bluuebunny/crossref_metadata_2025_split huggingface dataset:
External validation of a claims-based model to predict left ventricular ejection fraction class in patients with heart failure
Authors: Mahesri Mufaddal , Chin Kristyn , Kumar Abheenava , Barve Aditya , Studer Rachel , Lahoz Raquel , Desai Rishi J. 
Published: November 2020

ABSTRACTBACKGROUNDEjection fraction (EF) is an important prognostic factor in heart failure (HF), but administrative claims databases lack information on EF. We previously developed a model to predict EF class from Medicare claims. Here, we evaluated the performance of this model in an external validation sample of commercial insurance enrollees.METHODTruven MarketScan claims linked to electronic medical records (EMR) data (IBM Explorys) containing EF measurements were used to identify a cohort of US patients with HF between 01-01-2012 and 10-31-2019. By applying the previously developed model, patients were classified into HF with reduced EF (HFrEF) or preserved EF (HFpEF). EF values recorded in EMR data were used to define gold-standard HFpEF (LVEF ≥45%) and HFrEF (LVEF<45%). Model performance was reported in terms of overall accuracy, positive predicted values (PPV), and sensitivity for HFrEF and HFpEF.RESULTSA total of 7,001 HF patients with an average age of 71 years were identified, 1,700 (24.3%) of whom had HFrEF. An overall accuracy of 0.81 (95% CI: 0.80-0.82) was seen in this external validation sample. For HFpEF, the model had sensitivity of 0.96 (95%CI, 0.95-0.97) and PPV of 0.81 (95% CI, 0.81-0.82); while for HFrEF, the sensitivity was 0.32 (95%CI, 0.30-0.34) and PPV was 0.73 (95%CI, 0.69-0.76). These results were consistent with what was previously published in US Medicare claims data.CONCLUSIONSThe successful validation of the Medicare claims-based model provides evidence that this model may be used to identify patient subgroups with specific EF class in commercial claims databases as well.
A longitudinal comparison of spike and nucleocapsid SARS-CoV-2 antibody responses in a tertiary hospital’s laboratory workers with validation of DBS specimen analysis
Authors: Murrell I , Forde D , Tyson L , Chichester L , Garratt A , Vineall O , Palmer N , Jones R , Moore C 
Published: November 2020

AbstractThere is a requirement for easily accessible, high throughput serological testing as part of the SARS-CoV-2 pandemic response. Whilst of limited diagnostic use in an acute individual setting, its use on a population level is key to informing a coherent public health response. As experience of commercial assays increases, so too does knowledge of their precision and limitations. Here we present our experience of these systems thus far. We perform a spot sero-prevalence study amongst staff in a tertiary hospital’s clinical microbiology laboratory, before undertaking validation of DBS serological testing as an alternate specimen for analysis. Finally, we characterise the spike and nucleocapsid antibody response over 160 days post a positive PCR test in nine non-hospitalised staff members.Amongst a cohort of 195 staff, 17 tested positive for SARS-CoV-2 antibodies (8.7%). Self-reporting of SARS-CoV2 infection (P=<0.0001) and testing of a household contact (P = 0.027) were significant variables amongst the positive and negative sub-groups. Testing of 28 matched serum and DBS samples demonstrated 96% accuracy between the sample types. A differential rate of decline of SARS-CoV-2 antibodies against nucleocapsid or spike protein was observed. At 4 months post a positive PCR test 7/9 (78%) individuals had detectable antibodies against spike protein, but only 2/9 (22%) had detectable antibodies against nucleocapsid protein. This study reveals a broad agreement amongst commercial platforms tested and suggests the use of DBS as an alternate specimen option to enable widespread population testing for SARS-CoV-2 antibodies. These results suggest potential limitations of these platforms in estimating historical infection. By setting this temporal point of reference for this cohort of non-patient facing laboratory staff, future exposure risks and mitigation strategies can be evaluated more fully.
Identification of metabolomics biomarkers for type 2 diabetes: triangulating evidence from longitudinal and Mendelian randomization analyses
Authors: Porcu Eleonora , Gilardi Federica , Darrous Liza , Yengo Loic , Bararpour Nasim , Gasser Marie , Vidal Pedro Marques , Froguel Philippe , Waeber Gerard , Thomas Aurelien , Kutalik Zoltán 
Published: November 2020

AbstractThe number of people affected by Type 2 Diabetes Mellitus (T2DM) is close to half a billion and is on a sharp rise, representing a major and growing public health burden. As the case for many other complex diseases, early diagnosis is key to prevent irreversible end-organ damages. However, given its mild initial symptoms, T2DM is often diagnosed several years after its onset, leaving half of diabetic individuals undiagnosed. While several classical clinical and genetic biomarkers have been identified, improving early diagnosis by exploring other kinds of omics data remains crucial. In this study, we have combined longitudinal data from two population-based cohorts CoLaus and DESIR (comprising in total 493 incident cases vs 1’360 controls) to identify new or confirm previously implicated metabolomic biomarkers predicting T2DM incidence more than five years ahead of clinical diagnosis. Our longitudinal data have shown robust evidence for valine, leucine, carnitine and glutamic acid being predictive of future conversion to T2DM, and also confirmed to be causal by 2-sample Mendelian randomisation (based on independent data). Interestingly, for valine and leucine a strong reverse causal effect was detected, indicating that the genetic predisposition to T2DM may trigger early changes of these metabolites, which appear well-before any clinical symptoms. These findings indicate that molecular traits linked to the genetic basis of T2DM may be particularly promising early biomarkers.
Quantification of occupational and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large U.S. healthcare system
Authors: Baker Julia M. , Nelson Kristin N. , Overton Elizabeth , Lopman Benjamin A. , Lash Timothy L. , Photakis Mark , Jacob Jesse T. , Roback John , Fridkin Scott K. , Steinberg James P. 
Published: November 2020

AbstractBackgroundQuantifying occupational risk factors for SARS-CoV-2 infection among healthcare workers can inform efforts to improve healthcare worker and patient safety and reduce transmission. This study aimed to quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large metropolitan healthcare system.MethodsWe analyzed data from a cross-sectional survey conducted from April through June of 2020 linking risk factors for occupational and community exposure to COVID-19 with SARS-CoV-2 seropositivity. A multivariable logistic regression model was fit to quantify risk factors for infection. Participants were employees and medical staff members who elected to participate in SARS-CoV-2 serology testing offered to all healthcare workers as part of a quality initiative, and who completed a survey on exposure to COVID-19 and use of personal protective equipment. Exposures of interest included known demographic risk factors for COVID-19, residential zip code incidence of COVID-19, occupational exposure to PCR test-positive healthcare workers or patients, and use of personal protective equipment. The primary outcome of interest was SARS-CoV-2 seropositivity.ResultsSARS-CoV-2 seropositivity was estimated to be 5.7% (95% CI: 5.2%-6.1%) among 10,275 healthcare workers. Community contact with a person known or suspected to have COVID-19 (aOR=1.9, 95% CI:1.4-2.5) and zip code level COVID-19 incidence (aOR: 1.4, 95% CI: 1.0-2.0) increased the odds of infection. Black individuals were at high risk (aOR=2.0, 95% CI:1.6-2.4). Overall, occupational risk factors accounted for 27% (95% CI: 25%-30%) of the risk among healthcare workers and included contact with a PCR test-positive healthcare worker (aOR=1.2, 95% CI:1.0-1.6).ConclusionsCommunity risk factors, including contact with a COVID-19 positive individual and residential COVID-19 incidence, are more strongly associated with SARS-CoV-2 seropositivity among healthcare workers than exposure in the workplace.
COVID-19, a social disease in Paris: a socio-economic wide association study on hospitalized patients highlights low-income neighbourhood as a key determinant of severe COVID-19 incidence during the first wave of the epidemic
Authors: Jannot Anne-Sophie , Coutouris Hector , Burgun Anita , Katsahian Sandrine , Rance Bastien 
Published: November 2020

AbstractBackgroundStudies have already shown that many environmental factors are associated with COVID-19 incidence. However, none have studied a very large set of socio-economic indicators and analysed to what extent these factors could highlight populations at high risk for COVID-19. We propose here a new approach, a socio-economic wide study, to pinpoint subgroups with a high incidence of COVID-19, and illustrated this approach using hospitalized cases in Paris area.MethodsWe extracted 303 socio-economic indicators from French census data for the 855 residential units in Paris and assessed their association with COVID-19 hospitalization risk. We then fitted a predictive model using a penalized regression on these indicators to predict the incidence of patient hospitalization for COVID-19 in Paris.FindingsThe most associated indicator was income, corresponding to the 3rd decile of the population (OR= 0.11, CI95% [0.05; 0.20]). A model including only income achieves a high performance in both the training set (AUC=0.78, CI95%: 0.72-0.85) and the test set (AUC=0.79 (CI95%: 0.71-0.87). Overall, the 45% most deprived areas gathered 86% of the areas with a high incidence of COVID-19 hospitalized cases.InterpretationDuring the first wave of the epidemic, income predicted Paris areas at risk for a high incidence of patients hospitalized for COVID-19 with a high performance. Socio-economic wide association studies, collecting passively data from hospitalized cases, therefore not necessitating any effort for health caregivers, is of particular interest in such a period of hospital overcrowding as it provides real-time indirect information on populations having high COVID-19 incidence.
Robust SARS-CoV-2-specific T-cell immunity is maintained at 6 months following primary infection
Authors: Zuo J , Dowell A , Pearce H , Verma K , Long HM , Begum J , Aiano F , Amin-Chowdhury Z , Hallis B , Stapley L , Borrow R , Linley E , Ahmad S , Parker B , Horsley A , Amirthalingam G , Brown K , Ramsay ME , Ladhani S , Moss P 
Published: November 2020

AbstractThe immune response to SARS-CoV-2 is critical in both controlling primary infection and preventing re-infection. However, there is concern that immune responses following natural infection may not be sustained and that this may predispose to recurrent infection. We analysed the magnitude and phenotype of the SARS-CoV-2 cellular immune response in 100 donors at six months following primary infection and related this to the profile of antibody level against spike, nucleoprotein and RBD over the previous six months. T-cell immune responses to SARS-CoV-2 were present by ELISPOT and/or ICS analysis in all donors and are characterised by predominant CD4+ T cell responses with strong IL-2 cytokine expression. Median T-cell responses were 50% higher in donors who had experienced an initial symptomatic infection indicating that the severity of primary infection establishes a ‘setpoint’ for cellular immunity that lasts for at least 6 months. The T-cell responses to both spike and nucleoprotein/membrane proteins were strongly correlated with the peak antibody level against each protein. The rate of decline in antibody level varied between individuals and higher levels of nucleoprotein-specific T cells were associated with preservation of NP-specific antibody level although no such correlation was observed in relation to spike-specific responses. In conclusion, our data are reassuring that functional SARS-CoV-2-specific T-cell responses are retained at six months following infection although the magnitude of this response is related to the clinical features of primary infection.
Conditional distribution modeling as an alternative method for covariates simulation: comparison with joint multivariate normal and bootstrap techniques
Authors: Smania Giovanni , Jonsson E. Niclas 
Published: November 2020

AbstractClinical trial simulation (CTS) is a valuable tool in drug development. To obtain realistic scenarios, the subjects included in the CTS must be representative of the target population. Common ways of generating virtual subjects are based upon bootstrap (BS) procedures or multivariate normal distributions (MVND). Here, we investigated the performance of an alternative method based on conditional distributions (CD). Covariates data from a hypertension drug development program were used. The methods were evaluated based on the original dataset (internal evaluation) and on their ability to reproduce an older, unobserved population (extrapolation). Similar results were obtained in the internal evaluation for summary statistics, yet BS was able to preserve the correlation structure of the empirical distribution, which was not adequately reproduced by MVND; CD was in between BS and MVND. BS does not allow to extrapolate to an unobserved population. When the dataset used to inform the extrapolation was well approximated by a MVND, the results from CD and MVND were comparable. However, improved extrapolation performance was observed for CD when deviations from normality assumptions occurred. If CTS is used to simulate within the observed distribution, BS is the preferred method. When extrapolating to new populations, a parametric method like CD/MVND is needed. In case the empirical multivariate distribution is characterized by linearly related covariates and unimodal marginal distributions, MVND can be used because of the simpler statistical framework and well-established use; however, if uncertainty about the MVND assumptions exists, CD will increase the confidence in the simulations compared to MVND.
Bioassemblying Macro-Scale, Lumnized Airway Tubes of Defined Shape via Multi-Organoid Patterning and Fusion
Authors: Liu Ye , Dabrowska Catherine , Mavousian Antranik , Strauss Bernhard , Meng Fanlong , Mazzaglia Corrado , Ouaras Karim , Macintosh Callum , Terentjev Eugene , Lee Joo-Hyeon , Huang Yan Yan Shery 
Published: November 2020

AbstractEpithelial, stem-cell derived organoids are ideal building blocks for tissue engineering, however, scalable and shape-controlled bioassembly of epithelial organoids into larger and anatomical structures has yet to be achieved. Here, a robust organoid engineering approach, Multi-Organoid Patterning and Fusion (MOrPF), is presented to assemble individual airway organoids of different sizes into upscaled, scaffold-free airway tubes with pre-defined shapes. Multi-Organoid Aggregates (MOAs) undergo accelerated fusion in a matrix-depleted, free-floating environment, possess a continuous lumen and maintain prescribed shapes without an exogenous scaffold interface. MOAs in the floating culture exhibit a well-defined three-stage process of inter-organoid surface integration, luminal material clearance and lumina connection. The observed shape stability of patterned MOAs is confirmed by theoretical modelling based on organoid morphology and the physical forces involved in organoid fusion. Immunofluorescent characterization shows that fused MOA tubes possess an unstratified epithelium consisting mainly of tracheal basal stem cells. By generating large, shape-controllable organ tubes, MOrPF enables upscaled organoid engineering towards integrated organoid-devices and structurally complex organ tubes.
Functional brain network topology across the menstrual cycle is sex hormone dependent and correlates with the individual well-being
Authors: Liparoti Marianna , Lopez Emahnuel Troisi , Sarno Laura , Rucco Rosaria , Minino Roberta , Pesoli Matteo , Perruolo Giuseppe , Formisano Pietro , Lucidi Fabio , Sorrentino Giuseppe , Sorrentino Pierpaolo 
Published: November 2020

AbstractThe menstrual cycle is known to influence the behaviour. The neuronal bases of this phenomenon are poorly understood. We hypothesized that hormones, might affect the large-scale organization of the brain functional networks and that, in turn, such changes might have behavioural correlates in terms of the affective state. To test our hypothesis, we took advantage of magnetoencephalography to investigate brain topology in early follicular, ovulatory and luteal phases, in twenty-four naturally-cycling women without signs of anxiety and/or depression. We show that in the alpha band the betweenness centrality (BC) of the right posterior cingulate gyrus (PCG) during the ovulatory phase is increased and the rise is predicted by the levels of estradiol. We also demonstrate that the increase in the BC is related to improved subjective well-being that, in turn, is correlated to the estradiol levels. The increased topological centrality of the PCG during the ovulatory phase could have implications in reproductive psychology.
Photocatalyst under visible light irradiation inactivates SARS-CoV-2 on an abiotic surface
Authors: Uema Masashi , Yonemitsu Kenzo , Momose Yoshika , Ishii Yoshikazu , Tateda Kazuhiro , Inoue Takao , Asakura Hiroshi 
Published: November 2020

AbstractThere is a worldwide attempt to develop prevention strategies against SARS-CoV-2 transmission. Here we examined the effectiveness of visible light-responsive photocatalyst RENECAT™ on the inactivation of SARS-CoV-2 under different temperatures and exposure durations. The viral activation on the photocatalyst-coated glass slides decreased from 5.93±0.38 logTCID50/ml to 3.05±0.25 logTCID50/ml after exposure to visible light irradiation for 6h at 20°C. On the other hand, lighting without the photocatalyst, or the photocatalyst-coat without lighting retained viral stability. Immunoblotting and electron microscopic analyses showed the reduced amounts of spike protein on the viral surface after the photocatalyst treatment. Our data suggest a possible implication of the photocatalyst on the decontamination of the SARS-CoV-2 in indoor environments, thereby preventing indirect viral spread.
Phage Peptides Mediate Precision Base Editing with Focused Targeting Window
Authors: Jia Kun , Cui Yan-ru , Huang Shisheng , Yu Peihong , Lian Zhengxing , Ma Peixiang , Liu Jia 
Published: November 2020

AbstractCytidine base editors (CBE) are novel genome engineering tools that can generate C-to-T nucleotide substitutions without introducing double-stranded breaks (DSBs). Instead of generating single-point mutations, CBEs induce nucleotide substitutions at wobble positions within the 20-nucleotide target site. A variety of strategies have been developed to improve the targeting scope and window of CBEs. Among these strategies, molecular switches that can temporally control CBE activities represent compelling options. In this study, we investigated the feasibility of using a bacteriophage-derived peptide, referred to as G8PPD, as the off-switch of CBEs. We showed that G8PPDcould be employed to control the activities of and improve the targeting window of A3A and BE3 CBEs and adenine base editor 7.10 (ABE7.10). Notably, in a cell-based disease model of Marfan syndrome, G8PPDfacilitated A3A CBE-based gene correction with a more focused targeting window and improved the percentage of perfectly edited gene alleles from less than 4% to more than 38% of the whole population. Our study presents the first peptide off-switch that can improve the targeting scope of CBEs, thus highlighting the importance of the temporal control of BE activity for precision base editing.
Follicular fluid metabolome and cytokinome profiles in poor ovarian responders and the impact of dehydroepiandrosterone supplementation
Authors: Viardot-Foucault Veronique , Zhou Jieliang , Bi Dexi , Takinami Yoshihiko , Tan Heng Hao , Chan Jerry.K.Y. , Lee Yie Hou 
Published: November 2020

AbstractPoor ovarian responders (POR) are women undergoing in-vitro fertilization who respond poorly to ovarian stimulation, resulting in the retrieval of lower number of oocytes, and subsequently lower pregnancy rates. The follicular fluid (FF) provides a crucial microenvironment for the proper development of follicles and oocytes. Conversely, dysregulated FF metabolome and cytokinome could have detrimental effects on oocytes in POR. Androgens such as dehydroepiandrosterone (DHEA) have been proposed to alter the POR follicular microenvironment but its effects on the FF metabolome and cytokine profiles is unknown. In this study, untargeted LC-MS/MS metabolomics was performed on FF of POR patients with DHEA supplementation (DHEA+) and without (DHEA-) in a randomized clinical trial (N=52). Untargeted metabolomics identified 118 FF metabolites of diverse chemistries, which included lipids, steroids, amino acids, hormones, among others. FF metabolomes were different between DHEA+ and DHEA- groups. Specifically, glycerophosphocholine, linoleic acid, progesterone, and valine were significantly lower in DHEA+ relative to DHEA-. Among cytokines, MCP1, IFNγ, LIF and VEGF-D were significantly lower in DHEA+ relative to DHEA. Collectively, our data suggest a role of DHEA on these metabolic and cytokines pathways, and these FF metabolites could be used to guide future studies in DHEA supplementation regimen.
Demographic and psychological correlates of SARS-CoV-2 vaccination intentions in a sample of Canadian families
Authors: Lackner Christine L. , Wang Charles H. 
Published: November 2020

AbstractThe COVID-19 pandemic has been ongoing for close to a year, with second waves occurring presently and many viewing a vaccine as the most likely way to curb successive waves and promote herd immunity. Reaching herd immunity status likely necessitates that children, as well as their parents, receive a vaccine targeting SARS-CoV-2. In this exploratory study, we investigated the demographic, experiential, and psychological factors associated with the anticipated likelihood and speed of having children receive a SARS-CoV-2 vaccine in a sample of 455 Canadian families (857 children). Using linear mixed effects and proportional odds logistic regression models, we demonstrated that older parental age, living in the Prairies (relative to Central Canada), more complete child and parental vaccination history, more positive attitudes towards vaccines generally, higher psychological avoidance of the pandemic and a greater tendency to prioritize the risks of the disease relative to the risks of side effects (i.e., lower omission bias), were associated with higher likelihoods of intention to vaccinate participants’ children. In some models, subjective evaluations of proximal COVID-19 risk and higher levels of state anxiety were associated with increased likelihood of having children vaccinated. Faster speed of intended vaccination was predicted by a similar constellation of variables, with higher SES emerging as a trend-level predictor of vaccination speed. Results are discussed with respect to public health knowledge mobilization.