bluuebunny/crossref_metadata_2025_split huggingface dataset:
Covid-19 mortality rates in Northamptonshire UK: initial sub-regional comparisons and provisional SEIR model of disease spread
Authors: Petford Nick , Campbell Jackie 
Published: August 2020

AbstractObjectivesWe analysed mortality rates in a nonmetropolitan UK subregion (Northamptonshire) to understand SARSCoV2 disease fatalities at sub 1,000,000 population levels. A numerical (SEIR) model was then developed to predict the spread of Covid19 in Northamptonshire.MethodsA combined approach using statistically-weighted data to fit the start of the epidemic to the mortality record. Parameter estimates were then derived for the transmission rate and basic reproduction number.ResultsAge standardised mortality rates are highest in Northampton (urban) and lowest in semi-rural districts. Northamptonshire has a statistically higher Covid-19 mortality rate than for the East Midlands and England as a whole. Model outputs suggest the number of infected individuals exceed official estimates, meaning less than 40% of the population may require immunisation.ConclusionsCombining published (sub-regional) mortality rate data with deterministic models on disease spread has the potential to help public health practitioners develop bespoke mitigations, guided by local population demographics.
The Ontario Neurodegenerative Disease Research Initiative
Authors: Sunderland Kelly M. , Beaton Derek , Arnott Stephen R. , Kleinstiver Peter , Kwan Donna , Lawrence-Dewar Jane M. , Ramirez Joel , Tan Brian , Bartha Robert , Black Sandra E. , Borrie Michael , Brien Donald , Casaubon Leanne K. , Coe Brian C. , Cornish Benjamin , Dilliott Allison A. , Dowlatshahi Dar , Finger Elizabeth , Fischer Corinne , Frank Andrew , Fraser Julia , Freedman Morris , Greenberg Barry , Grimes David A. , Hassan Ayman , Hatch Wendy , Hegele Robert A. , Hudson Christopher , Jog Mandar , Kumar Sanjeev , Lang Anthony , Levine Brian , Lou Wendy , Mandzia Jennifer , Marras Connie , McIlroy William , Montero-Odasso Manuel , Munoz David G. , Munoz Douglas P. , Orange Joseph B. , Park David S. , Pasternak Stephen H. , Faria Frederico Pieruccini- , Rajji Tarek K. , Roberts Angela C. , Robinson John F. , Rogaeva Ekaterina , Sahlas Demetrios J. , Saposnik Gustavo , Scott Christopher J.M. , Seitz Dallas , Shoesmith Christen , Steeves Thomas D.L. , Strong Michael J. , Strother Stephen C. , Swartz Richard H. , Symons Sean , Tang-Wai David F. , Tartaglia Maria Carmela , Troyer Angela K. , Turnbull John , Zinman Lorne , McLaughlin Paula M. , Masellis Mario , Binns Malcolm A. 
Published: August 2020

AbstractObjectiveIn individuals over the age of 65, concomitant neurodegenerative pathologies contribute to cognitive and/or motor decline and can be aggravated by cerebrovascular disease, but our understanding of how these pathologies synergize to produce the decline represents an important knowledge gap. The Ontario Neurodegenerative Disease Research Initiative (ONDRI), a multi-site, longitudinal, observational cohort study, recruited participants across multiple prevalent neurodegenerative diseases and cerebrovascular disease, collecting a wide array of data and thus allowing for deep investigation into common and unique phenotypes. This paper describes baseline features of the ONDRI cohort, understanding of which is essential when conducting analyses or interpreting results.MethodsFive disease cohorts were recruited: Alzheimer’s disease/amnestic mild cognitive impairment (AD/MCI), amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), Parkinson’s disease (PD), and cerebrovascular disease (CVD). Assessment platforms included clinical, neuropsychology, eye tracking, gait and balance, neuroimaging, retinal imaging, genomics, and pathology. We describe recruitment, data collection, and data curation protocols, and provide a summary of ONDRI baseline characteristics.Results520 participants were enrolled. Most participants were in the early stages of disease progression. Participants had a median age of 69 years, a median Montreal Cognitive Assessment score of 25, a median percent of independence of 100 for basic activities of daily living, and a median of 93 for instrumental activities. Variation between disease cohorts existed for age, level of cognition, and geographic location.ConclusionONDRI data will enable exploration into unique and shared pathological mechanisms contributing to cognitive and motor decline across the spectrum of neurodegenerative diseases.
Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score
Authors: Knight Stephen R , Ho Antonia , Pius Riinu , Buchan Iain , Carson Gail , Drake Thomas M , Dunning Jake , Fairfield Cameron J , Gamble Carrol , Green Christopher A , Gupta Rishi , Halpin Sophie , Hardwick Hayley E , Holden Karl A , Horby Peter W , Jackson Clare , Mclean Kenneth A , Merson Laura , Nguyen-Van-Tam Jonathan S , Norman Lisa , Noursadeghi Mahdad , Olliaro Piero L , Pritchard Mark G , Russell Clark D , Shaw Catherine A , Sheikh Aziz , Solomon Tom , Sudlow Cathie , Swann Olivia V , Turtle Lance CW , Openshaw Peter JM , Baillie J Kenneth , Semple Malcolm G , Docherty Annemarie B , Harrison Ewen M 
Published: August 2020

AbstractObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19.DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020.Setting260 hospitals across England, Scotland, and Wales.ParticipantsAdult patients (≥18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction.Main outcome measuresIn-hospital mortality.ResultsThere were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 − 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score ≥15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score ≤3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73).ConclusionsWe have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic.Study registrationISRCTN66726260
The integrated approach of learning tuberculosis transmission within and outside households via random directed graph models
Authors: Li Tenglong , Jones-L□pez Edward C. , White Laura F. 
Published: August 2020

SummaryHousehold contact studies are frequently used in tuberculosis transmission research, and models based on them often focus on transmission within the household. This contradicts recent research which suggests the transmission may be more likely to happen outside the household than within the household in high burden settings where these studies are frequently conducted. Consequently, most models would lead to biased estimates and misleading public health interventions. There is a strong need for developing models that allow concurrent estimation of household and extra-household transmission. In this study, we develop a random directed graph model for tuberculosis transmission, which permits users to concurrently build models for both household and extra-household transmission. Furthermore, our model can estimate the relative frequency of household transmission versus extra-household transmission and consistently produce unbiased estimates for risk factors, regardless of whether community controls are available. We illustrate our approach with a household contact study conducted in Vitória, Brazil, and our results indicate that extra-household transmission can account for 63% to 98% of M. tuberculosis infections detected during such a study.
Kinetics of SARS-CoV-2 Antibody Avidity Maturation and Association with Disease Severity
Authors: Luo Yiqi Ruben , Chakraborty Indrani , Yun Cassandra , Wu Alan H.B. , Lynch Kara L. 
Published: August 2020

AbstractThe kinetics of IgG avidity maturation during SARS-CoV-2 infection was studied. The IgG avidity assay used a novel label-free immunoassay technology. It was found that there was a strong correlation between IgG avidity and days since symptom onset, and peak readings were significantly higher in severe than mild disease cases.
Data-driven modeling and forecasting of COVID-19 outbreak for public policy making
Authors: Hasan A. , Putri E.R.M. , Susanto H. , Nuraini N. 
Published: August 2020

AbstractThis paper presents a data-driven approach for COVID-19 outbreak modeling and forecasting, which can be used by public policy and decision makers to control the outbreak through Non-Pharmaceutical Interventions (NPI). First, we apply an extended Kalman filter (EKF) to a discrete-time stochastic augmented compartmental model to estimate the time-varying effective reproduction number ℛt. We use daily confirmed cases, active cases, recovered cases, deceased cases, Case-Fatality-Rate (CFR), and infectious time as inputs for the model. Furthermore, we define a Transmission Index (TI) as a ratio between the instantaneous and the maximum value of the effective reproduction number. The value of TI shows the disease transmission in a contact between a susceptible and an infectious individual due to current measures such as physical distancing and lock-down relative to a normal condition. Based on the value of TI, we forecast different scenarios to see the effect of relaxing and tightening public measures. Case studies in three countries are provided to show the practicability of our approach.
Visuospatial attention revamps cortical processing of sound: restrict stimulus uncertainty
Authors: Cervantes Constantino F. , Sánchez-Costa T. , Cipriani G. A. , Carboni A. 
Published: August 2020

AbstractSelective attentional biases arising from one sensory modality may manifest in another. The effects of visuospatial attention, often considered a foundation for visual object perception, are unclear in the auditory domain during audiovisual (AV) scene processing. This study investigates temporal and spatial factors that facilitate such cross-modal bias transfer at the neural level. Auditory encoding of random tone pips in AV scenes was investigated via a temporal response function model (TRF) of the participants’ electroencephalogram (N=30). The spatially uninformative pips were associated with spatially distributed visual contrast reversals (‘flips’) through asynchronous, probabilistic AV temporal onset distributions. Participants deployed visuospatial selection on these AV stimuli to perform a task. A late (~300 ms) cross-modal transfer of the unimodal attentional bias was found on the neural representation of pips. Transfer depended on the selected visual input being (i) presented during or shortly after a related sound in a relatively limited temporal window (<165 ms); and (ii) positioned across limited (1:4) visual foreground to background ratios. In addition, the magnitude of attentional enhancement was proportional to the proximity of flips to the foreground area. The results indicate that ongoing neural representations of sounds can incorporate relevant visuospatial attributes for auditory stream segregation.
Hybrid capture-based sequencing enables unbiased recovery of SAR-CoV-2 genomes from fecal samples and characterization of the dynamics of intra-host variants
Authors: Xu Yi , Kang Lu , Shen Zijie , Li Xufang , Wu Weili , Ma Wentai , Fang Chunxiao , Yang Fengxia , Jiang Xuan , Gong Sitang , Zhang Li , Li Mingkun 
Published: August 2020

AbstractBackgroundIn response to the current COVID-19 pandemic, it is crucial to understand the origin, transmission, and evolution of SARS-CoV-2, which relies on close surveillance of genomic diversity in clinical samples. Although the mutation at the population level had been extensively investigated, how the mutations evolve at the individual level is largely unknown, partly due to the difficulty of obtaining unbiased genome coverage of SARS-CoV-2 directly from clinical samples.MethodsEighteen time series fecal samples were collected from nine COVID-19 patients during the convalescent phase. The nucleic acids of SARS-CoV-2 were enriched by the hybrid capture method with different rounds of hybridization.ResultsBy examining the sequencing depth, genome coverage, and allele frequency change, we demonstrated the impeccable performance of the hybrid capture method in samples with Ct value < 34, as well as significant improvement comparing to direct metatranscriptomic sequencing in samples with lower viral loads. We identified 229 intra-host variants at 182 sites in 18 fecal samples. Among them, nineteen variants presented frequency changes > 0.3 within 1-5 days, reflecting highly dynamic intra-host viral populations. Meanwhile, we also found that the same mutation showed different frequency changes in different individuals, indicating a strong random drift. Moreover, the evolving of the viral genome demonstrated that the virus was still viable in the gastrointestinal tract during the convalescent period.ConclusionsThe hybrid capture method enables reliable analyses of inter- and intra-host variants of SARS-CoV-2 genome, which changed dramatically in the gastrointestinal tract; its clinical relevance warrants further investigation.
Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy
Authors: Barone Sierra M. , Paul Alberta G.A. , Muehling Lyndsey M. , Lannigan Joanne A. , Kwok William W. , Turner Ronald B. , Woodfolk Judith A. , Irish Jonathan M. 
Published: August 2020

AbstractFor an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitatively characterize cells associated with disease progression or clinical response. With repeated sampling, immune monitoring creates a real-time portrait of the cells reacting to a novel virus before disease specific knowledge and tools are established. However, single cell analysis tools can struggle to reveal rare cells that are under 0.1% of the population. Here, the machine learning workflow Tracking Responders Expanding (T-REX) was created to identify changes in both very rare and common cells in diverse human immune monitoring settings. T-REX identified cells that were highly similar in phenotype and localized to hotspots of significant change during rhinovirus and SARS-CoV-2 infections. Specialized reagents used to detect the rhinovirus-specific CD4+cells, MHCII tetramers, were not used during unsupervised analysis and instead ‘left out’ to serve as a test of whether T-REX identified biologically significant cells. In the rhinovirus challenge study, T-REX identified virus-specific CD4+T cells based on these cells being a distinct phenotype that expanded by ≥95% following infection. T-REX successfully identified hotspots containing virus-specific T cells using pairs of samples comparing Day 7 of infection to samples taken either prior to infection (Day 0) or after clearing the infection (Day 28). Mapping pairwise comparisons in samples according to both the direction and degree of change provided a framework to compare systems level immune changes during infectious disease or therapy response. This revealed that the magnitude and direction of systemic immune change in some COVID-19 patients was comparable to that of blast crisis acute myeloid leukemia patients undergoing induction chemotherapy and characterized the identity of the immune cells that changed the most. Other COVID-19 patients instead matched an immune trajectory like that of individuals with rhinovirus infection or melanoma patients receiving checkpoint inhibitor therapy. T-REX analysis of paired blood samples provides an approach to rapidly identify and characterize mechanistically significant cells and to place emerging diseases into a systems immunology context.
Specific mutations in genes responsible for Alzheimer and for Duchenne Muscular Dystrophy introduced by Base editing and PRIME editing
Authors: Rousseau Joël , Mbakam Cédric Happi , Guyon Antoine , Tremblay Guillaume , Begin Francis Gabriel , Tremblay Jacques P. 
Published: August 2020

ABSTRACTBase editing technique and PRIME editing techniques derived from the CRISPR/Cas9 discovery permit to modify selected nucleotides. We initially used the base editing technique to introduce in theAPPgene the A673T mutation, which prevents the development of Alzheimer’s disease. Although the desired cytidine to thymidine mutation was inserted in up to 17% of theAPPgene in HEK393T, there were also modifications of up to 20% of other nearby cytidines. More specific mutations of theAPPgene were obtained with the PRIME editing technique. However, the best percentage of mutations was only 5.8%. The efficiency of the PRIME editing treatment was initially tested on theEMX1gene. A single treatment produced the desired modification in 36% of theEMX1gene. Three consecutive treatments increased the percentage of mutations to 50%. The PRIME editing technique was also used to insert specific point mutations in exons 9 and 35 of theDMDgene coding for the dystrophin gene and which is mutated in Duchenne Muscular Dystrophy (DMD). Up to 10% desired mutations of theDMDgene were obtained. Three repeated treatments increased the percentage of specific mutations to 16%. Given that there are thousands of nuclei inside a human muscle fiber and that the dystrophin nuclear domain is about 500 μm, this level of modifications would be sufficient to produce a phenotype improvement in DMD patients.
Developmental Incongruity as a Dynamical Representation of Heterochrony
Authors: Alicea Bradly 
Published: August 2020

AbstractThe theory of heterochrony provides us with a generalized quantitative perspective on the dynamics of developmental trajectories. While useful, these linear developmental trajectories merely characterize changes in the speed and extent of growth in developmental time. One open problem in the literature involves how to characterize developmental trajectories for rare and incongruous modes of development. By combining nonlinear mathematical representations of development with models of gene expression networks (GRNs), the dynamics of growth given the plasticity and complexity of developmental timing are revealed. The approach presented here characterizes heterochrony as a dynamical system, while also proposing a computational motif in GRNs called triangular state machines (TSMs). TSMs enable local computation of phenotypic enhancement by producing nonlinear and potentially unexpected outputs. With a focus on developmental timing and a focus on sequential patterns of growth, formal techniques are developed to characterize delays and bifurcations in the developmental trajectory. More generally, growth is demonstrated using two conceptual models: a Galton board representing axial symmetry and a radial tree depicting differential growth. These techniques take into consideration the existence of multiple developmental genotypes operating in parallel, which ultimately characterize the exquisite phenotypic diversity observed in animal development.
The cooperative assembly of shelterin bridge provides a kinetic gateway that controls telomere length homeostasis
Authors: Liu Jinqiang , Hu Xichan , Bao Kehan , Kim Jin-Kwang , Jia Songtao , Qiao Feng 
Published: August 2020

AbstractShelterin is a six-proteins complex that coats chromosome ends to ensure their proper protection and maintenance. Similar to the human shelterin, fission yeast shelterin is composed of telomeric double- and single-stranded DNA-binding proteins, Taz1 and Pot1, respectively, bridged by Rap1, Poz1, and Tpz1. The assembly of the proteinaceous Tpz1-Poz1-Rap1 complex occurs cooperatively and disruption of this shelterin bridge leads to unregulated telomere elongation. However, how this biophysical property of bridge assembly is integrated into shelterin function is not known. Here, utilizing synthetic bridges with a range of binding properties, we find that synthetic shelterin bridge lacking cooperativity requires a linker pair that matches the native bridge in complex lifespan but has dramatically higher affinity. We find that cooperative assembly confers kinetic properties on the shelterin bridge allowing disassembly to function as a molecular timer, regulating the duration of the telomere open state, and consequently telomere lengthening to achieve a defined species-specific length range.
Minicells as a potential chassis for engineering lineage-agnostic organisms
Authors: Wei Eric , Jackson-Smith Anton , Endy Drew 
Published: August 2020

ABSTRACTBackgroundGenomes encode for organisms and thus genome synthesis implies the possibility of organismal synthesis, including the synthesis of organisms without constraint to lineage. Current genome-scale engineering projects are focused on minimization, refactoring, or recoding within the context of existing natural lineages. Minicells arise naturally as anucleate cells that are devoid of heritable genetic material but are capable of gene expression. Thus, minicells may serve as a useful starting point for developing lineage-agnostic organisms encoded by newly-designed synthetic genomes. However, the composition and expression capacity of minicells is fixed at the time of their formation. The possibility of reestablishing cellular growth and division starting from minicells and entirely heterologous synthetic genomes is unknown.ResultsWe observed expression and segregation of functional proteins among mixed populations of reproducing cells and so-derived anucleate minicells via fluorescence microscopy. By adapting and integrating established methods of preparation and purification we were able to isolate minicells from a growing population of progenitor cells with a purity of at least 500 minicells per progenitor. We then used heterologous expression of plasmid-encoded green fluorescent protein to estimate the absolute expression capacity of minicells. We found that minicells can support the formation of 4.9 ± 4.6 × 108peptide bonds prior to exhausting their initial intrinsic expression capacity.ConclusionsMinicells can be produced in large numbers with high purity and can also harbor and express engineered plasmids. The observed variation in minicell gene expression capacity suggests that about 13% of gene-expressing minicells can support the formation of more than one-billion peptide bonds, an amount sufficient to replicate known prokaryotic proteomes. Stated differently, while most minicells would require a sophisticated genetic ‘boot’ program to first increase minicell-specific expression capacity sufficient to instantiate newly reproducing lineages, a subset of minicells may be able to directly support whole genome, lineage-agnostic organism engineering.