bluuebunny/crossref_metadata_2025_split huggingface dataset:
Environmental factors and mobility predict COVID-19 seasonality
Authors: Hoogeveen Martijn J. , Kroes Aloys C.M. , Hoogeveen Ellen K. 
Published: September 2021

AbstractBackgroundWe recently showed that seasonal patterns of COVID-19 incidence and Influenza-Like Illnesses incidence are highly similar, in a country in the temperate climate zone, such as the Netherlands (latitude: 52°N). We hypothesize that in The Netherlands the same environmental factors and mobility trends that are associated with the seasonality of flu-like illnesses are predictors of COVID-19 seasonality as well.MethodsWe used meteorological, pollen/hay fever and mobility data from the Netherlands with its 17.4 million inhabitants. For the reproduction number of COVID-19 (Rt), we used data from the Dutch State Institute for Public Health. This Rt metric is a daily estimate that is based on positive COVID-19 tests in the Netherlands in hospitals and municipalities. For all datasets we selected the overlapping period of COVID-19 and the first allergy season: from February 17, 2020 till September 21, 2020 (total number of measurements: n = 218), the end of pollen season. Backward stepwise multiple linear regression was used to develop an environmental prediction model of the Rt of COVID-19. Next, we studied whether adding mobility trends to an environmental model improved the predictive power.ResultsBy means of stepwise backward multiple linear regression four highly significant (p value < 0.01) predictive factors are selected in our combined model: temperature, solar radiation, hay fever incidence, and mobility to indoor recreation locations. Our combined model explains 87.5% of the variance of Rt of COVID-19 and has a good and highly significant fit: F(4, 213) = 374.2, p-value < 0.00001. The combined model had a better overall predictive performance compared to a solely environmental model, which still explains 77.3% of the variance of Rt, and a good and highly significant fit: F(4, 213) = 181.3, p < 0.00001.ConclusionsWe conclude that the combined mobility and environmental model can adequately predict the seasonality of COVID-19 in a country with a temperate climate like the Netherlands. In this model higher solar radiation, higher temperature and hay fever are related to lower COVID-19 reproduction, and mobility to indoor recreation locations with increased COVID-19 spread.HighlightsThe seasonality of COVID-19 can be well-explained by environmental factors and mobility.A combined model explains 87.5% of the variance of the reproduction number of COVID-19Inhibitors of the reproduction number of COVID-19 are higher solar radiation, and seasonal allergens/allergies.Mobility, especially to indoor recreation locations, increases the reproduction number of COVID-19.Temperature has no direct effect on the reproduction number of COVID-19, but affects mobility and seasonal allergens.Adding mobility trends to an environmental model improves the predictive value regarding the reproduction number of COVID-19.
Impaired Lymphocyte Responses in Pediatric Sepsis Vary by Pathogen Type
Authors: Lindell Robert B. , Zhang Donglan , Bush Jenny , Wallace Douglas C. , Rabinowitz Joshua D. , Lu Wenyun , Wherry E. John , Weiss Scott L. , Henrickson Sarah E. 
Published: September 2021

ABSTRACTBackgroundSepsis is the leading cause of death in hospitalized children worldwide. Despite its hypothesized immune-mediated mechanism, targeted immunotherapy for sepsis is not available for clinical use.ObjectiveTo determine the association between cytometric, proteomic, bioenergetic, and metabolomic abnormalities and pathogen type in pediatric sepsis.MethodsSerial PBMC samples were obtained from 14 sepsis patients (34 samples) and 7 control patients for this pilot study. Flow cytometry was used to define immunophenotype, including T cell subset frequency and activation state, and assess intracellular cytokine production. Global immune dysfunction was assessed by TNF-production capacity and monocyte HLA-DR expression. Mitochondrial function was assessed by bulk respirometry. Plasma cytokine levels were determined via Luminex assay. Metabolites were measured by liquid chromatography-mass spectrometry. Results were compared by timepoint and pathogen type.ResultsSepsis patients were older and had higher illness severity compared to controls; demographics were otherwise similar. Compared to controls, sepsis patients demonstrated global immune dysfunction, loss of peripheral of non-naïve CD4+ T cells, and reduced PBMC mitochondrial function. Metabolomic findings in sepsis patients were most pronounced at sepsis onset and included elevated uridine and 2-dehydrogluconate and depleted citrulline. Loss of peripheral non-naïve CD4+ T cells was associated with immune dysfunction and reduced cytokine production despite increased T cell activation. CD4+ T cell differentiation and corresponding pro- and anti-inflammatory cytokines varied by pathogen.ConclusionPediatric sepsis patients exhibit a complex, dynamic physiologic state characterized by immunometabolic dysregulation which varies by pathogen type.
Characterisation of the blood RNA host response underpinning severity in COVID-19 patients
Authors: Jackson Heather , Calle Irene Rivero , Broderick Claire , Habgood-Coote Dominic , d’Souza Giselle , Nichols Samuel , Gómez-Rial Jose , Rivero-Velasco Carmen , Rodríguez-Núñez Nuria , Barbeito-Castiñeiras Gema , Pérez-Freixo Hugo , Acosta Manuel Barreiro-de , Cunnington Aubrey J. , Herberg Jethro A. , Wright Victoria J. , Gómez-Carballa Alberto , Salas Antonio , Levin Mike , Martinon-Torres Federico , Kaforou Myrsini ,   PERFORM consortium and GEN-COVID study group
Published: September 2021

AbstractInfection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups. Increasing COVID-19 severity was characterised by an abundance of inflammatory immune response genes and pathways, including many related to neutrophils and macrophages, in addition to an upregulation of immunoglobulin genes. Our insights into COVID-19 severity reveal the role of immune dysregulation in the progression to severe disease and highlight the need for further research exploring the interplay between SARS-CoV-2 and the inflammatory immune response.
Blood biochemical parameters as predictors of disease severity and mortality in COVID-19 patients- an updated systematic review and meta-analysis
Authors: Majid Afsha , Mishra Pinki , Parveen Rizwana , Bajpai Ram , Khan Mohd. Ashif , Agarwal Nidhi Bharal 
Published: September 2021

ABSTRACTBackgroundThe outbreak of coronavirus disease 2019 (COVID-19) has been rapidly spreading across the globe and poses a great risk to human health. Patients with abnormalities in laboratory parameters are more susceptible to COVID-19. Therefore, we explored the association of blood biochemical parameters with severity and mortality of COVID-19 amongst 3695 patients across seventeen studies.MethodsWe searched PubMed, Cochrane library and LitCOVID database until February 28, 2021. Seventeen studies were included in the meta-analysis with 3695 COVID-19 patients.ResultsThe pooled analysis showed that compared to non-severe group, severe group was characterised by significantly elevated alanine aminotransferase (ALT) (standardised mean difference [SMD]: 0.65, 95% confidence interval [CI]: 0.23 to 1.06; p<0.001, erythrocyte sedimentation rate (ESR) (SMD: 0.55, 95%CI: 0.02 to 1.07 p=0.004) and lymphopenia (SMD: -1.22, 95% CI: -2.15 to -0.30; p<0.01), decreased serum albumin (SMD: -1.60, 95% CI: -2.96 to -0.22 ; p<0.001), creatinine (SMD: 0.54, 95% CI: 0.17 to 0.90; p<0.001), lactate dehydrogenase (LDH)(SMD: -1.54, 95% CI: - 2.27 to -0.80; p=0.002) and haemoglobin (SMD:-0.89, 95% CI: ; p<0.001). Additionally, in the non-survivor group, elevated lactate dehydrogenase (LDH) (SMD: 1.54 95% CI: -2.27 to 0.80; p=0.002), decreased serum albumin (SMD: 1.08, 95% CI: 0.75 to 1.42; p<0.001) were reported. There was no comorbidity which was found to be significant in the severe group.ConclusionSerum albumin, ALT, ESR, lymphopenia, haemoglobin, and leucocytosis can reflect the severity of COVID-19, while the LDH, leucocytosis and albumin can be considered as risk factor to higher mortality.SummaryOur manuscript discusses the various blood biochemical markers as potential predictors of disease severity and mortality in COVID-19 patients. The timely detection of these parameters can help in providing appropriate course of treatment and reducing the mortality rate in the patients. We have found an association between the blood biochemical markers and disease severity and mortality in COVID-19 patients. Serum albumin, alanine aminotransferase (ALT), Erythrocyte Sedimentation Rate (ESR), lymphopenia, hemoglobin, and leukocytosis can reflect the severity of the disease, while the LDH, leukocytosis and albumin can be considered as risk factor to higher mortality.
Association of inflammatory markers with severity of disease and mortality in COVID-19 patients: a systematic review and meta-analysis
Authors: Khan Sara , Mishra Pinki , Parveen Rizwana , Bajpai Ram , Khan Mohd Ashif , Agarwal Nidhi Bharal 
Published: September 2021

ABSTRACTPurposeLiterature suggests association of inflammatory markers with the severity and mortality related to COVID-19, but there are varying conclusions available. We aimed to provide an overview of the association of inflammatory markers with the severity and mortality of COVID-19 patients.MethodsWe searched Medline (via PubMed), Cochrane, Clinicaltrials.gov databases until Sept 1, 2020.ResultsA total of 21 studies comprising 4023 patients with COVID-19 were included in our analysis. Levels of IL-6 (WMD=18.17 95%CI 3.38 to 32.96, p=0.016), IL-8 (WMD=12.09 95%CI 4.41 to 19.77, p=0.002), MCP-1 (WMD=146.66 95%CI 88.16 to 205.16, p<0.001), CRP (WMD=31.09 95%CI 10.08 to 52.10, p=0.004), PCT (WMD= -31.23 95%CI -37.70 to -24.76, p<0.001), IL-2R (WMD=861.93 95%CI 275.45 to 1448.41, p=0.004), ferritin (WMD= 1083.34 95%CI 431.99 to 1734.70, p=0.001) were found significantly higher in the severe group compared with the non-severe group of COVID-19 patients. Moreover, non-survivors had a higher levels of IL-2R (WMD= -666.06 95%CI -782.54 to -549.59, p<0.001), IL-8 (WMD= -26.63 95%CI -33.031 to -20.236, p<0.001), IL-10 (WMD= -7.60 95%CI -8.93 to -6.26, p<0.001), TNF-α (WMD= -4.60 95%CI -5.71 to -3.48, p<0.001), IL-1β (WMD=22.66 95%CI 8.13 to 37.19, p=0.002), CRP (WMD= -96.40 95%CI -117.84 to -74.97, p<0.001), and ferritin (WMD= -937.60 95%CI -1084.15 to -791.065, p<0.001) when compared to the non-survivor group.ConclusionThis meta-analysis highlights the association of inflammatory markers with the severity and mortality of COVID-19 patients. Measurement of these inflammatory markers may assist clinicians to monitor and evaluate the severity and prognosis of COVID-19 thereby reducing the mortality rate.
Risk of heart disease following breast cancer: results from a population-based cohort study
Authors: Yang Haomin , Bhoo-Pathy Nirmala , Brand Judith S. , Hedayati Elham , Grassmann Felix , Zeng Erwei , Bergh Jonas , Bian Weiwei , Ludvigsson Jonas F. , Hall Per , Czene Kamila 
Published: September 2021

ABSTRACTBACKGROUNDThere is a rising concern about treatment-associated cardiotoxicities in breast cancer patients.OBJECTIVESThis study aimed to determine the time- and treatment-specific incidence of arrhythmia, heart failure and ischemic heart disease in women diagnosed with breast cancer.METHODSA register-based matched cohort study was conducted including 8338 breast cancer patients diagnosed from 2001-2008 in the Stockholm-Gotland region and followed-up until 2017. Overall and time dependent risks of arrhythmia, ischemic heart disease and heart failure in breast cancer patients were assessed using flexible parametric models as compared to matched controls from general population. Treatment-specific effects were estimated in breast cancer patients using Cox model.RESULTSDuring a median follow-up of 10.8 years, the hazard ratios for arrhythmia, heart failure and ischemic heart disease, were 1.27 (95% CI = 1.18-1.37), 1.38 (95% CI = 1.23-1.55), and 0.93 (95% CI = 0.84-1.03), respectively. Time-dependent analyses revealed long-term increased risks of arrhythmia, and heart failure in breast cancer patients compared to matched controls. The risk of ischemic heart disease was only elevated in the first year after cancer diagnosis. Trastuzumab and anthracyclines were associated with increased risk of heart failure. Aromatase inhibitors, but not tamoxifen, were associated with risk of ischemic heart disease. No increased risk of heart disease was identified following loco-regional radiotherapy.CONCLUSIONSAdministration of systemic adjuvant therapies appear to be associated with increased risks of heart disease. The risk estimates observed in this study may serve as reference to aid adjuvant therapy decision-making and patient counseling in oncology practices.
A novel method for an unbiased estimate of cross-ancestry genetic correlation using individual-level data
Authors: Momin Md. Moksedul , Shin Jisu , Lee Soohyun , Truong Buu , Benyamin Beben , Lee S. Hong 
Published: September 2021

AbstractCross-ancestry genetic correlation is an important parameter to understand the genetic relationship between two ancestry groups for a complex trait. However, existing methods cannot properly account for ancestry-specific genetic architecture, which is diverse across ancestries, producing biased estimates of cross-ancestry genetic correlation. Here, we present a method to construct a genomic relationship matrix (GRM) that can correctly account for the relationship between ancestry-specific allele frequencies and ancestry-specific causal effects. Through comprehensive simulations, we show that the proposed method outperforms existing methods in the estimations of SNP-based heritability and cross-ancestry genetic correlation. The proposed method is further applied to six anthropometric traits from the UK Biobank data across 5 ancestry groups. One of our findings is that for obesity, the estimated genetic correlation between African and European ancestry cohorts is significantly different from unity, suggesting that obesity is genetically heterogenous between these two ancestry groups.
The supramolecular organization of SARS-CoV and SARS-CoV-2 virions revealed by coarse-grained models of intact virus envelopes
Authors: Wang Beibei , Zhong Changqing , Tieleman D. Peter 
Published: September 2021

ABSTRACTThe coronavirus disease 19 (COVID-19) pandemic is causing a global health crisis and has already caused a devastating societal and economic burden. The pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a high sequence and architecture identity with SARS-CoV, but far more people have been infected by SARS-CoV-2. Here, combining structural data from cryo-EM and structure prediction, we constructed bottom-up Martini coarse-grained models of intact SARS-CoV and SARS-CoV-2 envelopes. Microsecond molecular dynamics simulations were performed, allowing us to explore their dynamics and supramolecular organization. Both SARS-CoV and SARS-CoV-2 envelopes present a spherical morphology with structural proteins forming multiple string-like islands in the membrane and clusters between heads of spike proteins. Critical differences between the SARS-CoV and SARS-CoV-2 envelopes are the interaction pattern between spike proteins and the flexibility of spike proteins. Our models provide structural and dynamic insights in the SARS virus envelopes, and could be used for further investigation, such as drug design, and fusion and fission processes.
A shared brain system forming confidence judgment across cognitive domains
Authors: Rouault Marion , Lebreton Maël , Pessiglione Mathias 
Published: September 2021

ABSTRACTConfidence is typically defined as a subjective judgment about whether a decision is right. Decisions are based on sources of information that come from various cognitive domains and are processed in different brain systems. An unsettled question is whether the brain computes confidence in a similar manner whatever the domain or in a manner that would be idiosyncratic to each domain. To address this issue, human participants of both sexes performed two tasks probing confidence in decisions made about the same material (history and geography statements), but based on different cognitive processes: semantic memory for deciding whether the statement was true or false, and duration perception for deciding whether the statement display was long or short. At the behavioral level, we found that the same factors (difficulty, accuracy, response time and confidence in the preceding decision) predicted confidence judgments in both tasks. At the neural level, we observed using fMRI that confidence judgments in both tasks were associated to activity in the same brain regions: positively in the ventromedial prefrontal cortex and negatively in a prefronto-parietal network. Together, these findings suggest the existence of a shared brain system that generates confidence judgments in a similar manner across cognitive domains.
Myelin Imaging Using Dual-echo 3D Ultra-short Echo Time MRI with Rosette k-Space Pattern
Authors: Shen Xin , Özen Ali Caglar , Sunjar Antonia , Ilbey Serhat , Shi Riyi , Chiew Mark , Emir Uzay 
Published: September 2021

AbstractPurposeThis study aimed to develop a new 3D dual-echo rosette k-space trajectory, specifically for ultra-short echo time (UTE) magnetic resonance imaging (MRI) applications. The direct imaging of the myelin bilayer, which has ultra-short transverse relaxation time (uT2), was acquired to test the performance of the proposed UTE sequence.Theory and MethodsThe rosette trajectory was developed based on rotations of a ‘petal-like’ pattern in the kx-kyplane, with oscillated extensions in kz-direction for 3D coverage. Five healthy volunteers were recruited and underwent ten dual-echo 3D rosette UTE scans with various echo times (TEs). Dual-exponential complex model fitting was performed on the magnitude data to separate uT2signals, with the output of uT2fraction, uT2value, and long T2value.ResultsThe reconstructed images’ signal contrast between whiate matter (WM) and grey matter (GM) increased with longer TEs. The WM regions had higher uT2fraction values than GM (10.9%±1.9% vs. 5.7%±2.4%). The uT2value was approximately 0.15 milliseconds in WM.ConclusionThe higher uT2fraction value in WM compared to GM demonstrated the ability of the proposed sequence to capture rapidly decaying signals.
Intrinsic neural activity predisposes susceptibility to a body illusion
Authors: Hsu Tzu-Yu , Zhou Ji-Fan , Northoff Georg , Yeh Su-Ling , Lane Timothy Joseph 
Published: September 2021

AbstractSusceptibility to the rubber hand illusion (RHI) varies. Thus far, however, there is no consensus as regards how to explain this variation. Previous studies, focused on the role of multisensory integration, have searched for neural correlates of the illusion. Those studies, however, have failed to identify a sufficient set of functionally specific neural correlates. An alternative explanation of the illusion is that it results from demand characteristics, chiefly variability in the disposition to respond to imaginative suggestion: the degree to which intrinsic neural activity allows for a blurring of boundaries between self and external objects. Some evidence suggests that frontal α power is one means of tracking neural instantiations of self; therefore, we hypothesized that the higher the frontal α power during eyes-closed resting state, the more stable the self. As a corollary, we infer that the more stable the self, the less susceptible are participants to a blurring of boundaries—to feeling that the rubber hand belongs to them. Indeed, we found that frontal α amplitude oscillations negatively correlate with susceptibility. Moreover, since α and δ oscillations seem to be associated in pathological states that allow for a blurring of boundaries between self and external objects, we conjectured that the high frontal α power observed in low-RHI participants is modulated by δ frequency oscillations. Indeed, we found this to be the case. Based on our findings we propose that the two explanatory frameworks might be complementary: that is, the neural correlates of multisensory integration might be necessary for the RHI, but a sufficient explanation requires investigation of variable intrinsic neural activity that acts to modulate how the brain responds to incompatible sensory stimuli.Highlights~Intrinsic frontal α power negatively correlates with susceptibility to the RHI.~Intrinsic α power modulated by δ oscillations varies with susceptibility to the RHI.~Sufficient explanation of RHI requires understanding of intrinsic neural dispositions that regulate the boundary between self and the external world.
iCOMIC: a graphical interface-driven bioinformatics pipeline for analyzing cancer omics data
Authors: Anilkumar Sithara Anjana , Maripuri Devi Priyanka , Moorthy Keerthika , Ganesh Sai Sruthi Amirtha , Philip Philge , Banerjee Shayantan , Sudhakar Malvika , Raman Karthik 
Published: September 2021

AbstractDespite the tremendous increase in omics data generated by modern sequencing technologies, their analysis can be tricky and often requires substantial expertise in bioinformatics. To address this concern, we have developed a user-friendly pipeline to analyze (cancer) genomic data that takes in raw sequencing data (FASTQ format) as input and outputs insightful statistics on the nature of the data. Our iCOMIC toolkit pipeline can analyze whole-genome and transcriptome data and is embedded in the popular Snakemake workflow management system. iCOMIC is characterized by a user-friendly GUI that offers several advantages, including executing analyses with minimal steps, eliminating the need for complex command-line arguments. The toolkit features many independent core workflows for both whole genomic and transcriptomic data analysis. Even though all the necessary, well-established tools are integrated into the pipeline to enable ‘out-of-the-box’ analysis, we provide the user with the means to replace modules or alter the pipeline as needed. Notably, we have integrated algorithms developed in-house for predicting driver and passenger mutations based on mutational context and tumor suppressor genes and oncogenes from somatic mutation data. We benchmarked our tool against Genome In A Bottle (GIAB) benchmark dataset (NA12878) and got the highest F1 score of 0.971 and 0.988 for indels and SNPs, respectively, using the BWA MEM - GATK HC DNA-Seq pipeline. Similarly, we achieved a correlation coefficient of r=0.85 using the HISAT2-StringTie-ballgown and STAR-StringTie-ballgown RNA-Seq pipelines on the human monocyte dataset (SRP082682). Overall, our tool enables easy analyses of omics datasets, with minimal steps, significantly ameliorating complex data analysis pipelines.Availability:https://github.com/RamanLab/iCOMIC