bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinguish Coronavirus Disease 2019 Patients in General Surgery Emergency by CIAAD Scale: Development and Validation of a Prediction Model Based on 822 Cases in China
Authors: Zhao Bangbo , Wei Yingxin , Sun Wenwu , Qin Cheng , Zhou Xingtong , Wang Zihao , Li Tianhao , Cao Hongtao , Wang Weibin , Wang Yujun 
Published: April 2020

ABATRACTIMPORTANCEIn the epidemic, surgeons cannot distinguish infectious acute abdomen patients suspected COVID-19 quickly and effectively.OBJECTIVETo develop and validate a predication model, presented as nomogram and scale, to distinguish infectious acute abdomen patients suspected coronavirus disease 2019 (COVID-19).DESIGNDiagnostic model based on retrospective case series.SETTINGTwo hospitals in Wuhan and Beijing, China.PTRTICIPANTS584 patients admitted to hospital with laboratory confirmed SARS-CoV-2 from 2 Jan 2020 to15 Feb 2020 and 238 infectious acute abdomen patients receiving emergency operation from 28 Feb 2019 to 3 Apr 2020.METHODSLASSO regression and multivariable logistic regression analysis were conducted to develop the prediction model in training cohort. The performance of the nomogram was evaluated by calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA) and clinical impact curves in training and validation cohort. A simplified screening scale and managing algorithm was generated according to the nomogram.RESULTSSix potential COVID-19 prediction variables were selected and the variable abdominal pain was excluded for overmuch weight. The five potential predictors, including fever, chest computed tomography (CT), leukocytes (white blood cells, WBC), C-reactive protein (CRP) and procalcitonin (PCT), were all independent predictors in multivariable logistic regression analysis (p ≤0.001) and the nomogram, named COVID-19 Infectious Acute Abdomen Distinguishment (CIAAD) nomogram, was generated. The CIAAD nomogram showed good discrimination and calibration (C-index of 0.981 (95% CI, 0.963 to 0.999) and AUC of 0.970 (95% CI, 0.961 to 0.982)), which was validated in the validation cohort (C-index of 0.966 (95% CI, 0.960 to 0.972) and AUC of 0.966 (95% CI, 0.957 to 0.975)). Decision curve analysis revealed that the CIAAD nomogram was clinically useful. The nomogram was further simplified into the CIAAD scale.CONCLUSIONSWe established an easy and effective screening model and scale for surgeons in emergency department to distinguish COVID-19 patients from infectious acute abdomen patients. The algorithm based on CIAAD scale will help surgeons manage infectious acute abdomen patients suspected COVID-19 more efficiently.
Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions
Authors: Linka Kevin , Peirlinck Mathias , Costabal Francisco Sahli , Kuhl Ellen 
Published: April 2020

ABSTRACTFor the first time in history, on March 17,2020, the European Union closed all its external borders to contain the spreading of the coronavirus 2019, COVID-19. Throughout two past months, governments around the world have implemented massive travel restrictions and border control to mitigate the outbreak of this global pandemic. However, the precise effects of travel restrictions on the outbreak dynamics of COVID-19 remain unknown. Here we combine a global network mobility model with a local epidemiology model to simulate and predict the outbreak dynamics and outbreak control of COVID-19 across Europe. We correlate our mobility model to passenger air travel statistics and calibrate our epidemiology model using the number of reported COVID-19 cases for each country. Our simulations show that mobility networks of air travel can predict the emerging global diffusion pattern of a pandemic at the early stages of the outbreak. Our results suggest that an unconstrained mobility would have significantly accelerated the spreading of COVID-19, especially in Central Europe, Spain, and France. Ultimately, our network epidemiology model can inform political decision making and help identify exit strategies from current travel restrictions and total lockdown.
Abnormal AMPAR-mediated synaptic plasticity, cognitive and autistic-like behaviors in a missenseFmr1mutant mouse model of Fragile X syndrome
Authors: Prieto Marta , Folci Alessandra , Poupon Gwénola , Schiavi Sara , Buzzelli Valeria , Pronot Marie , François Urielle , Pousinha Paula , Lattuada Norma , Abelanet Sophie , Castagnola Sara , Chafai Magda , Khayachi Anouar , Gwizdek Carole , Brau Frédéric , Deval Emmanuel , Francolini Maura , Bardoni Barbara , Humeau Yann , Trezza Viviana , Martin Stéphane 
Published: April 2020

AbstractFragile X syndrome (FXS) is the most frequent form of inherited intellectual disability and the best-described monogenic cause of autism. FXS is usually caused by a CGG-repeat expansion in theFMR1gene leading to its silencing and the loss-of-expression of the Fragile X Mental Retardation Protein (FMRP). Missense mutations were also identified in FXS patients, including the recurrent FMRP-R138Q mutation. To investigate the mechanisms underlying FXS in these patients, we generated a knock-in mouse model(Fmr1R138Q)expressing the FMRP-R138Q protein. We demonstrate that theFmr1R138Qhippocampus has an increased spine density associated with postsynaptic ultrastructural defects and increased AMPA receptor surface expression. Combining biochemical assays, high-resolution imaging and electrophysiological recordings, we also show that the mutation impairs the hippocampal long-term potentiation (LTP) and leads to socio-cognitive deficits inFmr1R138Qmice. These findings reveal that the R138Q mutation impacts the synaptic functions of FMRP and highlight potential mechanisms causing FXS in FMRP-R138Q patients.
Epidemiological impact of SARS-CoV-2 vaccination: mathematical modeling analyses
Authors: Makhoul Monia , Ayoub Houssein H. , Chemaitelly Hiam , Seedat Shaheen , Mumtaz Ghina R , Al-Omari Sarah , Abu-Raddad Laith J. 
Published: April 2020

AbstractBackgroundSeveral SARS-CoV-2 vaccine candidates are currently in the pipeline. This study aims to inform SARS-CoV-2 vaccine development, licensure, decision-making, and implementation by determining key preferred vaccine product characteristics and associated population-level impact.MethodsVaccination impact was assessed at various efficacies using an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression, with application for China.ResultsA prophylactic vaccine with efficacy against acquisition (VES) of ≥70% is needed to eliminate this infection. A vaccine withVES<70% will still have a major impact, and may control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, or alternatively if supplemented with a moderate social-distancing intervention (<20% reduction in contact rate), or complemented with herd immunity. Vaccination is cost-effective. For a vaccine withVESof 50%, number of vaccinations needed to avert one infection is only 2.4, one severe disease case is 25.5, one critical disease case is 33.2, and one death is 65.1. Gains in effectiveness are achieved by initially prioritizing those ≥60 years. Probability of a major outbreak is virtually zero with a vaccine withVES≥70%, regardless of number of virus introductions. Yet, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact.ConclusionsEven a partially-efficacious vaccine can offer a fundamental solution to control SARS-CoV-2 infection and at high cost-effectiveness. In addition to the primary endpoint on infection acquisition, developers should assess natural history and disease progression outcomes and/or proxy biomarkers, since such secondary endpoints may prove critical in licensure, decision-making, and vaccine impact.
Optimizing COVID-19 surveillance in long-term care facilities: a modelling study
Authors: Smith David RM , Duval Audrey , Pouwels Koen B , Guillemot Didier , Fernandes Jérôme , Huynh Bich-Tram , Temime Laura , Opatowski Lulla 
Published: April 2020

ABSTRACTBackgroundLong-term care facilities (LTCFs) are vulnerable to COVID-19 outbreaks. Timely epidemiological surveillance is essential for outbreak response, but is complicated by a high proportion of silent (non-symptomatic) infections and limited testing resources.MethodsWe used a stochastic, individual-based model to simulate SARS-CoV-2 transmission along detailed inter-individual contact networks describing patient-staff interactions in real LTCF settings. We distributed nasopharyngeal swabs and RT-PCR tests using clinical and demographic indications, and evaluated the efficacy and resource-efficiency of a range of surveillance strategies, including group testing (sample pooling) and testing cascades, which couple (i) testing for multiple indications (symptoms, admission) with (ii) random daily testing.ResultsIn the baseline scenario, randomly introducing SARS-CoV-2 into a 170-bed LTCF led to large outbreaks, with a cumulative 86 (6-224) infections after three weeks of unmitigated transmission. Efficacy of symptom-based screening was limited by (i) lags between infection and symptom onset, and (ii) silent transmission from asymptomatic and pre-symptomatic infections. Testing upon admission detected up to 66% of patients silently infected upon LTCF entry, but missed potential introductions from staff. Random daily testing was more effective when targeting patients than staff, but was overall an inefficient use of limited resources. At high testing capacity (>1 test/10 beds/day), cascades were most effective, with a 22-52% probability of detecting outbreaks prior to any nosocomial transmission, and 38-63% prior to first onset of COVID-19 symptoms. Conversely, at low capacity (<1 test/85 beds/day), pooling randomly selected patients in a daily group test was most effective (9-15% probability of detecting outbreaks prior to transmission; 30-44% prior to symptoms). The most efficient strategy compared to the reference was to pool individuals with any COVID-like symptoms, requiring only 5-7 additional tests and 17-24 additional swabs to detect outbreaks 5-6 days earlier, prior to an additional 14-18 infections.ConclusionsGroup testing is an effective and efficient COVID-19 surveillance strategy for resource-limited LTCFs. Cascades are even more effective given ample testing resources. Increasing testing capacity and updating surveillance protocols accordingly could facilitate earlier detection of emerging outbreaks, informing a need for urgent intervention in settings with ongoing nosocomial transmission.
Potential magnitude of COVID-19-induced healthcare resource depletion in Ontario, Canada
Authors: Barrett Kali , Khan Yasin A. , Mac Stephen , Ximenes Raphael , Naimark David MJ , Sander Beate 
Published: April 2020

ABSTRACTBackgroundThe global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing significant strain to healthcare systems. The purpose of our study is to predict the impact of the COVID-19 pandemic on patient outcomes and the healthcare system in Ontario, Canada.MethodsWe developed an individual-level simulation to model the flow of COVID-19 patients through the Ontario healthcare system. We simulated different combined scenarios of epidemic trajectory and healthcare capacity. Outcomes include numbers of patients needing admission to the ward, Intensive Care Unit (ICU), and requiring ventilation; days to resource depletion; and numbers of patients awaiting resources and deaths associated with limited access to resources.FindingsWe demonstrate that with effective early public health measures system resources need not be depleted. For scenarios considering late or ineffective implementation of physical distancing, health system resources would be depleted within 14-26 days. Resource depletion was also avoided or delayed with aggressive measures to rapidly increase ICU, ventilator, and acute care hospital capacity.InterpretationWe found that without aggressive physical distancing measures the Ontario healthcare system would have been inadequately equipped to manage the expected number of patients with COVID-19, despite the rapid capacity increase. This overall lack of resources would have led to an increase in mortality. By slowing the spread of the disease via ongoing public health measures and having increased healthcare capacity, Ontario may have avoided catastrophic stresses to its health care system.
A Bayesian analysis of the total number of cases of the COVID 19 when only a few data is available. A case study in the state of Goias, Brazil
Authors: Silva Renato Rodrigues , Velasco Wisley Donizetti , Silva Marques Wanderson da , Gonçalves Tibiriçá Carlos Augusto 
Published: April 2020

AbstractThe outbreak of COVID 19 has been provoking several problems to the health system around the world. One of the concerning is the crash of the health system due to the increasing demand suddenly. To avoid it, knowing the total number and daily new cases is crucial. In this study, we fitted curves growth models using a Bayesian approach. We extracted information obtained from some countries to build the prior distribution of the model. The total number of cases of the COVID 19 in the state of Goias was analyzed. Results from analysis indicated that the date of the outbreak peak is between 51 and 68 days after the beginning. Moreover, the total number of cases is around 3180 cases. The analysis did not take into consideration possibles changes in government control measures. We hope this study can provide some valuable information to public health management.
Seasonality and uncertainty in COVID-19 growth rates
Authors: Merow Cory , Urban Mark C. 
Published: April 2020

AbstractThe virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown if summer weather will reduce its continued spread, thereby alleviating strains on hospitals and providing time for vaccine development. Early insights from laboratory studies of related coronaviruses predicted that COVID-19 would decline at higher temperatures, humidity, and ultraviolet light. Using current, fine-scaled weather data and global reports of infection we developed a model that explained 36% of variation in early growth rates before intervention, with 17% based on weather or demography and 19% based on country-specific effects. We found that ultraviolet light was most strongly associated with lower COVID-19 growth rates. Projections suggest that, in the absence of intervention, COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. However, uncertainty remains high and the probability of a weekly doubling rate remained >20% throughout the summer in the absence of control. Consequently, aggressive policy interventions will likely be needed in spite of seasonal trends.
Spectral DQE of the Volta Phase Plate
Authors: Buijsse Bart , Trompenaars Piet , Altin Veli , Danev Radostin , Glaeser Robert M. 
Published: April 2020

ABSTRACTThe Volta Phase Plate (VPP) consists of a heated, thin film that is placed in the same plane as the focused diffraction pattern of an electron microscope. A change in surface potential develops at the point irradiated by the intense, unscattered electron beam, and this altered surface potential produces, in turn, a phase shift between the unscattered and scattered parts of the electron wave. While the VPP thus increases the image contrast for weak-phase objects at low spatial frequencies, we report here that it also leads to the loss of an increasing fraction of the signal at higher resolution. The approximately linear dependence (with increasing resolution) of this loss has been quantified at 200 kV and 300 kV, using evaporated-carbon films of different thicknesses as Volta phase plates. In all cases, the loss of signal remains almost independent of variation of the conditions and parameters that were tested. In spite of having done a number or additional, discovery-based experiments, the cause of this loss of signal remains unexplained at this point.
Probing the structure-function relationship with neural networks constructed by solving a system of linear equations
Authors: Mininni Camilo J. , Zanutto B. Silvano 
Published: April 2020

AbstractNeural network models are an invaluable tool to understand brain function, since they allow to connect the cellular and circuit levels with behaviour. Neural networks usually comprise a huge number of parameters, which must be chosen carefully such that networks reproduce anatomical, behavioural and neurophysiological data. These parameters are usually fitted with off-the-shelf optimization algorithms that iteratively change network parameters and simulate the network to evaluate the changes and improve fitting. Here we propose to invert the fitting process by proceeding from the network dynamics towards network parameters. Firing state transitions are chosen according to the transition graph followed by an agent when solving a given behavioural task. Then, a system of linear equations is constructed from the network firing states and membrane potentials, in such a way that system consistency in guarantee. This allows to uncouple the activity features of the model, like its neurons firing rate and correlation, from the connectivity features and from the task-solving algorithm implemented by the network, allowing to fit these three levels separately. We employed the method to probe the structure-function relationship in a stimuli sequence memory task, finding solution networks where commonly employed optimization algorithms failed. The constructed networks showed reciprocity and correlated firing patterns that recapitulated experimental observations. We argue that the proposed method is a complementary and needed alternative to the way neural networks are constructed to model brain function.
Complementation can maintain a quasispecies of drug sensitive and resistant HIV
Authors: Jackson Laurelle , Cele Sandile , Lustig Gila , Giandhari Jennifer , de Oliveira Tulio , Neher Richard A. , Sigal Alex 
Published: April 2020

AbstractHIV exists as multiple genotypes in a single infected individual referred to as a quasispecies. Here we reproduced a quasispecies by moderate selective pressure using an HIV reverse transcriptase inhibitor. The drug resistant genotype never completely supplanted the drug sensitive genotype, which stabilized at about 20 percent of viral sequences. Single-cell sequencing showed that resistant genotype frequency plateaued when cells were co-infected with sensitive and resistant genotypes, suggesting a sharing of viral proteins in co-infected cells (complementation) which masks genotypic differences. To test if complementation can confer phenotypic drug resistance, we co-transfected fluorescently labelled molecular clones of sensitive and resistant HIV and observed that genotypically sensitive virus from co-transfected cells was drug resistant. Resistant virus preferentially infected cells in tandem with drug sensitive HIV, explaining how co-infections of sensitive and resistant genotypes were initiated. Modelling this effect, we observed that a stable quasispecies could form at the experimental multiplicities of infection for the drug resistant and drug sensitive virus, showing that complementation can lead to a quasispecies in an HIV evolution experiment.
A reduced order model of the spine to study pediatric scoliosis
Authors: Neelakantan Sunder , Purohit Prashant K. , Pasha Saba 
Published: April 2020

AbstractThe S-shaped curvature of the spine has been hypothesized as the underlying mechanical cause of adolescent idiopathic scoliosis. In earlier work we proposed a reduced order model in which the spine was viewed as an S-shaped elastic rod under torsion and bending. Here, we simulate the deformation of S-shaped rods of a wide range of curvatures and inflection points under a fixed mechanical loading. Our analysis determines three distinct axial projection patterns of these S-shaped rods: two loop (in opposite directions) patterns and one lemniscate pattern. We further identify the curve characteristics associated with each deformation pattern showing that for rods deforming in a loop 1 shape the position of the inflection point is the highest and the curvature of the rod is smaller compared to the other two types. For rods deforming in the loop 2 shape the position of the inflection point is the lowest (closer to the fixed base) and the curvatures are higher than the other two types. These patterns matched the common clinically observed scoliotic curves - Lenke 1 and Lenke 5. Our elastic rod model predicts deformations that are similar to those of a pediatric spine and it can differentiate between the clinically observed deformation patterns. This provides validation to the hypothesis that changes in the sagittal profile of the spine can be a mechanical factor in parthenogenesis of pediatric idiopathic scoliosis.
Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain
Authors: Kumar Sreejan , Ellis Cameron T. , O’Connell Thomas , Chun Marvin M , Turk-Browne Nicholas B. 
Published: April 2020

AbstractThe extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model are more widely distributed across the brain than previously acknowledged. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.