bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 Diagnostic Testing For All - Using Non-Dilutive Saliva Sample Collection, Stabilization and Ambient Transport Devices
Authors: Carrington Yuan , Orlino Justin , Romero Alejandro , Gustin Jessica , Rezaei Mahssa , Greene Elizabeth , Rose Summer , Aiyer Ramani A. , Nasarabadi Shanavaz 
Published: January 2021

AbstractCOVID-19 testing is not accessible for millions during this pandemic despite our best efforts. Without greatly expanded testing of asymptomatic individuals, contact tracing and subsequent isolation of spreaders remains as a means for control. In an effort to increase RT-PCR assay testing for the presence of the novel beta-coronavirus SARS-CoV-2 as well as improve sample collection safety, GenTegra LLC has introduced two products for saliva collection and viral RNA stabilization: GTR-STM™ (GenTegra Saliva Transport Medium) and GTR-STMdk™ (GenTegra Saliva Transport Medium Direct to PCR). Both products contain a proprietary formulation based on GenTegra’s novel “Active Chemical Protection™” (ACP) technology that gives non-dilutive, error-free saliva sample collection using RNA stabilization chemicals already dried in the collection tube.GTR-STM can be used for safer saliva-based sample collection at home (or at a test site). Following saliva collection, the sample-containing GTR-STM can be kept at ambient temperature during shipment to an authorized CLIA lab for analysis. SARS-CoV-2 viral RNA in GTR-STM is stable for over a month at ambient temperature, easily surviving the longest transit times from home to lab. GTR-STM enhances patient comfort, convenience, compliance and reduces infectious virus exposure to essential medical and lab professionals.Alternatively, the GTR-STMdk direct-into-PCR product can be used to improve lab throughput and reduce reagent costs for saliva sample collection and testing at any lab site with access to refrigeration. GTR-STMdk reduces lab process time by 25% and reagent costs by 30% compared to other approaches. Since GTR-STMdk retains SARS-CoV-2 viral RNA stability for three days at ambient temperature, it is optimized for lab test site rather than at home saliva collection. SARS-COV-2 viral RNA levels as low as 0.4 genome equivalents/uL are detected in saliva samples using GTR-STMdk. The increased sensitivity of SARS-CoV-2 detection can expand COVID-19 testing to include asymptomatic individuals using pooled saliva.One Sentence SummaryGTR-STM and Direct-into-PCR GTR-STMdk offer substantive improvements in SARS-CoV-2 viral RNA stability, safety, and RT-PCR process efficiency for COVID-19 testing by using a non-dilutive saliva sample collection system for individuals at home or onsite respectively.
Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles
Authors: Hautakangas Heidi , Winsvold Bendik S. , Ruotsalainen Sanni E. , Bjornsdottir Gyda , Harder Aster V. E. , Kogelman Lisette J. A. , Thomas Laurent F. , Noordam Raymond , Benner Christian , Gormley Padhraig , Artto Ville , Banasik Karina , Bjornsdottir Anna , Boomsma Dorret I. , Brumpton Ben M. , Sølvsten Burgdorf Kristoffer , Buring Julie E. , Chalmer Mona Ameri , de Boer Irene , Dichgans Martin , Erikstrup Christian , Färkkilä Markus , Garbrielsen Maiken Elvestad , Ghanbari Mohsen , Hagen Knut , Häppölä Paavo , Hottenga Jouke-Jan , Hrafnsdottir Maria G. , Hveem Kristian , Johnsen Marianne Bakke , Kähönen Mika , Kristoffersen Espen S. , Kurth Tobias , Lehtimäki Terho , Lighart Lannie , Magnusson Sigurdur H. , Malik Rainer , Pedersen Ole Birger , Pelzer Nadine , Penninx Brenda W. J. H. , Ran Caroline , Ridker Paul M. , Rosendaal Frits R. , Sigurdardottir Gudrun R. , Skogholt Anne Heidi , Sveinsson Olafur A. , Thorgeirsson Thorgeir E. , Ullum Henrik , Vijfhuizen Lisanne S. , Widén Elisabeth , van Dijk Ko Willems ,   International Headache Genetics Consortium, Headache HUNT All-in ,   Danish Blood Donor Study Genomic Cohort, Aromaa Arpo , Belin Andrea Carmine , Freilinger Tobias , Ikram M. Arfan , Järvelin Marjo-Riitta , Raitakari Olli T. , Terwindt Gisela M. , Kallela Mikko , Wessman Maija , Olesen Jes , Chasman Daniel I. , Nyholt Dale R. , Stefánsson Hreinn , Stefansson Kari , van den Maagdenberg Arn M. J. M. , Hansen Thomas Folkmann , Ripatti Samuli , Zwart John-Anker , Palotie Aarno , Pirinen Matti 
Published: January 2021

AbstractMigraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. This genome-wide association study (GWAS) of 102,084 migraine cases and 771,257 controls identified 123 loci of which 86 are novel. The loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. A stratification of the risk loci using 29,679 cases with subtype information, of which approximately half have never been used in a GWAS before, indicated three risk variants that appear specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that appear specific for migraine without aura (near SPINK2 and near FECH), and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.
Clarifying Values: An Updated and Expanded Systematic Review and Meta-Analysis
Authors: Witteman Holly O. , Ndjaboue Ruth , Vaisson Gratianne , Dansokho Selma Chipenda , Arnold Bob , Bridges John F. P. , Comeau Sandrine , Fagerlin Angela , Gavaruzzi Teresa , Marcoux Melina , Pieterse Arwen , Pignone Michael , Provencher Thierry , Racine Charles , Regier Dean , Rochefort-Brihay Charlotte , Thokala Praveen , Weernink Marieke , White Douglas B. , Wills Celia E. , Jansen Jesse 
Published: January 2021

AbstractBackgroundPatient decision aids should help people make evidence-informed decisions aligned with their values. There is limited guidance about how to achieve such alignment.PurposeTo describe the range of values clarification methods available to patient decision aid developers, synthesize evidence regarding their relative merits, and foster collection of evidence by offering researchers a proposed set of outcomes to report when evaluating the effects of values clarification methods.Data SourcesMEDLINE, EMBASE, PubMed, Web of Science, the Cochrane Library, CINAHLStudy SelectionWe included articles that described randomized trials of one or more explicit values clarification methods. From 30,648 records screened, we identified 33 articles describing trials of 43 values clarification methods.Data ExtractionTwo independent reviewers extracted details about each values clarification method and its evaluation.Data SynthesisCompared to control conditions or to implicit values clarification methods, explicit values clarification methods decreased the frequency of values-disgruent choices (risk difference -0.04 95% CI [-0.06 to -0.02], p<.001) and decisional regret (standardized mean difference -0.20 95% CI [-0.29 to -0.11], p<0.001). Multicriteria decision analysis led to more values-congruent decisions than other values clarification methods (Chi-squared(2)=9.25, p=.01). There were no differences between different values clarification methods regarding decisional conflict (Chi-squared(2)=6.08, p=.05).LimitationsSome meta-analyses had high heterogeneity. We grouped values clarification methods into broad categories.ConclusionsCurrent evidence suggests patient decision aids should include an explicit values clarification method. Developers may wish to specifically consider multicriteria decision analysis. Future evaluations of values clarification methods should report their effects on decisional conflict, decisions made, values congruence, and decisional regret.
Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs
Authors: Blanes-Selva Vicent , Doñate-Martínez Ascensión , Linklater Gordon , García-Gómez Juan M. 
Published: January 2021

AbstractIntroductionPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Nowadays, there is a growing consensus about giving access these care services to non-cancer older patients. Bad survival prognosis and patients’ decline are working criterions to guide PC decision making.ObjectiveThe main aim of this work is to propose complementary models based on machine learning approaches to predict frailty and mortality in older patients in the context of supporting PC decision making.MethodsThe dataset used in this study is composed by 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. Predictive models based on Gradient Boosting Machines and Deep Neural Networks were implemented for binary one-year mortality classification, survival estimation and binary one-year frailty classification. Besides, we tested the similarity between mortality and frailty distributions.ResultsThe one-year mortality classifier achieved an AUC ROC of 0.87 [0.86, 0.87]; whereas the mortality regression model achieved an MAE of 333.13 [323.10, 342.49] days. Moreover, the one-year frailty classifier obtained an AUC ROC of 0.89 [0.88, 0.90].ConclusionsThe performance of our one-year mortality model is competitive with the current state-of-the-art. Besides, to our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty criteria are weakly correlated and have different distributions; therefore, we interpreted them as complementary assessment measurements for palliative care decision making. Predictive models are accessible as an online tool athttp://demoiapc.upv.es. The models presented here may be part of decision support systems for care services in non-cancer older patients after their external validation.
Does the posteromedial cortex play a primary role for the capacity for consciousness in rats?
Authors: Arena A. , Juel B.E. , Comolatti R. , Thon S. , Storm J.F. 
Published: January 2021

AbstractIt remains unclear how specific cortical regions contribute to the brain’s overall capacity for consciousness. Clarifying this could help distinguish between theories of consciousness. Here, we investigate the association between markers of regionally specific (de)activation and the brain’s overall capacity for consciousness.We recorded electroencephalographic (EEG) responses to cortical electrical stimulation in 6 rats, and computed Perturbational Complexity Index state-transition (PCIST), which has been extensively validated as an index of the capacity for consciousness in humans. We also estimated the balance between activation and inhibition of specific cortical areas with the ratio between high and low frequency power (HF/LF) from spontaneous EEG activity at each electrode. We repeated these measurements during wakefulness, and under the influence of ketamine anaesthesia at two doses: the minimal dose needed to induce behavioural unresponsiveness and twice this dose.We found that PCIST was only slightly reduced from wakefulness to light ketamine anaesthesia, but dropped significantly down with deeper anaesthesia. The high-dose effect was selectively associated with reduced HF/LF ratio in the posteromedial cortex, which strongly correlated with PCIST. Conversely, behavioural unresponsiveness induced by light ketamine anaesthesia, was associated with similar spectral changes in frontal, but not posterior cortical regions.These findings seem to support the claim that the posteromedial cortex may play a primary role for the capacity for consciousness. Such region-specific associations between cortical activation and the overall capacity for consciousness must be accounted for by theories of consciousness.
Single neuron firing cascades underlie global spontaneous brain events
Authors: Liu Xiao , Leopold David A. , Yang Yifan 
Published: January 2021

AbstractThe resting brain consumes enormous energy and shows highly organized spontaneous activity. To investigate how this activity is manifest among single neurons, we analyzed spiking discharges of ∼10,000 isolated cells recorded from multiple cortical and subcortical regions of the mouse brain during immobile rest. We found that firing of a significant proportion (∼70%) of neurons conformed to a ubiquitous, temporally sequenced cascade of spiking that was synchronized with global events and elapsed over timescales of 5-10 seconds. Across the brain, two intermixed populations of neurons supported orthogonal cascades. The relative phases of these cascades determined, at each moment, the response magnitude evoked by an external visual stimulus. Furthermore, the spiking of individual neurons embedded in these cascades was time locked to physiological indicators of arousal, including local field potential (LFP) power, pupil diameter, and hippocampal ripples. These findings demonstrate that the large-scale coordination of low-frequency spontaneous activity, which is commonly observed in brain imaging and linked to arousal, sensory processing, and memory, is underpinned by sequential, large-scale temporal cascades of neuronal spiking across the brain.
Association between clinical characteristics and laboratory findings with outcome of hospitalized COVID-19 patients, a report from northeast of Iran
Authors: Sobhani Sahar , Aryan Reihaneh , Kalantari Elham , Soltani Salman , Malek Nafise , Pirzadeh Parisa , Yarahmadi Amir , Aghaee Atena 
Published: January 2021

AbstractCoronavirus disease 2019 (COVID-19) was first discovered in December 2019 in China and has rapidly spread worldwide. Clinical characteristics, laboratory findings, and their association with the outcome of patients with COVID-19 can be decisive in management and early diagnosis. Data were obtained retrospectively from medical records of 397 hospitalized COVID-19 patients between February and May 2020 in Imam Reza hospital, northeast of Iran. Clinical and laboratory features were evaluated among survivors and non-survivors. The correlation between variables and duration of hospitalization and admission to the Intensive Care Unit (ICU) was determined. Male sex, age, hospitalization duration, and admission to ICU were significantly related to mortality rate. Headache was a more common feature in patients who survived (p = 0.017). It was also related to a shorter stay in the hospital (p = 0.032) as opposed to patients who experienced chest pain (p = 0.033). Decreased levels of consciousness and dyspnea were statistically more frequent in non-survivors (p = 0.003 and p = 0.011, respectively). Baseline white blood cell count (WBC), erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) were significantly higher in non-survivors (p < 0.001). Patients with higher WBC and CRP levels were more likely to be admitted to ICU (p = 0.009 and p = 0.001, respectively). Evaluating clinical and laboratory features can help clinicians find ways for risk stratifying patients and even make predictive tools. Chest pain, decreased level of consciousness, dyspnea, and increased CRP and WBC levels seem to be the most potent predictors of severe prognosis.
Long-read metagenomics of soil communities reveals phylum-specific secondary metabolite dynamics
Authors: Van Goethem Marc W. , Osborn Andrew R. , Bowen Benjamin P. , Andeer Peter F. , Swenson Tami L. , Clum Alicia , Riley Robert , He Guifen , Koriabine Maxim , Sandor Laura , Yan Mi , Daum Chris G. , Yoshinaga Yuko , Makhalanyane Thulani P. , Garcia-Pichel Ferran , Visel Axel , Pennacchio Len A. , O’Malley Ronan C. , Northen Trent R. 
Published: January 2021

AbstractMicrobial biosynthetic gene clusters (BGCs) encoding secondary metabolites are thought to impact a plethora of biologically mediated environmental processes, yet their discovery and functional characterization in natural microbiomes remains challenging. Here we describe deep long-read sequencing and assembly of metagenomes from biological soil crusts, a group of soil communities that are rich in BGCs. Taking advantage of the unusually long assemblies produced by this approach, we recovered nearly 3,000 BGCs for analysis, including 695 novel, full-length BGCs. Functional exploration through metatranscriptome analysis of a 3-day wetting experiment uncovered phylum-specific BGC expression upon activation from dormancy, elucidating distinct roles and complex phylogenetic and temporal dynamics in wetting processes. For example, a pronounced increase in BGC transcription occurs at night in cyanobacteria but not in other phyla, implicating BGCs in nutrient scavenging roles and niche competition. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional dynamics of BGCs in environmental processes and suggests a central role of secondary metabolites in maintaining phylogenetically conserved niches within biocrusts.
NCodR: A multi-class SVM classification to distinguish between non-coding RNAs in Viridiplantae
Authors: Nithin Chandran , Mukherjee Sunandan , Basak Jolly , Bahadur Ranjit Prasad 
Published: January 2021

ABSTRACTNon-coding RNAs (ncRNAs) are major players in the regulation of gene expression. This study analyses seven classes of ncRNAs in plants using sequence and secondary structure-based RNA folding measures. We observe distinct regions in the distribution of AU content along with overlapping regions for different ncRNA classes. Additionally, we find similar averages for minimum folding energy index across various ncRNAs classes except for pre-miRNAs and lncRNAs. Various RNA folding measures show similar trends among the different ncRNA classes except for pre-miRNAs and lncRNAs. We observe different k-mer repeat signatures of length three among various ncRNA classes. However, in pre-miRs and lncRNAs, a diffuse pattern of k-mers is observed. Using these attributes, we train eight different classifiers to discriminate various ncRNA classes in plants. Support-vector machines employing radial basis function show the highest accuracy (average F1 of ~91%) in discriminating ncRNAs, and the classifier is implemented as a web server, NCodR.
Using an Ecological and Biological Framing for an Anti-racist Covid-19 Approach
Authors: Camargo Araceli , Hossain Elahi , Aliko Sarah , Akinola-Odusola Daniel , Artus Josh , Kelman Ilan 
Published: January 2021

AbstractIn the United States and the United Kingdom COVID-19 has disproportionately affected Black, Indigenous and People of Colour (BIPOC) and Black, Asian and Minority Ethnic (BAME) people respectively. Multiple studies identify environmental factors such as overcrowded housing and poor workplace conditions as contributing factors for the disproportionate COVID-19 rates amongst BAME and BIPOC communities. This paper will show that to fully understand the phenomenon, both an ecological and biological approach is needed. An ecological approach highlights how a person’s habitat and the experiences within it mediate their susceptibility to disease. Moreover, to understand how this mediation works, this paper will use allostatic load as a biological pathway to link a person to their habitat and the poor health outcomes that contributed to COVID-19 susceptibility. In introducing this new approach, the paper will serve as an anti-racist framework for understanding how COVID-19 affected BAME and BIPOC communities. It is anti-racist by centring poor health outcomes on the habitats people are forced to live in due to structural racism rather than the physiology of a person’s race or ethnicity. This is important in order to avoid similar crises in the future and to improve the health of marginalised communities.
Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises
Authors: Chowell Gerardo , Dahal Sushma , Bono Raquel , Mizumoto Kenji 
Published: January 2021

AbstractTo ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and the testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.
Next generation vaccine platform: polymersomes as stable nanocarriers for a highly immunogenic and durable SARS-CoV-2 spike protein subunit vaccine
Authors: Lam Jian Hang , Khan Amit Kumar , Cornell Thomas Andrew , Dress Regine Josefine , Chia Teck Wan , William Yeow Wen Wang , Mohd-Ismail Nur Khairiah , Venkatraman Shrinivas , Ng Kim Tien , Tan Yee-Joo , Anderson Danielle E. , Ginhoux Florent , Nallani Madhavan 
Published: January 2021

AbstractMultiple successful vaccines against SARS-CoV-2 are urgently needed to address the ongoing Covid-19 pandemic. In the present work, we describe a subunit vaccine based on the SARS-CoV-2 spike protein co-administered with CpG adjuvant. To enhance the immunogenicity of our formulation, both antigen and adjuvant were encapsulated with our proprietary artificial cell membrane (ACM) polymersome technology. Structurally, ACM polymersomes are self-assembling nanoscale vesicles made up of an amphiphilic block copolymer comprising of polybutadiene-b-polyethylene glycol and a cationic lipid 1,2-dioleoyl-3-trimethylammonium-propane. Functionally, ACM polymersomes serve as delivery vehicles that are efficiently taken up by dendritic cells, which are key initiators of the adaptive immune response. Two doses of our formulation elicit robust neutralizing titers in C57BL/6 mice that persist at least 40 days. Furthermore, we confirm the presence of memory CD4+and CD8+T cells that produce Th1 cytokines. This study is an important step towards the development of an efficacious vaccine in humans.