bluuebunny/crossref_metadata_2025_split huggingface dataset:
Arrhythmia variant associations and reclassifications in the eMERGE-III sequencing study
Authors: Glazer Andrew M. , Davogustto Giovanni , Shaffer Christian M. , Vanoye Carlos G. , Desai Reshma R. , Farber-Eger Eric H. , Dikilitas Ozan , Shang Ning , Pacheco Jennifer A. , Yang Tao , Muhammad Ayesha , Mosley Jonathan D. , Driest Sara L. Van , Wells Quinn S. , Rinke Lauren Lee , Kalash Olivia R. , Wada Yuko , Bland Sarah , Yoneda Zachary T. , Mitchell Devyn W. , Kroncke Brett M. , Kullo Iftikhar J. , Jarvik Gail P. , Gordon Adam S. , Larson Eric B. , Manolio Teri A. , Mirshahi Tooraj , Luo Jonathan Z. , Schaid Daniel , Namjou Bahram , Alsaied Tarek , Singh Rajbir , Singhal Ashutosh , Liu Cong , Weng Chunhua , Hripcsak George , Ralston James D. , McNally Elizabeth M. , Chung Wendy K. , Carrell David S. , Leppig Kathleen A. , Hakonarson Hakon , Sleiman Patrick , Sohn Sunghwan , Glessner Joseph ,   the eMERGE Network, Denny Joshua , Wei Wei-Qi , George Alfred L. , Shoemaker M. Benjamin , Roden Dan M. 
Published: April 2021

AbstractIn 21,846 eMERGE-III participants, sequencing 10 arrhythmia syndrome disease genes identified 123 individuals with pathogenic or likely pathogenic (P/LP) variants. Compared to non-carriers, P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records (EHRs). Fifty one participants had variant results returned. Eighteen of these 51 participants had inherited arrhythmia syndrome diagnoses (primarily long QT syndrome), and 11/18 of these diagnoses were made only after variant results were returned. Afterin vitrofunctional evaluation of 50 variants of uncertain significance (VUS), we reclassified 11 variants: 3 to likely benign and 8 to P/LP. As large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, EHR phenotypes, andin vitrofunctional studies.
Cost-effectiveness of Stockholm3 test and magnetic resonance imaging in prostate cancer screening: a microsimulation study
Authors: Hao Shuang , Heintz Emelie , Östensson Ellinor , Discacciati Andrea , Jäderling Fredrik , Grönberg Henrik , Eklund Martin , Nordström Tobias , Clements Mark 
Published: April 2021

AbstractObjectiveAssess the cost-effectiveness of no screening and quadrennial magnetic resonance imaging (MRI)-based screening for prostate cancer using either Stockholm3 or prostate-specific antigen (PSA) test as a reflex test.MethodsTest characteristics were estimated from the STHLM3-MR study (NCT03377881). A cost-utility analysis was conducted from a lifetime societal perspective using a microsimulation model for men aged 55-69 in Sweden for no screening and three quadrennial screening strategies, including: PSA≥3ng/mL; and Stockholm3 with reflex test thresholds of PSA≥1.5 and 2ng/mL. Men with a positive test had an MRI, and those MRI positive had combined targeted and systematic biopsies. Predictions included the number of tests, cancer incidence and mortality, costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs). Uncertainties in key parameters were assessed using sensitivity analyses.ResultsCompared with no screening, the screening strategies were predicted to reduce prostate cancer deaths by 7-9% across a lifetime and were considered to be moderate costs per QALY gained in Sweden. Using Stockholm3 with a reflex threshold of PSA≥2ng/mL resulted in a 60% reduction in MRI compared with screening using PSA. This Stockholm3 strategy was cost-effective with a probability of 70% at a cost-effectiveness threshold of €47,218 (500,000 SEK).ConclusionsAll screening strategies were considered to be moderate costs per QALY gained compared with no screening. Screening with Stockholm3 test at a reflex threshold of PSA≥2ng/mL and MRI was predicted to be cost-effective in Sweden. Use of the Stockholm3 test may reduce screening-related harms and costs while maintaining the health benefits from early detection.
First-in-Human Trial of a Recombinant Stabilized Prefusion SARS-CoV-2 Spike Protein Vaccine with Adjuvant of Aluminum Hydroxide and CpG 1018
Authors: Hsieh Szu-Min , Liu Wang-Da , Huang Yu-Shan , Lin Yi-Jiun , Hsieh Erh-Fang , Lian Wei-Cheng , Chen Charles , Tai I-Chen , Chang Shan-Chwen 
Published: April 2021

AbstractDesignThis is a phase 1, dose-escalation open-label trial to evaluate the safety and immunogenicity of MVC-COV1901, a recombinant stabilized prefusion SARS-CoV-2 spike (S-2P) protein vaccine with adjuvant of aluminum hydroxide and CpG 1018.MethodsWe enrolled 45 healthy adults from 20 to 49 years of age to be administered with two vaccinations of MVC-COV1901 in a low dose (LD), middle dose (MD), and high dose (HD) of spike protein at 28 days apart. There were 15 participants in each dose group, and all of them were followed up for 28 days after the second vaccination at the time of interim analysis. Adverse events (AEs) and laboratory data were recorded for safety evaluation. Blood samples were collected for wild-type SARS-CoV-2 and pseudovirus neutralization assays as well as SARS-CoV-2 spike-specific immunoglobulin G (IgG) at various times. Overall, the study duration will be 7 months.ResultsSolicited events were mostly mild and similar in the participants of all three dose groups. No subject experienced fever. There were no serious nor adverse events of special interest at the time point of this interim report. After the second vaccination, the SARS-CoV-2 spike specific IgG titers increased with peak geometric mean titers at 7178.245 (LD), 7746.086 (MD), and 11220.58 (HD), respectively. Serum neutralizing activity was detected by two methods in all participants of MD and HD groups, with geometric mean values generally comparable to those of a panel of control convalescent serum specimens. All of the participants in the MD and HD groups were seroconverted after the second vaccination.ConclusionsThe MVC-COV1901 vaccine is safe and elicits remarkable immune responses especially in the MD and HD groups.Trial RegistrationClinicalTrials.gov NCT 04487210
The prevalence and density of asymptomatic Plasmodium falciparum infections among children and adults in three communities of western Kenya
Authors: Salgado Christina , Ayodo George , Macklin Michael D. , Gould Meetha P. , Nallandhighal Srinivas , Odhiambo Eliud O. , Obala Andrew , O’Meara Prudhomme Wendy , John Chandy C. , Tran Tuan M. 
Published: April 2021

ABSTRACTBackgroundFurther reductions in malaria incidence as more countries approach malaria elimination require the identification and treatment of asymptomatic individuals who carry mosquito-infective Plasmodium gametocytes that are responsible for furthering malaria transmission. Assessing the relationship between total parasitemia and gametocytemia in field surveys can provide insight as to whether detection of low-density, asymptomatic Plasmodium falciparum infections using sensitive molecular methods can sufficiently detect the majority of infected individuals who are potentially capable of onward transmission.MethodsIn a cross-sectional survey of 1,354 healthy children and adults in three communities in western Kenya across a gradient of malaria transmission (Ajigo, Webuye, and Kapsisywa-Kipsamoite), we screened for asymptomatic P. falciparum infections by rapid diagnostic tests, blood smear, and quantitative PCR of dried blood spots targeting the varATS gene in genomic DNA. A multiplex quantitative reverse-transcriptase PCR assay targeting female and male gametocyte genes (pfs25, pfs230p), a gene with a transcriptional pattern restricted to asexual blood-stages (piesp2), and human GAPDH was also developed to determine total parasite and gametocyte densities among parasitemic individuals.ResultsThe prevalence of varATS-detectable asymptomatic infections was greatest in Ajigo (42%), followed by Webuye (10%). Only two infections were detected in Kapsisywa. No infections were detected in Kipsamoite. Across all communities, children aged 11-15 years account for the greatest proportion total and sub-microscopic asymptomatic infections. In younger age groups, the majority of infections were detectable by microscopy, while 68% of asymptomatically infected adults (>21 years old) had sub-microscopic parasitemia. Piesp2-derived parasite densities correlated poorly with microscopy-determined parasite densities in patent infections relative to varATS-based detection. In general, both male and female gametocytemia increased with increasing varATS-derived total parasitemia. A substantial proportion (41.7%) of individuals with potential for onward transmission had qPCR-estimated parasite densities below the limit of microscopic detection but above the detectable limit of varATS qPCR.ConclusionsThis assessment of parasitemia and gametocytemia in three communities with different transmission intensities revealed evidence of a substantial sub-patent infectious reservoir among asymptomatic carriers of P. falciparum. Experimental studies are needed to definitively determine whether the low-density infections in communities such as Ajigo and Webuye contribute significantly to malaria transmission.
Development of Childhood Asthma Prediction Models using Machine Learning Approaches
Authors: Kothalawala Dilini M. , Murray Clare S. , Simpson Angela , Custovic Adnan , Tapper William J. , Arshad S. Hasan , Holloway John W. , Rezwan Faisal I. 
Published: April 2021

ABSTRACTBackgroundWheeze is common in early life and often transient. It is difficult to identify which children will experience persistent symptoms and subsequently develop asthma. Machine learning approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models.ObjectiveTo apply machine learning approaches for predicting school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model).MethodsData on clinical symptoms and environmental exposures were collected from children enrolled in the Isle of Wight Birth Cohort (N=1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified the optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art machine learning classification algorithms were used to develop the models and the results were compared. To optimize the models, training was performed by applying 5-fold cross-validation, imputation and resampling. Predictive performances were evaluated on the test set and externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort.ResultsRFE identified eight and 12 predictors for the CAPE and CAPP models, respectively. The best predictive performance was demonstrated by a Support Vector Machine (SVM) algorithm for both the CAPE model (area under the receiver operating curve, AUC=0.71) and CAPP model (AUC=0.82). Both models demonstrated good generalisability in MAAS (CAPE 8YR=0.71, 11YR=0.71, CAPP 8YR=0.83, 11YR=0.79).ConclusionUsing machine learning approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma.
Covid-19, non-Covid-19 and excess mortality rates not comparable across countries
Authors: Kelly Gabrielle , Petti Stefano , Noah Norman 
Published: April 2021

AbstractEvidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported Covid-19 mortality rates, is derived from mortality data. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015-2020 were tabulated for 35 countries together with economic, health, demographic, and government response stringency index variables. Residual mortality rates (RMR) in 2020 were calculated as excess mortality minus reported mortality rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015-2019. Differences in RMR are differences not attributed to reported Covid-19. For about half the countries, RMR’s were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, population density and proportion of female smokers were positively associated with both Covid-19 and excess mortality while the human development index and proportion of male smokers were negatively associated with both. RMR was not associated with any of the investigated variables. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries. This may be due to differences in Covid-19 death reporting and in addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.
A BIBLIOMETRIC ANALYSIS OF RHEUMATOLOGY AND COVID-19 RESEARCHES
Authors: Pasin Ozge , Pasin Tugce 
Published: April 2021

ABSTRACTObjectivesCOVID-19 has had a substantial impact on rheumatology. This study provides a general overview of studies on rheumatology and COVID-19.MethodsData were taken from the Web of Science (WoS) website. Analysis and network visualization mapping processes were carried out using VOSviewer. A total of 234 publications were analyzed, and the correlations between citation numbers and reference counts, usage counts and page numbers were analyzed with Spearman correlation coefficients.ResultsThe average number of citations per item was 6.03. The studies were cited 1,411 times in total, and 1,121 times without self-citations. The countries with the highest number of publications on rheumatology and COVID-19 were the USA and England; the countries with the highest number of citations were Italy and the USA, and Jinoos Yazdany was the most cited author. The Annals of the Rheumatic Diseases was the most cited journal, whereas the highest number of articles on rheumatology and COVID-19 were published in Arthritis and Rheumatology.ConclusionsBibliometric analysis of rheumatology and COVID-19 can be useful to future studies because it provides a general perspective on the studies. This study provides an insight into the development of publications on rheumatology during the COVID-19 pandemic.
Using deep learning algorithms to simultaneously identify right and left ventricular dysfunction from the electrocardiogram
Authors: Vaid Akhil , Johnson Kipp W , Badgeley Marcus A , Somani Sulaiman S , Bicak Mesude , Landi Isotta , Russak Adam , Zhao Shan , Levin Matthew , Freeman Robert S , Charney Alexander W , Kukar Atul , Kim Bette , Danilov Tatyana , Lerakis Stamatios , Argulian Edgar , Narula Jagat , Nadkarni Girish N , Glicksberg Benjamin S 
Published: April 2021

AbstractBackgroundRapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECG) can assist diagnostic workflow. However, DL tools to estimate right ventricular (RV) function do not exist, while ones to estimate left ventricular (LV) function are restricted to quantification of very low LV function only.ObjectivesThis study sought to develop deep learning models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.MethodsA multi-center study was conducted with data from five New York City hospitals; four for internal testing and one serving as external validation. We created novel DL models to classify Left Ventricular Ejection Fraction (LVEF) into categories derived from the latest universal definition of heart failure, estimate LVEF through regression, and predict a composite outcome of either RV systolic dysfunction or RV dilation.ResultsWe obtained echocardiogram LVEF estimates for 147,636 patients paired to 715,890 ECGs. We used Natural Language Processing (NLP) to extract RV size and systolic function information from 404,502 echocardiogram reports paired to 761,510 ECGs for 148,227 patients.For LVEF classification in internal testing, Area Under Curve (AUC) at detection of LVEF<=40%, 40%<LVEF<=50%, and LVEF>50% was 0.94 (95% CI:0.94-0.94), 0.82 (0.81-0.83), and 0.89 (0.89-0.89) respectively. For external validation, these results were 0.94 (0.94-0.95), 0.73 (0.72-0.74) and 0.87 (0.87-0.88). For regression, the mean absolute error was 5.84% (5.82-5.85) for internal testing, and 6.14% (6.13-6.16) in external validation. For prediction of the composite RV outcome, AUC was 0.84 (0.84-0.84) in both internal testing and external validation.ConclusionsDL on ECG data can be utilized to create inexpensive screening, diagnostic, and predictive tools for both LV/RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography, and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.
Using 2D Video-based Pose Estimation for Automated Prediction of Autism Spectrum Disorders in Preschoolers
Authors: Kojovic Nada , Natraj Shreyasvi , Mohanty Sharada Prasanna , Maillart Thomas , Schaer Marie 
Published: April 2021

ABSTRACTClinical research in autism has recently witnessed promising digital phenotyping results, mainly focused on single feature extraction, such as gaze, head turn on name-calling or visual tracking of the moving object. The main drawback of these studies is the focus on relatively isolated behaviors elicited by largely controlled prompts. We recognize that while the diagnosis process understands the indexing of the specific behaviors, ASD also comes with broad impairments that often transcend single behavioral acts. For instance, the atypical nonverbal behaviors manifest through global patterns of atypical postures and movements, fewer gestures used and often decoupled from visual contact, facial affect, speech. Here, we tested the hypothesis that a deep neural network trained on the non-verbal aspects of social interaction can effectively differentiate between children with ASD and their typically developing peers. Our model achieves an accuracy of 80.9% (F1 score: 0.818; precision: 0.784; recall: 0.854) with the prediction probability positively correlated to the overall level of symptoms of autism in social affect and repetitive and restricted behaviors domain. Provided the non-invasive and affordable nature of computer vision, our approach carries reasonable promises that a reliable machine-learning-based ASD screening may become a reality not too far in the future.
Suppression of endothelial miR-22-3p mediates non-small cell lung cancer cell-induced angiogenesis
Authors: Gu Yuan , Pais Gianni , Becker Vivien , Körbel Christina , Ampofo Emmanuel , Ebert Elke , Hohneck Johannes , Ludwig Nicole , Meese Eckart , Bohle Rainer M. , Zhao Yingjun , Menger Michael D. , Laschke Matthias W. 
Published: April 2021

AbstractMicroRNAs (miRNAs) expressed in endothelial cells (ECs) are powerful regulators of angiogenesis, which is essential for tumor growth and metastasis. Here, we demonstrated that miR-22-3p (miR-22) is preferentially and highly expressed in ECs, while its endothelial level is significantly down-regulated in human non-small cell lung cancer (NSCLC) tissues when compared to matched non-tumor lung tissues. This reduction of endothelial miR-22 is induced by NSCLC cell-secreted tumor necrosis factor (TNF)-α and interleukin (IL)-1β. Endothelial miR-22 functions as a potent angiogenesis inhibitor that inhibits all the key angiogenic activities of ECs and consequently NSCLC growth through directly targeting sirtuin (SIRT)1and fibroblast growth factor receptor (FGFR)1in ECs, leading to inactivation of AKT/mammalian target of rapamycin (mTOR) signaling. These novel findings provide insight into the molecular mechanisms of NSCLC angiogenesis and indicate that endothelial miR-22 represents a potential target for the future anti-angiogenic treatment of NSCLC.
MSABrowser: dynamic and fast visualization of sequence alignments, variations, and annotations
Authors: Torun Furkan M. , Bilgin Halil I. , Kaplan Oktay I. 
Published: April 2021

SummarySequence alignment is an excellent way to visualize the similarities and differences between DNA, RNA, or protein sequences, yet it is currently difficult to jointly view sequence alignment data with genetic variations, modifications such as post-translational modifications, and annotations (i.e. protein domains). Here, we develop the MSABrowser tool that makes it easy to co-visualize genetic variations, modifications, and annotations on the respective positions of amino acids or nucleotides in pairwise or multiple sequence alignments. MSABrowser is developed entirely in JavaScript and works on any modern web browser at any platform, including Linux, Mac OS X, and Windows systems without any installation. MSABrowser is also freely available for the benefit of the scientific community.Availability and implementationMSABrowser is released as open-source and web-based software under GNU General Public License, version 3.0 (GPLv3). The visualizer, documentation, all source codes, and examples are available athttp://thekaplanlab.github.io/and GitHub repositoryhttps://github.com/thekaplanlab/msabrowser.Supplementary informationSupplementary data are available online.
Intragenomic sequence variations in the second internal transcribed spacer (ITS2) ribosomal DNA of the malaria vectorAnopheles stephensi
Authors: Mishra Shobhna , Sharma Gunjan , Das Manoj K. , Pande Veena , Singh Om P. 
Published: April 2021

AbstractSecond Internal Transcribed Spacer (ITS2) ribosomal DNA (rDNA) sequence is a widely used molecular marker for species-identification or -delimitation due to observed concerted evolution which is believed to homogenize rDNA copies in an interbreeding population. However, intra-specific differences in ITS2 ofAnopheles stephensihave been reported. This study reports the presence of intragenomic sequence variation in the ITS2-rDNA ofAn. stephensiand hypothesizes that observed intra-specific differences in this species may have resulted due to ambiguous DNA sequence-chromatogram resulting from intragenomic heterogeneity.Anopheles stephensicollected from different parts of India were sequenced for complete ITS2 and the variable region of 28S-rDNA (d1-d3 domains). Intragenomic variations were found in ITS2 region of allAn. stephensisequenced, but no such variation was observed in d1 to d3 domains of 28S-rDNA. Cloning and sequencing of ITS2 through the d3 domain of the 28S region of rDNA from representative samples from northern, central, and southern India confirmed the presence of intragenomic variation in ITS2 due to transitions at three loci and two bp indel in a di-nucleotide microsatellite locus. Multiple haplotypes were observed in ITS2 raised from such variations. Due to the absence of detectable intragenomic sequence variation in the d1 to d3 domain of 28S rDNA ofAn. stephensi, this region can serve as an ideal reference sequence for taxonomic and phylogenetic studies. The presence of intragenomic variation in rDNA should be carefully examined before using this as a molecular marker for species delimitation or phylogenetic analyses.