fever 59% (n=139), Headache 43% (n=101), and Anosmia 39% (n=91) were found to be the top three symptoms mentioned by the reports. They count also for the top-3 common first symptoms in a way that 28% (n=65) said their covid journey started with a Fever, 15% (n=34) with a Headache and 12% (n=28) with Anosmia. Out of the Saudi symptomatic reported cases (n=110), the most common three symptoms were Fever 59% (n=65), Anosmia 42% (n=46), and Headache 38% (n=42).ConclusionsThis study demonstrates that Twitter is a valuable resource to analyze and identify COVID-19 early symptoms within the Arabic content of Twitter. It also suggests the possibility of developing a real-time covid-19 risk estimator based on the users’ tweets.
On the sensitivity of non-pharmaceutical intervention models for SARS-CoV-2 spread estimation
Authors: Soltesz Kristian , Gustafsson Fredrik , Timpka Toomas , Jaldén Joakim , Jidling Carl , Heimerson Albin , Schön Thomas B. , Spreco Armin , Ekberg Joakim , Dahlström Örjan , Carlson Fredrik Bagge , Jöud Anna , Bernhardsson Bo 
Published: June 2020

AbstractIntroductionA series of modelling reports that quantify the effect of non-pharmaceutical interventions (NPIs) on the spread of the SARS-CoV-2 virus have been made available prior to external scientific peer-review. The aim of this study was to investigate the method used by the Imperial College COVID-19 Research Team (ICCRT) for estimation of NPI effects from the system theoretical viewpoint of model identifiability.MethodsAn input-sensitivity analysis was performed by running the original software code of the systems model that was devised to estimate the impact of NPIs on the reproduction number of the SARS-CoV-2 infection and presented online by ICCRT in Report 13 on March 30 2020. An empirical investigation was complemented by an analysis of practical parameter identifiability, using an estimation theoretical framework.ResultsDespite being simplistic with few free parameters, the system model was found to suffer from severe input sensitivities. Our analysis indicated that the model lacks practical parameter identifiability from data. The analysis also showed that this limitation is fundamental, and not something readily resolved should the model be driven with data of higher reliability.DiscussionReports based on system models have been instrumental to policymaking during the SARS-CoV-2 pandemic. With much at stake during all phases of a pandemic, we conclude that it is crucial to thoroughly scrutinise any SARS-CoV-2 effect analysis or prediction model prior to considering its use as decision support in policymaking. The enclosed example illustrates what such a review might reveal.