bluuebunny/crossref_metadata_2025_split huggingface dataset:
A rapid, cost efficient and simple method to identify current SARS-CoV-2 variants of concern by Sanger sequencing part of the spike protein gene
Authors: Jørgensen Tue Sparholt , Blin Kai , Kuntke Franziska , Salling Henrik K. , Michaelsen Thomas Y , Albertsen Mads , Larsen Helene 
Published: March 2021

AbstractIn 2020, the novel coronavirus, SARS-CoV-2, caused a pandemic, which is still raging at the time of writing this. Many countries have set up high throughput RT-qPCR based diagnostics for people with COVID-19 symptoms and for the wider population. In addition, with the use of whole genome sequencing (WGS) new lineages of SARS-CoV-2 have been identified that have been associated with increased transmissibility or altered vaccine efficacy, so-called Variants of Concern (VoC). WGS is generally too labor intensive and expensive to be applied to all positive samples from the diagnostic tests, and often has a turnaround time too long to enable VoC focused contact tracing. Here, we propose to use Sanger sequencing for the detection of common variants of concern and key mutations in early 2021, using a single set of the recognized ARTIC Network primers. The proposed setup relies entirely on materials and methods already in use in diagnostic RT-qPCR labs and on existing infrastructure from companies that have specialized in cheap and rapid turnaround Sanger sequencing. In addition, we provide an automated mutation calling software (https://github.com/kblin/covid-spike-classification). We have validated the setup on 195 SARS-CoV-2 positive samples, and we were able to profile >85% of RT-qPCR positive samples, where the last 15% largely stem from samples with low viral count. At approximately 4€ per sample in material cost, with minimal hands-on time, little data handling, and a turnaround time of less than 30 hours, the setup is simple enough to be implemented in any SARS-CoV-2 RT-qPCR diagnostic lab. Our protocol provides results that can be used to focus contact-tracing efforts and it is cheap enough for the tracking and surveillance of all positive samples for emerging variants such as B.1.1.7, B.1.351 and P.1 as of January 2021.
Circulating interleukin-6 levels and incident ischemic stroke: a systematic review and meta-analysis of population-based cohort studies
Authors: Papadopoulos Andreas , Palaiopanos Konstantinos , Björkbacka Harry , Peters Annette , de Lemos James A. , Seshadri Sudha , Dichgans Martin , Georgakis Marios K. 
Published: March 2021

ABSTRACTObjectiveTo determine the association between circulating interleukin-6 (IL-6) levels and risk of incident ischemic stroke in the general population.MethodsFollowing the PRISMA guidelines, we systematically searched the literature for population-based prospective cohort studies exploring the association between circulating IL-6 levels and risk of incident ischemic stroke. We pooled association estimates for ischemic stroke risk with random-effect meta-analyses and explored non-linear effects in dose-response meta-analyses. Risk of bias was assessed with the Newcastle-Ottawa scale (NOS).ResultsWe identified 11 studies (n=27,411 individuals; 2,669 incident stroke cases) meeting our eligibility criteria. Overall, quality of the included studies was high (median 8 out of 9 NOS points). In meta-analyses, 1-standard deviation increment in circulating IL-6 levels was associated with a 19% increase in risk of incident ischemic stroke over a mean follow-up of 12.4 years (RR 1.19; 95% CI 1.10 to 1.28). A dose-response meta-analysis showed a linear association between circulating IL-6 levels and ischemic stroke risk. There was only moderate heterogeneity and the results were consistent in sensitivity analyses restricted to studies of low risk of bias and studies fully adjusting for demographic and vascular risk factors. The results also remained stable following adjustment for publication bias.ConclusionsHigher circulating IL-6 levels in community-dwelling individuals are associated with higher long-term risk of incident ischemic stroke in a linear pattern and independently of conventional vascular risk factors. Along with findings from genetic studies and clinical trials, these results provide additional support for a key role of IL-6 signaling in ischemic stroke.
Clinical Utility of Automatable Prediction Models for Improving Palliative and End-Of-Life Care Outcomes: Towards Routine Decision Analysis Before Implementation
Authors: Taseen Ryeyan , Ethier Jean-François 
Published: March 2021

ABSTRACTObjectiveTo evaluate the clinical utility of automatable prediction models for increasing goals-of-care discussions among hospitalized patients at the end-of-life.Materials and MethodsWe developed three Random Forest models and updated the Modified Hospital One-year Mortality Risk model: alternative models to predict one-year mortality (proxy for EOL status) using admission-time data. Admissions from July 2011-2016 were used for training and those from July 2017-2018 were used for temporal validation. We simulated alerts for admissions in the validation cohort and modelled alternative scenarios where alerts lead to code status orders (CSOs) in the EHR. We linked actual CSOs and calculated the expected risk difference (eRD), the number needed to benefit (NNB) and the net benefit (NB) of each model for the patient-centered outcome of a CSO among EOL hospitalizations.ResultsModels had a C-statistic of 0.79-0.86 among unique patients. A CSO was documented during 2599 of 3773 hospitalizations at the EOL (68.9%). At a threshold that identified 10% of eligible admissions, the eRD ranged from 5.4% to 10.7% (NNB 5.4-10.9 alerts). Under usual care, a CSO had a 34% PPV for EOL status. Using this to inform the relative cost of FPs, only two models improved NB over usual care. A RF model with diagnostic predictors had the highest clinical utility by either measure, including in sensitivity analyses.DiscussionAutomatable prediction models with acceptable temporal validity differed meaningfully in their expected ability to improve patient-centered outcomes over usual care.ConclusionDecision-analysis should precede implementation of automated prediction models for improving palliative and EOL care outcomes.
An EMG-assisted Muscle-Force Driven Finite Element Analysis Pipeline to Investigate Joint- and Tissue-Level Mechanical Responses in Functional Activities: Towards a Rapid Assessment Toolbox
Authors: Esrafilian A. , Stenroth L. , Mononen M. E. , Vartiainen P. , Tanska P. , Karjalainen P. A. , Suomalainen J. S. , Arokoski J. , Lloyd D. G. , Korhonen R. K. 
Published: March 2021

AbstractJoint tissue mechanics (e.g., stress and strain) are believed to have a major involvement in the onset and progression of musculoskeletal disorders, e.g., knee osteoarthritis (KOA). Accordingly, considerable efforts have been made to develop musculoskeletal finite element (MS-FE) models to estimate highly-detailed tissue mechanics that predict cartilage degeneration. However, creating such models is time-consuming and requires advanced expertise. This limits these complex, yet promising MS-FE models to research applications with few participants and making the models impractical for clinical assessments. Also, these previously developed MS-FE models are not assessed for any activities other than the gait. This study introduces and validates a semi-automated rapid state-of-the-art MS-FE modeling and simulation toolbox incorporating an electromyography (EMG) assisted MS model and a muscle-force driven FE model of the knee with fibril-reinforced poro(visco)elastic cartilages and menisci. To showcase the usability of the pipeline, we estimated joint- and tissue-level knee mechanics in 15 KOA individuals performing different daily activities. The pipeline was validated by comparing the estimated muscle activations and joint mechanics to existing experimental data. Also, to examine the importance of EMG-assisted MS analyses, results were compared against outputs from the same FE models but driven by static-optimization-based MS models. The EMG-assisted MS-FE pipeline bore a closer resemblance to experiments, compared to the static-optimization-based MS-FE pipeline. More importantly, the developed pipeline showed great potentials as a rapid MS-FE analysis toolbox to investigate multiscale knee mechanics during different activities of individuals with KOA.
Epithelial GPR35 protects fromCitrobacter rodentiuminfection by preserving goblet cells and mucosal barrier integrity
Authors: Melhem Hassan , Kaya Berna , Kaymak Tanay , Wuggenig Philipp , Flint Emilio , Roux Julien , Cavelti-Weder Claudia , Balmer Maria L. , Walser Jean-Claude , Morales Rodrigo A. , Riedel Christian U. , Liberali Prisca , Villablanca Eduardo J. , Niess Jan Hendrik 
Published: March 2021

SummaryGoblet cells secrete mucin to create a protective mucus layer against invasive bacterial infection and are therefore essential for maintaining intestinal health. However, the molecular pathways that regulate goblet cell function remain largely unknown. Although GPR35 is highly expressed in colonic epithelial cells, its importance in promoting the epithelial barrier is unclear. In this study, we show that epithelial Gpr35 plays a critical role in goblet cell function. In mice, cell type-specific deletion ofGpr35in epithelial cells but not in macrophages results in goblet cell depletion and dysbiosis, rendering these animals more susceptible toCitrobacter rodentiuminfection. Mechanistically, scRNA-seq analysis indicates that signaling of epithelial Gpr35 is essential to maintain normal pyroptosis levels in goblet cells. Our work shows that the epithelial presence of Gpr35 is a critical element for the function of goblet cell-mediated symbiosis between host and microbiota.
Stimulus presentation can enhance spiking irregularity across subcortical and cortical regions
Authors: Fayaz Saleh , Fakharian Mohammad Amin , Ghazizadeh Ali 
Published: March 2021

AbstractStimulus presentation is believed to quench neural response variability as measured by fano-factor (FF). However, the relative contribution of within trial spike irregularity (nΨ) and trial to trial rate variability (nRV) to FF reduction has remained elusive. Here, we introduce a principled approach for accurate estimation of variability components for a doubly stochastic point process which unlike previous methods allows for a time varying nΨ (aka ϕ). Notably, analysis across multiple subcortical and cortical areas showed across the board reduction in rate variability. However, unlike what was previously thought, spiking irregularity was not constant in time and was even enhanced in some regions abating the quench in the post-stimulus FF. Simulations confirmed plausibility of a time varying nΨ arising from within and between pool correlations of excitatory and inhibitory neural inputs. By accurate parsing of neural variability, our approach constrains candidate mechanisms that give rise to observed rate variability and spiking irregularity within brain regions.
Measuring hidden phenotype: Quantifying the shape of barley seeds using the Euler Characteristic Transform
Authors: Amézquita Erik J. , Quigley Michelle Y. , Ophelders Tim , Landis Jacob B. , Koenig Daniel , Munch Elizabeth , Chitwood Daniel H. 
Published: March 2021

AbstractShape plays a fundamental role in biology. Traditional phenotypic analysis methods measure some features but fail to measure the information embedded in shape comprehensively. To extract, compare, and analyze this information embedded in a robust and concise way, we turn to Topological Data Analysis (TDA), specifically the Euler Characteristic Transform. TDA measures shape comprehensively using mathematical representations based on algebraic topology features. To study its use, we compute both traditional and topological shape descriptors to quantify the morphology of 3121 barley seeds scanned with X-ray Computed Tomography (CT) technology at 127 micron resolution. The Euler Characteristic Transform measures shape by analyzing topological features of an object at thresholds across a number of directional axes. A Kruskal-Wallis analysis of the information encoded by the topological signature reveals that the Euler Characteristic Transform picks up successfully the shape of the crease and bottom of the seeds. Moreover, while traditional shape descriptors can cluster the seeds based on their accession, topological shape descriptors can cluster them further based on their panicle. We then successfully train a support vector machine (SVM) to classify 28 different accessions of barley based exclusively on the shape of their grains. We observe that combining both traditional and topological descriptors classifies barley seeds better than using just traditional descriptors alone. This improvement suggests that TDA is thus a powerful complement to traditional morphometrics to comprehensively describe a multitude of “hidden” shape nuances which are otherwise not detected.
Occupation as a risk factor for progression of chronic kidney disease: retrospective cohort study
Authors: Takada Daisuke , Kunisawa Susumu , Kikuno Akira , Iritani Tomoko , Imanaka Yuichi 
Published: March 2021

AbstractBackgroundSeveral social determinants of health are associated with the progression of chronic kidney disease (CKD). We compared the risk of CKD progression among 18 occupational classifications using an annual health-checkup database.MethodsWe used the annual health checkup data and health insurance claims data of the Japan Health Insurance Association in Kyoto prefecture between April 2012 and March 2016. The primary outcome for survival analysis was defined as a more than 30% change in the estimated glomerular filtration rate (eGFR) from the first health checkup. We used the Cox proportional-hazards model for time-to-event analyses to estimate the hazard ratio, and 95% CIs for the primary outcome, adjusting for age, sex, eGFR, body mass index, blood pressure, blood sugar, dyslipidemia, uric acid, urinary protein, and existence of kidney diseases at first health checkup.ResultsWe analyzed 239,506 employees, and 1,736 (0.7%) individuals whose eGFR had decreased by 30% or more; the mean follow-up period was 2.8 years (standard deviation: 1.2 years). When we compared the risk for “manufacturing,” five categories of industries (“information and communications”; “transport and postal services”; “accommodations, eating and drinking services”; “living-related and personal services and amusement service”; “medical, health care and welfare”) were associated with a decline in the risk of eGFR after adjusting for the confounding factors and/or mediators.ConclusionsWe provided evidence that the risk of CKD progression depends on occupation type. Further research is needed to confirm the mechanism and causal relationships involved.
The effects of emotional valence and intensity on cognitive and affective empathy after insula lesions
Authors: Holtmann Olga , Franz Marcel , Moenig Constanze , Tenberge Jan-Gerd , Preul Christoph , Schwindt Wolfram , Bruchmann Maximilian , Melzer Nico , Miltner Wolfgang H.R. , Straube Thomas 
Published: March 2021

AbstractThe insula plays a central role in empathy. However, the complex structure of empathic deficits following insular damage is not fully understood. While previous lesion research has shown variable deficits in patients with insular damage on basic discrimination tasks or self-report measures, it is unclear in how far patients with insular damage are impaired in cognitive (CE) and affective empathy (AE) functions depending on valence and arousal of stimuli using an ecologically valid paradigm. In the present study, patients with insular lesions (n= 20) and demographically-matched healthy controls (n= 24) viewed 16 videos (duration: 60 sec each) that varied in terms of valence and emotional intensity. The videos showed a person (target) reporting on a personal life event. In CE conditions, subjects continuously rated the affective state of the target, while in AE conditions they continuously rated their own affect. Mean Squared Error (MSE) assessed deviations between subject and target ratings (CE: deviation between targets’ and participants’ ratings of targets’ emotions; AE: deviation between targets’ and participants’ self-ratings of emotion). Patients differed from controls only in negative, low intensity AE, rating their own affective state less negative than the target rated his/her affect. This deficit was not related to trait empathy, neuropsychological or clinical parameters, or laterality of lesion. Our findings provide important insights into the profile of social cognition impairment after insular damage. Empathic functions may be widely spared after insular damage in a naturalistic, dynamic setting, potentially due to the intact interpretation of social context cues by residual networks outside the lesion. The particular role of the insula in AE for negative states may evolve specifically in situations that bear higher uncertainty, which points to a threshold role of the insula in online ratings of AE.
A fluorescent nanosensor paint reveals the heterogeneity of dopamine release from neurons at individual release sites
Authors: Elizarova S. , Chouaib A. , Shaib A. , Mann F. , Brose N. , Kruss S. , Daniel J.A. 
Published: March 2021

AbstractThe neurotransmitter dopamine is released from discrete axonal structures called varicosities. Its release is essential in behaviour and is critically implicated in prevalent neuropsychiatric diseases. Existing dopamine detection methods are not able to detect and distinguish discrete dopamine release events from multiple varicosities. This prevents an understanding of how dopamine release is regulated across populations of discrete varicosities. Using a near infrared fluorescent (980 nm) dopamine nanosensor ‘paint’ (AndromeDA), we show that action potential-evoked dopamine release is highly heterogeneous across release sites and also requires molecular priming. Using AndromeDA, we visualize dopamine release at up to 100 dopaminergic varicosities simultaneously within a single imaging field with high temporal resolution (15 images/s). We find that ‘hotspots’ of dopamine release are highly heterogeneous and are detected at only ~17% of all varicosities. In neurons lacking Munc13 proteins, which prime synaptic vesicles, dopamine release is abolished during electrical stimulation, demonstrating that dopamine release requires vesicle priming. In summary, AndromeDA reveals the spatiotemporal organization of dopamine release.
Fast model-based ordination with copulas
Authors: Popovic Gordana C. , Hui Francis K. C. , Warton David I. 
Published: March 2021

ABSTRACTVisualising data is a vital part of analysis, allowing researchers to find patterns, and assess and communicate the results of statistical modeling. In ecology, visualisation is often challenging when there are many variables (often for different species or other taxonomic groups) and they are not normally distributed (often counts or presence-absence data). Ordination is a common and powerful way to overcome this hurdle by reducing data from many response variables to just two or three, to be easily plotted.Ordination is traditionally done using dissimilarity-based methods, most commonly non-metric multidimensional scaling (nMDS). In the last decade however, model-based methods for unconstrained ordination have gained popularity. These are primarily based on latent variable models, with latent variables estimating the underlying, unobserved ecological gradients.Despite some major benefits, a major drawback of model-based ordination methods is their speed, as they typically taking much longer to return a result than dissimilarity-based methods, especially for large sample sizes.We introduce copula ordination, a new, scalable model-based approach to unconstrained ordination. This method has all the desirable properties of model-based ordination methods, with the added advantage that it is computationally far more efficient. In particular, simulations show copula ordination is an order of magnitude faster than current model-based methods, and can even be faster than nMDS for large sample sizes, while being able to produce similar ordination plots and trends as these methods.
Effects of short-term isolation on social animals’ behavior: an experimental case study of Japanese macaque
Authors: Morita T , Toyoda A , Aisu S , Kaneko A , Suda-Hashimoto N , Adachi I , Matsuda I , Koda H 
Published: March 2021

AbstractOne of the goals in animal socioecology is to understand the functions and dynamics of group living. While observations of free-ranging animals are a crucial source of information, an experimental investigation that manipulates the size or composition, or both, of animal groups in captivity can also bring complementary contributions to the research inquiry. When paired with an automatic data collection by biologging technology, experimental studies on captive animals also allow for big data analyses based on recent machine learning techniques. As an initial exploration of this research paradigm, the present study inquired to what extent isolation of captive Japanese macaques (Macaca fuscata) changed their movement patterns. Using three-dimensional location trajectories of the macaques that were systematically collected via Bluetooth Low Energy beacons and a deep neural network, we estimated the identifiability of whether a macaque was behaving in isolation or in group. We found that the neural network identified the isolation vs. in-group conditions with more than 90% accuracy from a five-minute location trajectory, suggesting that the isolation caused notable changes from the canonical group-living behaviors. In addition, the isolation made each individual more identifiable from one another based on their location trajectories.
Laboratory mice with a wild microbiota generate strong allergic immune responses
Authors: Ma Junjie , Classon Cajsa H. , Stark Julian M. , Li Muzhen , Huang Huey-Jy , Vrtala Susanne , Rosshart Stephan P. , Nylén Susanne , Coquet Jonathan M. 
Published: March 2021

AbstractAllergic disorders are caused by a combination of hereditary and environmental factors. The hygiene hypothesis postulates that early life microbial exposures impede the development of subsequent allergic disease. However, unambiguous evidence that microbes reduce the development of allergic disorders is still lacking. Recently developed ‘wildling’ mice contain a rich and diverse commensal and encounter a repertoire of microbes typical of the wild, with pathogenic potential. Here, we probed the hygiene hypothesis by comparing the development of allergic inflammation in wildlings to that of genetically identical mice lacking diverse microbial exposure. We find that wildlings develop stronger allergic inflammation in response to house dust mites with allergic T cell responses driven not only by cognate peptide antigens, but also by innate cytokines. In all, the results suggest that high microbial content and diversity potentiates, rather than restricts, allergic immune responses.One sentence summaryStrong allergic inflammation in the face of rich and diverse microbial exposures