bluuebunny/crossref_metadata_2025 huggingface dataset:
Mask adherence and rate of COVID-19 across the United States
Authors: Fischer Charlie B. , Adrien Nedghie , Silguero Jeremiah J. , Hopper Julianne J. , Chowdhury Abir I. , Werler Martha M.
Published: January 2021

Mask wearing has been advocated by public health officials as a way to reduce the spread of COVID-19. In the United States, policies on mask wearing have varied from state to state over the course of the pandemic. Even as more and more government leaders encourage or even mandate mask wearing, many citizens still resist the notion. Our research examines mask wearing policy and adherence in association with COVID-19 case rates. We used state-level data on mask wearing policy for the general public and on proportion of residents who stated they always wear masks in public. For all 50 states and the District of Columbia (DC), these data were abstracted by month for April ⍰ September 2020 to measure their impact on COVID-19 rates in the subsequent month (May ⍰ October 2020). Monthly COVID-19 case rates (number of cases per capita over two weeks) >200 per 100,000 residents were considered high. Fourteen of the 15 states with no mask wearing policy for the general public through September reported a high COVID-19 rate. Of the 8 states with at least 75% mask adherence, none reported a high COVID-19 rate. States with the lowest levels of mask adherence were most likely to have high COVID-19 rates in the subsequent month, independent of mask policy or demographic factors. Mean COVID-19 rates for states with at least 75% mask adherence in the preceding month was 109.26 per 100,000 compared to 249.99 per 100,000 for those with less adherence. Our analysis suggests high adherence to mask wearing could be a key factor in reducing the spread of COVID-19. This association between high mask adherence and reduced COVID-19 rates should influence policy makers and public health officials to focus on ways to improve mask adherence across the population in order to mitigate the spread of COVID-19.
Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies
Authors: McAloon Conor G. , Wall Patrick , Butler Francis , Codd Mary , Gormley Eamonn , Walsh Cathal , Duggan Jim , Murphy T. Brendan , Nolan Philip , Smyth Breda , O’Brien Katie , Teljeur Conor , Green Martin J. , O’Grady Luke , Culhane Kieran , Buckley Claire , Carroll Ciara , Doyle Sarah , Martin Jennifer , More Simon J.
Published: January 2021

Background

Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling.

Methods

We analysed data from 140,204 contacts of 39861 cases in Ireland from 1st May to 1st December 2020. Only ‘close’ contacts were included in the analysis. A close contact was defined as any individual who had had > 15 minutes face-to-face (<2 m) contact with a case; any household contact; or any individual sharing a closed space for longer than 2 hours, in any setting.

Results

The number of contacts per case was overdispersed, the mean varied considerably over time, and was temporally associated with government interventions. Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days.

Discussion

These data were collected for a specific purpose and therefore any inferences must be made with caution. The data are representative of contact rates of cases, and not of the overall population. However, the data may be a more accurate indicator of the likely degree of onward transmission than might be the case if a random sample of the population were taken. Furthermore, since we analysed only the number of close contacts, the total number of contacts per case would have been higher. Nevertheless, this analysis provides useful information for monitoring the impact of government interventions on the number of contacts; for helping pre-empt increases or decreases in case numbers, and for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.
Survey of Contaminated Percutaneous Injuries in Anesthesia Practitioners
Authors: Zbeidy Reine , Livingstone Joshua , Shatz Vadim , Raveh Yehuda , Gad Rofayda , Nicolau-Raducu Ramona , Souki Fouad G.
Published: January 2021

Background

Anesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.

Methods

After institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).

Results

The overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50–68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings’ years of anesthesia practice was 69% (95% CI, 44–94) for 5-10 years, 62.5% (95% CI, 29–96) for 10-15 years, and 79% (95% CI, 63– 95) for greater than 15 years of practice.

35% (95% CI, 26–44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65–85) reported the incident at the time of injury. 59% (95% CI, 48–70) of injuries were due to hollow bore needles. 50% (95% CI, 39–61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.

Conclusion

Most anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting.
Analytical and clinical evaluation of antibody tests for SARS-CoV-2 serosurveillance studies used in Finland in 2020
Authors: Ekström Nina , Virta Camilla , Haveri Anu , Dub Timothée , Hagberg Lotta , Solastie Anna , Österlund Pamela , Vihervaara Terhi , Erlund Iris , Nohynek Hanna , Melin Merit
Published: January 2021

Background

Sensitive and highly specific antibody tests are critical for detection of SARS-CoV-2 antibodies especially in populations where seroprevalence is low.

Aim

To set up, optimize and evaluate the analytical and clinical performance of a new in-house microsphere immunoassay for measurement of IgG antibodies to SARS-CoV-2 nucleoprotein for assessment of population seroprevalence in Finland.

Methods

We set up a new in-house microsphere immunoassay (FMIA) with SARS-CoV-2 nucleoprotein and optimized its analytical performance. For evaluation of clinical performance, we tested sera collected in a well-characterized cohort of PCR positive-confirmed SARS-CoV-2 patients (n=89) with mostly mild symptoms, and before the COVID-19 pandemic (n=402), for nucleoprotein specific IgG concentrations by FMIA and a commercial chemiluminescent immunoassay and for neutralizing antibodies by the microneutralization test.

Results

The analytical performance of FMIA was established in terms of sensitivity, linearity and precision. FMIA discriminated between COVID-19 patient and control samples with high specificity (100%) and sensitivity (100%). We generated FMIA seropositivity cut-offs, 0.46 and 1.71 U/ml, for low- and high-seroprevalence settings, respectively. In addition, we obtained high level of agreement between FMIA results and results by the microneutralization test.

Conclusion

The fluorescent microsphere immunoassay showed excellent analytical and clinical performance and is well suited for serosurveillance studies of SARS-CoV-2. However, to optimize analytical sensitivity and clinical specificity of the assay, different seropositivity thresholds depending on the intended use of the assay and the target population, may be needed.
Determinants of the incidence and mortality rates of COVID-19 during the first six months of the pandemic; a cross-country study
Authors: Asem Noha , Ramadan Ahmed , Hassany Mohamed , Ghazy Ramy Mohamed , Abdallah Mohamed , Gamal Eman M. , Hassan Shaimaa , Kamal Nehal , Zaid Hala
Published: January 2021

COVID-19 pandemic raises an extraordinary challenge to the healthcare systems globally. The governments are taking key measures to constrain the corresponding health, social, and economic impacts, however, these measures vary depending on the nature of the crisis and country-specific circumstances.

Objectives

Considering different incidence and mortality rates across different countries, we aimed at explaining variance of these variables by performing accurate and precise multivariate analysis with aid of suitable predictors, accordingly, the model would proactively guide the governmental responses to the crisis.

Methods

Using linear and exponential time series analysis, this research aimed at studying the incidence and mortality rates of COVID-19 in 18 countries during the first six months of the pandemic, and further utilize multivariate techniques to explain the variance in monthly exponential growth rates of cases and deaths with aid of a set of different predictors: the recorded Google mobility trends towards six categories of places, daily average temperature, daily humidity, and key socioeconomic attributes of each country.

Results

The analysis showed that changes in mobility trends were the most significant predictors of the incidence and mortality rates, temperature and humidity were also significant but to a much lesser extent, on the other hand, the socioeconomic attributes did not contribute significantly to explaining different incidence and mortality rates across countries.

Conclusion

Changes in mobility trends across countries dramatically affected the incidence and mortality rates across different countries, thus, it might be used as a proxy measure of contact frequency.
Using Non-Pharmaceutical Interventions and High Isolation of Asymptomatic Carriers to Contain the Spread of SARS-CoV-2 in Nursing Homes
Authors: Schmidt Alec J. , García Yury , Pinheiro Diego , Reichert Tom , Nuño Miriam A.
Published: January 2021

Objective

Using a pandemic influenza model modified for COVID-19, this study investigated the degree of control over pre-symptomatic transmission that common non-pharmaceutical interventions (NPIs) would require to reduce the spread in long-term care facilities.

Methods

We created a stochastic compartmental SEIR model with Poisson-distributed transition states that compared the effect of R0, common NPIs, and isolation rates of pre-symptomatic carriers primarily on attack rate, peak cases, and timing in a 200-resident nursing home. Model sensitivity was assessed with 1st order Sobol’ indices.

Results

The most rigorous NPIs decreased the peak number of infections by 4.3 and delayed the peak by 9.7 days in the absence of pre-symptomatic controls. Reductions in attack rate were not likely, even with rigorous application of all defined NPIs, unless pre-symptomatic carriers were identified and isolated at rates exceeding 76%. Attack rate was most sensitive to the pre-symptomatic isolation rate (Sobol’ index > 0.7) and secondarily to R0.

Conclusions

Common NPIs delayed and reduced epidemic peaks. Reducing attack rates ultimately required efficient isolation of pre-symptomatic cases, including rapid antigen tests on a nearly daily basis. This must be accounted for in testing and contact tracing plans for group living settings.
The ferroxidase HEPHaestin in Lung cancer: Pathological Significance and Prognostic Value
Authors: Zacchi Paola , Belmonte Beatrice , Mangogna Alessandro , Morello Gaia , Scola Letizia , Martorana Anna , Borelli Violetta
Published: January 2021

Iron is a fundamental nutrient utilized by living cells to support several key cellular processes. Despite its paramount role to sustain cell survival, excess of labile iron availability can inflict severe cell damage via reactive oxygen species generation which, in turn, can promote neoplastic transformation. The lung is particularly sensitive to iron-induced oxidative stress, given the high oxygen tensions herein present. Moreover, cigarette smoke as well as air pollution particulate can function as vehicles of iron supply, leading to an iron dysregulation condition shown to be crucial in the pathogenesis of several respiratory diseases including lung cancer. Hephaestin (HEPH) belongs to a group of exocytoplasmic ferroxidases emerged to contribute to cellular iron homeostasis by favouring its export. Although HEPH can affect the concentration of intracellular iron labile pool, its expression in lung cancer and its influence on prognosis have not been investigated.

In this study we explored the expression pattern and prognostic value of HEPH in the most prevalent histotypes of lung cancers including lung adenocarcinoma and lung squamous cell carcinoma across in silico analyses using UALCAN, Gepia and Kaplan-Meier plotter bioninformatics. We took advantage of TIMER to assess the correlation between HEPH and tumour infiltrating immune and non-immune cells. Then we performed immunohistochemical analysis to dissect the presence of HEPH either in “healthy” and tumor lung tissues. Overall, our data suggest a positive correlation between higher level of HEPH expression with a favorable prognosis in both cancer histotypes.
Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform
Authors:   The OpenSAFELY Collaborative, Tazare John , Walker Alex J , Tomlinson Laurie , Hickman George , Rentsch Christopher T , Williamson Elizabeth J , Bhaskaran Krishnan , Evans David , Wing Kevin , Mathur Rohini , Wong Angel YS , Schultze Anna , Bacon Seb , Bates Chris , Morton Caroline E , Curtis Helen J , Nightingale Emily , McDonald Helen I , Mehrkar Amir , Inglesby Peter , Davy Simon , MacKenna Brian , Cockburn Jonathan , Hulme William J , Warren-Gash Charlotte , Bhate Ketaki , Nitsch Dorothea , Powell Emma , Mulick Amy , Forbes Harriet , Minassian Caroline , Croker Richard , Parry John , Hester Frank , Harper Sam , Eggo Rosalind M , Evans Stephen JW , Smeeth Liam , Douglas Ian J , Goldacre Ben
Published: January 2021

Background

Patients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19.

Methods

Working on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts.

Results

Amongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44).

Interpretation

Cardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures.

Funding

Wellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.
Integrated evaluation of telomerase activation and telomere maintenance across cancer cell lines
Authors: Hu Kevin , Ghandi Mahmoud , Huang Franklin W.
Published: January 2021

In cancer, telomere maintenance is critical for the development of replicative immortality. Using genome sequences from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer Project, we calculated telomere content across 1,299 cancer cell lines. We find that telomerase reverse transcriptase (TERT) expression correlates with telomere content in lung, central nervous system, and leukemia cell lines. Using CRISPR/Cas9 screening data, we show that lower telomeric content is associated with dependency of CST telomere maintenance components. Increased dependencies of shelterin members are associated with wild-typeTP53status. Investigating the epigenetic regulation ofTERT, we find widespread allele-specific expression in promoter-wildtype contexts.TERTpromoter-mutant cell lines exhibit hypomethylation at PRC2-repressed regions, suggesting a cooperative global epigenetic state in the reactivation of telomerase. By incorporating telomere content with genomic features across comprehensively characterized cell lines, we provide further insights into the role of telomere regulation in cancer immortality.
Searching for universal model of amyloid signaling motifs using probabilistic context-free grammars
Authors: Dyrka Witold , Gąsior-Głogowska Marlena , Szefczyk Monika
Published: January 2021

Background

Amyloid signaling motifs are a class of protein motifs which share basic structural and functional features despite lack of apparent sequence homology. They are hard to detect in large sequence databases either with the alignment-based profile methods (due to short length and diversity) or with generic amyloid- and prion-finding tools (due to insufficient discriminative power). We propose to address the challenge with a machine learning grammatical model capable of generalizing over diverse collections of unaligned yet related motifs.

Results

First, we introduce and test improvements to our probabilistic context-free grammar framework for protein sequences that allow for inferring more sophisticated models achieving high sensitivity at low false positive rates. Then, we infer universal grammars for a collection of recently identified bacterial amyloid signaling motifs and demonstrate that the method is capable of generalizing by successfully searching for related motifs in fungi. The results are compared to available alternative methods. Finally, we conduct spectroscopy analyses of selected peptides to verify their structural and functional relationship.

Conclusions

While the profile HMMs remain the method of choice for modeling homologous sets of sequences, PCFGs seem more suitable for building meta-family descriptors and extrapolating beyond the seed sample.
FIVEx: an interactive multi-tissue eQTL browser
Authors: Kwong Alan , Boughton Andrew P. , Wang Mukai , VandeHaar Peter , Boehnke Michael , Abecasis Gonçalo , Kang Hyun Min
Published: January 2021

Expression quantitative trait loci (eQTLs) characterize the associations between genetic variation and gene expression to provide insights into tissue-specific gene regulation. Interactive visualization of tissue-specific eQTLs can facilitate our understanding of functional variants relevant to disease-related traits. However, combining the multi-dimensional nature of eQTLs into a concise and informative visualization is challenging. Existing eQTL visualization tools provide useful ways to summarize the unprecedented scale of transcriptomic data but are not necessarily tailored to answer questions about the functional interpretations of trait-associated variants or other variants of interest. We developed FIVEx, an interactive eQTL browser with an intuitive interface tailored to the functional interpretation of associated variants. It features the ability to navigate seamlessly between different data views while providing relevant tissue- and locus-specific information to offer users a better understanding of population-scale multi-tissue transcriptomic profiles. Our implementation of the FIVEx browser on the Gene-Tissue Expression (GTEx) dataset provides important insights for understanding potential tissue-specific regulatory mechanisms underlying trait-associated signals.

Availability and implementation

A FIVEx instance visualizing GTEx v8 data can be found athttps://eqtl.pheweb.org. The FIVEx source code is open source under an MIT license athttps://github.com/statgen/fivex.
MAESTRO affords ‘breadth and depth’ for mutation testing
Authors: Gydush Gregory , Nguyen Erica , Bae Jin H. , Rhoades Justin , Reed Sarah C. , Shea Douglas , Xiong Kan , Liu Ruolin , Blewett Timothy , Yu Fangyan , Leong Ka Wai , Choudhury Atish D. , Stover Daniel G. , Tolaney Sara M. , Krop Ian E. , Love J. Christopher , Parsons Heather A. , Makrigiorgos G. Mike , Golub Todd R. , Adalsteinsson Viktor A.
Published: January 2021

The ability to assay large numbers of low-abundance mutations is crucial in biomedicine. Yet, the technical hurdles of sequencing multiple mutations at extremely high depth and accuracy remain daunting. For sequencing low-level mutations, it’s either ‘depth or breadth’ but not both. Here, we report a simple and powerful approach to accurately track thousands of distinct mutations with minimal reads. Our technique called MAESTRO (minoralleleenrichedsequencingthroughrecognitionoligonucleotides) employs massively-parallel mutation enrichment to empower duplex sequencing—one of the most accurate methods—to track up to 10,000 low-frequency mutations with up to 100-fold less sequencing. In example use cases, we show that MAESTRO could enable mutation validation from cancer genome sequencing studies. We also show that it could track thousands of mutations from a patient’s tumor in cell-free DNA, which may improve detection of minimal residual disease from liquid biopsies. In all, MAESTRO improves the breadth, depth, accuracy, and efficiency of mutation testing.
Hi-C Analyses with GENOVA: a case study with cohesin variants
Authors: van der Weide Robin H. , van den Brand Teun , Haarhuis Judith H.I. , Teunissen Hans , Rowland Benjamin D. , de Wit Elzo
Published: January 2021

Conformation capture-approaches like Hi-C can elucidate chromosome structure at a genome-wide scale. Hi-C datasets are large and require specialised software. Here, we present GENOVA: a user-friendly software package to analyse and visualise conformation capture data. GENOVA is an R-package that includes the most common Hi-C analyses, such as compartment and insulation score analysis. It can create annotated heatmaps to visualise the contact frequency at a specific locus and aggregate Hi-C signal over user-specified genomic regions such as ChIP-seq data. Finally, our package supports output from the major mapping-pipelines. We demonstrate the capabilities of GENOVA by analysing Hi-C data from HAP1 cell lines in which the cohesin-subunits SA1 and SA2 were knocked out. We find that ΔSA1 cells gain intra-TAD interactions and increase compartmentalisation. ΔSA2 cells have longer loops and a less compartmentalised genome. These results suggest that cohesinSA1 forms longer loops, while cohesinSA2 plays a role in forming and maintaining intra-TAD interactions. Our data supports the model that the genome is provided structure in 3D by the counter-balancing of loop formation on one hand, and compartmentalization on the other hand. By differentially controlling loops, cohesinSA1 and cohesinSA2 therefore also affect nuclear compartmentalization. We show that GENOVA is an easy to use R-package, that allows researchers to explore Hi-C data in great detail.
Phototrophy and carbon fixation in Chlorobi postdate the rise of oxygen
Authors: Ward LM , Shih PM
Published: January 2021

While most productivity on the surface of the Earth today is fueled by oxygenic photosynthesis, during the early parts of Earth history it is thought that anoxygenic photosynthesis—using compounds like ferrous iron or sulfide as electron donors—drove most global carbon fixation. Anoxygenic photosynthesis is still performed by diverse bacteria in niche environments today. Of these, the Chlorobi (formerly green sulfur bacteria) are often interpreted as being particularly ancient and are frequently proposed to have fueled the biosphere early in Earth history before the rise of oxygenic photosynthesis. Here, we perform comparative genomic, phylogenetic, and molecular clock analyses to determine the antiquity of the Chlorobi and their characteristic phenotypes. We show that contrary to common assumptions, the Chlorobi clade is relatively young, with anoxygenic phototrophy, carbon fixation via the rTCA pathway, and iron oxidation all significantly postdating the rise of oxygen ~2.3 billion years ago. The Chlorobi therefore could not have fueled the Archean biosphere, but instead represent a relatively young radiation of organisms which likely acquired the capacity for anoxygenic photosynthesis and other traits via horizontal gene transfer sometime after the evolution of oxygenic Cyanobacteria.
DEPP: Deep Learning Enables Extending Species Trees using Single Genes
Authors: Jiang Yueyu , Balaban Metin , Zhu Qiyun , Mirarab Siavash
Published: January 2021

Placing new sequences onto reference phylogenies is increasingly used for analyzing environmental samples, especially microbiomes. However, existing placement methods have a fundamental limitation: they assume that query sequences have evolved using specific models directly on the reference phylogeny. Thus, they can place single-gene data (e.g., 16S rRNA amplicons) onto their own gene tree. This practice is a proxy for a more ambitious goal: extending a (genome-wide) species tree given data from individual genes. No algorithm currently addresses this challenging problem. Here, we introduce Deep-learning Enabled Phylogenetic Placement (DEPP), an algorithm that learns to extend species trees using single genes without pre-specified models. We show that DEPP updates the multi-locus microbial tree-of-life with single genes with high accuracy. We further demonstrate that DEPP can achieve the long-standing goal of combining 16S and metagenomic data onto a single tree, enabling community structure analyses that were previously impossible and producing robust patterns.
Automatic classification of ICA components from infant EEG using MARA
Authors: Marriot Haresign I. , Phillips E. , Whitehorn M. , Noreika V. , Jones E.J.H. , Leong V. , Wass S.V.
Published: January 2021

Automated systems for identifying and removing non-neural ICA components are growing in popularity among adult EEG researchers. Infant EEG data differs in many ways from adult EEG data, but there exists almost no specific system for automated classification of source components from paediatric populations. Here, we adapt one of the most popular systems for adult ICA component classification for use with infant EEG data. Our adapted classifier significantly outperformed the original adult classifier on samples of naturalistic free play EEG data recorded from 10 to 12-month-old infants, achieving agreement rates with the manual classification of over 75% across two validation studies (n=44, n=25). Additionally, we examined both classifiers ability to remove stereotyped ocular artifact from a basic visual processing ERP dataset, compared to manual ICA data cleaning. Here the new classifier performed on level with expert manual cleaning and was again significantly better than the adult classifier at removing artifact whilst retaining a greater amount of genuine neural signal, operationalised through comparing ERP activations in time and space. Our new system (iMARA) offers developmental EEG researchers a flexible tool for automatic identification and removal of artifactual ICA components.
Modulation of auditory responses by visual inputs in the mouse auditory cortex
Authors: Sharma Sudha , Srivastava Hemant Kumar , Bandyopadhyay Sharba
Published: January 2021

So far, our understanding on the role of the auditory cortex (ACX) in processing visual information has been limited to infragranular layers of the ACX, which have been shown to respond to visual stimulation. Here, we investigate the neurons in supragranular layers of the mouse ACX using 2-photon calcium imaging. Contrary to previous reports, here we show that more than 20% of responding neurons in layer2/3 of the ACX respond to full-field visual stimulation. These responses occur by both excitation and hyperpolarization. The primary ACX (A1) has a greater proportion of visual responses by hyperpolarization compared to excitation likely driven by inhibitory neurons of the infragranular layers of the ACX rather than local layer 2/3 inhibitory neurons. Further, we found that more than 60% of neurons in the layer 2/3 of A1 are multisensory in nature. We also show the presence of multisensory neurons in close proximity to exclusive auditory neurons and that there is a reduction in the noise correlations of the recorded neurons during multisensory presentation. This is evidence in favour of deep and intricate visual influence over auditory processing. The results have strong implications for decoding visual influences over the early auditory cortical regions.

Significance statement

To understand, what features of our visual world are processed in the auditory cortex (ACX), understanding response properties of auditory cortical neurons to visual stimuli is important. Here, we show the presence of visual and multisensory responses in the supragranular layers of the ACX. Hyperpolarization to visual stimulation is more commonly observed in the primary ACX. Multisensory stimulation results in suppression of responses compared to unisensory stimulation and an overall decrease in noise correlation in the primary ACX. The close-knit architecture of these neurons with auditory specific neurons suggests the influence of non-auditory stimuli on the auditory processing.
Antidiabetic action of Mcy protein through the regulation of number and affinity of insulin receptors
Authors: Marella Saritha , Kotha Peddanna , Nabi S. Abdul , Girish B.P. , Badri Kameswara Rao , Chippada Apparao
Published: January 2021

Evidence based immunological cross-reactivity studies and anti-diabetic investigations have suggested the presence of insulin-like peptides in plants. Mcy protein, isolated from the fruits ofMomordicacymbalaria, was shown to have antihyperglycemic, antihyperlipidemic activities along with renal as well as hepatoprotective activities in Streptozotocin induced diabetic rats.Mcy protein was shown to have insulin like and/or insulin secretagoguestructure and/or functions. Hence, the present study was conducted to elucidate molecular mechanism wherebyMcy protein elicits its therapeutic role and also to know whether the Mcyprotein has any structural and functional similarity with insulin. Results of our experiments revealed that the Mcyprotein is insulin like protein. Further, we assessed the effect of treatment of Mcy protein on the levels of glucose transport (glucose transporter (GLUT-2) and on the levels of key regulators of glucose and lipid metabolisms like hepatic glucokinase (GK) and sterol regulated element binding protein-1c (SREBP-1c). Our findings demonstrated that Mcy protein decreased the elevated expressions of GK, SREBP-1c and GLUT-2 that were observed in diabetic animals. Insulin-receptor binding studies using rat erythrocytes demonstrated that mean specific binding of insulin with insulin receptors was significantly increased in Mcy treated diabetic rats when compared to diabetic control rats. Scatchard analyses of insulin-binding studies yielded curvilinear plots, and the number of receptor sites per cell was found to be 180±21.1 in Mcy treated diabetic animals calculated to be significantly superior to that of diabetic control animals. Kinetic analyses also revealed an increase in the average receptor affinity of erythrocytes from Mcy treated rats compared to diabetic control rats suggesting acute alteration in the number and affinity of insulin receptors on the membranes of erythrocytes.
SARS-CoV-2 seroprevalence among healthcare workers in general hospitals and clinics in Japan
Authors: Yoshihara Tatsuya , Ito Kazuya , Zaitsu Masayoshi , Chung Eunhee , Aoyagi Izumi , Kaji Yoshikazu , Tsuru Tomomi , Yonemura Takuma , Yamaguchi Koji , Nakayama Shinichi , Tanaka Yosuke , Yurino Nobuo , Koyanagi Hideki , Matsuki Shunji , Urae Ryuji , Irie Shin
Published: January 2021

Coronavirus disease 2019 (COVID-19) has become a serious public health problem worldwide. However, little is known about the prevalence of COVID-19 among healthcare workers in Japan. We aimed to examine the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) antibodies among 2,160 healthcare workers in general hospitals and clinics in Japan. The prevalence of SARS-CoV-2 immunoglobulin G was 1.2% in August and October 2020, which is relatively higher than that in the general population in Japan. Because of the higher risk of COVID-19 infection, healthcare workers should be the top priority for further social support and vaccination against SARS-CoV-2.
ENOX2 NADH Oxidase: A BCR-ABL1-dependent cell surface and secreted redox protein in chronic myeloid leukemia (CML)
Authors: Baykal-Köse Seda , Voldoire Maud , Desterke Christophe , Sorel Nathalie , Cayssials Emilie , Johnson-Ansah Hyacinthe , Guerci-Bresler Agnes , Bennaceur-Griscelli Annelise , Chomel Jean-Claude , Turhan Ali G
Published: January 2021

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm caused by the acquisition ofBCR-ABL1fusion in a hematopoietic stem cell. We identified theENOX2gene as up-regulated inBCR-ABL1-expressing UT-7 cell lines through a transcriptome assay. The oncofoetal ENOX2 protein (Ecto-Nicotinamide Adenine Dinucleotide Oxidase Disulfide Thiol Exchanger 2) is expressed on the external plasma membrane surface of cancer cells and can be released in cancer patients’ serum. Considering these data, we studied ENOX2 expression in CML cell lines and patients using quantitative RT-PCR, western-blots, the ELISA method, and transcriptomic dataset reanalysis. We confirmed increasedENOX2mRNA expression in theBCR-ABL1-expressing UT-7 cell line. Comparable results were obtained in CML patients at diagnosis. Western-blot analyses on UT-7 and TET-inducible Ba/F3 cell lines established the up-regulation of ENOX2 protein. BCR-ABL1 has been found to induce ENOX2 overexpression in a kinase-dependent manner. In a series of 41 patients with CML, ELISA assays showed a highly significant increase of ENOX2 protein levels in the plasma of patients with CML (p < 0.0001) as compared to controls (n=28). Transcriptomic dataset (GSE4170) reanalyzes have shown specificENOX2mRNA overexpression in the chronic phase of the disease. Bioinformatic analyses identified several genes whose mRNA expression was positively correlated toENOX2. Some of them encode proteins involved in cellular functions compatible with the growth deregulation observed in CML. All in all, our results demonstrate for the first time the upregulation of a secreted Redox protein in a BCR-ABL1-dependent manner in CML. Our data suggest that ENOX2 (through its transcriptional program) plays a significant role in the BCR-ABL1 leukemogenesis. Further studies are required to clarify the relationship between BCR-ABL1 and ENOX2.
Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples
Authors: Stiehl Thomas , Marciniak-Czochra Anna
Published: January 2021

Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.
An Efficient Algorithm for Estimating Population History from Genetic Data
Authors: Rogers Alan R.
Published: January 2021

The Legofit statistical package uses genetic data to estimate parameters describing population history. Previous versions used computer simulations to estimate probabilities, an approach that limited both speed and accuracy. This article describes a new deterministic algorithm, which makes Legofit faster and more accurate. The speed of this algorithm declines as model complexity increases. With very complex models, the deterministic algorithm is slower than the stochastic one. In an application to simulated data sets, the estimates produced by the deterministic and stochastic algorithms were essentially identical. Reanalysis of a human data set replicated the findings of a previous study and provided increased support for the hypotheses that (a) early modern humans contributed genes to Neanderthals, and (b) a “superarchaic” population (which separated from all other humans early in the Pleistocene) was either large or deeply subdivided.
Disaggregating proportional multistate lifetables by population heterogeneity to estimate intervention impacts on inequalities
Authors: Andersen Patrick , Mizdrak Anja , Wilson Nick , Davies Anna , Bablani Laxman , Blakely Tony
Published: January 2021

Background

Simulation models can be used to quantify the projected health impact of interventions. Quantifying heterogeneity in these impacts, for example by socioeconomic status, is important to understand impacts on health inequalities.

We aim to disaggregate one type of Markov macro-simulation model, the proportional multistate lifetable, ensuring that under business-as-usual (BAU) the sum of deaths across disaggregated strata in each time step returns the same as the initial non-disaggregated model. We then demonstrate the application by deprivation quintiles for New Zealand (NZ), for: hypothetical interventions (50% lower all-cause mortality, 50% lower coronary heart disease mortality) and a dietary intervention to substitute 59% of sodium with potassium chloride in the food supply.

Methods

We developed a disaggregation algorithm that iteratively rescales mortality, incidence and case fatality rates by time-step of the model to ensure correct total population counts were retained at each step.

To demonstrate the algorithm on deprivation quintiles in NZ, we used the following inputs: overall (non-disaggregated) all-cause mortality &morbidity rates, coronary heart disease incidence &case fatality rates; stroke incidence &case fatality rates. We also obtained rate ratios by deprivation for these same measures. Given all-cause and cause-specific mortality rates by deprivation quintile, we derived values for the incidence, case fatality and mortality rates for each quintile, ensuring rate ratios across quintiles and the total population mortality and morbidity rates were returned when averaged across groups.

The three interventions were then run on top of these scaled BAU scenarios.

Results

The algorithm exactly disaggregated populations by strata in BAU. The intervention scenario life years and health adjusted life years (HALYs) gained differed slightly when summed over the deprivation quintile compared to the aggregated model, due to the stratified model (appropriately) allowing for differential background mortality rates by strata. Modest differences in health gains (health adjusted life years) resulted from rescaling of sub-population mortality and incidence rates to ensure consistency with the aggregate population.

Conclusion

Policy makers ideally need to know the effect of population interventions estimated both overall, and by socioeconomic and other strata. We demonstrate a method and provide code to do this routinely within proportional multistate lifetable simulation models and similar Markov models.
Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries
Authors: Kong Jude D. , Tekwa Edward W. , Gignoux-Wolfsohn Sarah A.
Published: January 2021

Objective

To assess whether the basic reproduction number (R0) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors characterize initial vulnerability to the virus.

Methods

We fit logistic growth curves to reported daily case numbers, up to the first epidemic peak. This fitting estimates R0. We then use a generalized additive model to discern the effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated R0.

Findings

We found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors-population between 20-34 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality-as having strong relationships with R0. An intermediate level of youth and GINI inequality are associated with high R0, while high city population and high social media use are associated with high R0. Environmental and climate factors were not found to have strong relationships with R0.

Conclusion

Studies that aim to measure the effectiveness of interventions should account for the intrinsic differences between populations.
Meta-analysis reveals consistent immune response patterns in COVID-19 infected patients at single-cell resolution
Authors: Garg Manik , Li Xu , Moreno Pablo , Papatheodorou Irene , Shu Yuelong , Brazma Alvis , Miao Zhichao
Published: January 2021

A number of single-cell RNA studies looking at the human immune response to the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been recently published. However, the number of samples used in each individual study typically is small, moreover the technologies and protocols used in different studies vary, thus somewhat restricting the range of conclusions that can be made with high confidence. To better capture the cellular gene expression changes upon SARS-CoV-2 infection at different levels and stages of disease severity and to minimise the effect of technical artefacts, we performed meta-analysis of data from 9 previously published studies, together comprising 143 human samples, and a set of 16 healthy control samples (10X). In particular, we used generally accepted immune cell markers to discern specific cell subtypes and to look at the changes of the cell proportion over different disease stages and their consistency across the studies. While half of the observations reported in the individual studies can be confirmed across multiple studies, half of the results seem to be less conclusive. In particular, we show that the differentially expressed genes consistently point to upregulation of type I Interferon signal pathway and downregulation of the mitochondrial genes, alongside several other reproducibly consistent changes. We also confirm the presence of expanded B-cell clones in COVID-19 patients, however, no consistent trend in T-cell clonal expansion was observed.
Homozygosity at its Limit: Inbreeding Depression in WildArabidopsis arenosaPopulations
Authors: Barragan A. Cristina , Collenberg Maximilian , Schwab Rebecca , Kerstens Merijn , Bezrukov Ilja , Bemm Felix , Požárová Doubravka , Kolář Filip , Weigel Detlef
Published: January 2021

New combinations of genetic material brought together through hybridization can lead to unfit offspring as a result of outbreeding or inbreeding depression. In selfing plants such asArabidopsis thaliana, outbreeding depression is typically the result of pairwise deleterious epistatic interactions between two alleles that can geographically co-occur. What remains elusive is how often alleles resulting in genetic incompatibilities co-occur in natural populations of outcrossing plant species. To address this question, we screened over two thousand five hundred wildArabidopsis arenosahybrid plants in search for potential genetic mismatches. We show that although abnormal deleterious phenotypes are common, the transcriptional profiles of these abnormalA. arenosaplants differ substantially from those seen in incompatibleA. thalianahybrids. The abnormal hybrid phenotypes inA. arenosahad different underlying genetic architectures, yet a repeated theme was increased homozygosity, indicating that inbreeding rather than outbreeding depression gives rise to some of the deleterious phenotypes segregating in wildA. arenosapopulations.