scholarly journals Immunological and Genetic Investigation of SARS-CoV-2 Reinfection in an Otherwise Healthy, Young Marine Recruit

Pathogens ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1589
Author(s):  
Andrew G. Letizia ◽  
Catherine E. Arnold ◽  
Bishwo N. Adhikari ◽  
Logan J. Voegtly ◽  
Lindsay Glang ◽  
...  
Keyword(s):  
Genetic Information ◽  
Sequence Data ◽  
Multiple Time ◽  
Rt Pcr ◽  
Genetic Investigation ◽  
Serological Studies ◽  
Health Action ◽  
Routine Sampling ◽  
Multiple Time Points ◽  
Prospective Longitudinal

We used epidemiologic and viral genetic information to identify a case of likely reinfection in an otherwise healthy, young Marine recruit enrolled in the prospective, longitudinal COVID-19 Health Action Response for Marines (CHARM) study, and we paired these findings with serological studies. This participant had a positive RT-PCR to SARS-CoV-2 upon routine sampling on study day 7, although he was asymptomatic at that time. He cleared the infection within seven days. On study day 46, he had developed symptoms consistent with COVID-19 and tested positive by RT-PCR for SARS-CoV-2 again. Viral whole genome sequencing was conducted from nares swabs at multiple time points. The day 7 sample was determined to be lineage B.1.340, whereas both the day 46 and day 49 samples were B.1.1. The first positive result for anti-SARS-CoV-2 IgM serology was collected on day 49 and for IgG on day 91. This case appears most consistent with a reinfection event. Our investigation into this case is unique in that we compared sequence data from more than just paired specimens, and we also assayed for immune response after both the initial infection and the later reinfection. These data demonstrate that individuals who have experienced an infection with SARS-CoV-2 may fail to generate effective or long-lasting immunity, similar to endemic human beta coronaviruses.

scholarly journals Physical activity levels among ovarian cancer survivors: a prospective longitudinal cohort study

2021 ◽  
pp. ijgc-2020-002107
Author(s):  
Tamara Jones ◽  
Carolina Sandler ◽  
Dimitrios Vagenas ◽  
Monika Janda ◽  
Andreas Obermair ◽  
...  
Keyword(s):  
Physical Activity ◽  
Ovarian Cancer ◽  
Stage Iv ◽  
Multiple Time ◽  
Activity Levels ◽  
Prospective Longitudinal Study ◽  
Physical Activity Advice ◽  
Physical Activity Levels ◽  
Multiple Time Points ◽  
Prospective Longitudinal

ObjectivePhysical activity following cancer diagnosis is associated with improved outcomes, including potential survival benefits, yet physical activity levels among common cancer types tend to decrease following diagnosis and remain low. Physical activity levels following diagnosis of less common cancers, such as ovarian cancer, are less known. The objectives of this study were to describe physical activity levels and to explore characteristics associated with physical activity levels in women with ovarian cancer from pre-diagnosis to 2 years post-diagnosis.MethodsAs part of a prospective longitudinal study, physical activity levels of women with ovarian cancer were assessed at multiple time points between pre-diagnosis and 2 years post-diagnosis. Physical activity levels and change in physical activity were described using metabolic equivalent task hours and minutes per week, and categorically (sedentary, insufficiently, or sufficiently active). Generalized Estimating Equations were used to explore whether participant characteristics were related to physical activity levels.ResultsA total of 110 women with ovarian cancer with a median age of 62 years (range 33–88) at diagnosis were included. 53–57% of the women were sufficiently active post-diagnosis, although average physical activity levels for the cohort were below recommended levels throughout the 2-year follow-up period (120–142.5min/week). A decrease or no change in post-diagnosis physical activity was reported by 44–60% of women compared with pre-diagnosis physical activity levels. Women diagnosed with stage IV disease, those earning a lower income, those receiving chemotherapy, and those currently smoking or working were more likely to report lower physical activity levels and had increased odds of being insufficiently active or sedentary.ConclusionsInterventions providing patients with appropriate physical activity advice and support for behavior change could potentially improve physical activity levels and health outcomes.

A Systematic Review of Allostatic Load, Health, and Health Disparities

2012 ◽  
Vol 14 (4) ◽  
pp. 311-346 ◽  
Author(s):  
Theresa M. Beckie
Keyword(s):  
Systematic Review ◽  
Health Outcomes ◽  
Allostatic Load ◽  
Health Priorities ◽  
Empirical Literature ◽  
Future Research ◽  
Multiple Time ◽  
Physical And Mental Health ◽  
Multiple Time Points ◽  
Prospective Longitudinal

The theoretical constructs of allostasis and allostatic load (AL) have contributed to our understanding of how constantly changing social and environmental factors impact physiological functioning and shape health and aging disparities, particularly along socioeconomic, gendered, racial, and ethnic lines. AL represents the cumulative dysregulation of biological systems with prolonged or poorly regulated allostatic responses. Nearly two decades of empirical research has focused on operationalizing the AL construct for examining the antecedents and health outcomes accompanying multisystem biological dysregulation. The purpose of this systematic review is to examine the empirical literature that quantifies the AL construct; the review also evaluates the social, environmental, and genetic antecedents of AL as well as its predictive utility for a variety of health outcomes. A total of 58 articles published between 1997 and 2012 were retrieved, analyzed, and synthesized. The results revealed considerable heterogeneity in the operationalization of AL and the measurement of AL biomarkers, making interpretations and comparisons across studies challenging. There is, however, empirical substantiation for the relationships between AL and socioeconomic status, social relationships, workplace, lifestyle, race/ethnicity, gender, stress exposure, and genetic factors. The literature also demonstrated associations between AL and physical and mental health and all-cause mortality. Targeting the antecedents of AL during key developmental periods is essential for improving public health. Priorities for future research include conducting prospective longitudinal studies, examining a broad range of antecedent allostatic challenges, and collecting reliable measures of multisystem dysregulation explicitly designed to assess AL, at multiple time points, in population-representative samples.

scholarly journals The molecular make up of smoldering myeloma highlights the evolutionary pathways leading to multiple myeloma

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Eileen M. Boyle ◽  
Shayu Deshpande ◽  
Ruslana Tytarenko ◽  
Cody Ashby ◽  
Yan Wang ◽  
...  
Keyword(s):  
Tumour Suppressor Genes ◽  
Multiple Time ◽  
Clonal Structure ◽  
Time To Progression ◽  
Novel Mutations ◽  
Evolutionary Patterns ◽  
Risk Of Progression ◽  
Multiple Time Points ◽  
Smoldering Myeloma ◽  
Copy Number Changes

AbstractSmoldering myeloma (SMM) is associated with a high-risk of progression to myeloma (MM). We report the results of a study of 82 patients with both targeted sequencing that included a capture of the immunoglobulin and MYC regions. By comparing these results to newly diagnosed myeloma (MM) we show fewer NRAS and FAM46C mutations together with fewer adverse translocations, del(1p), del(14q), del(16q), and del(17p) in SMM consistent with their role as drivers of the transition to MM. KRAS mutations are associated with a shorter time to progression (HR 3.5 (1.5–8.1), p = 0.001). In an analysis of change in clonal structure over time we studied 53 samples from nine patients at multiple time points. Branching evolutionary patterns, novel mutations, biallelic hits in crucial tumour suppressor genes, and segmental copy number changes are key mechanisms underlying the transition to MM, which can precede progression and be used to guide early intervention strategies.

scholarly journals Use of TanDEM-X and SRTM-C Data for Detection of Deforestation Caused by Bark Beetle in Central European Mountains

2021 ◽  
Vol 13 (15) ◽  
pp. 3042
Author(s):  
Kateřina Gdulová ◽  
Jana Marešová ◽  
Vojtěch Barták ◽  
Marta Szostak ◽  
Jaroslav Červenka ◽  
...  
Keyword(s):  
Bark Beetle ◽  
Synergistic Effects ◽  
Canopy Height ◽  
Surface Model ◽  
Multiple Time ◽  
Central European ◽  
Time Points ◽  
Bohemian Forest ◽  
Multiple Time Points ◽  
Surrounding Areas

The availability of global digital elevation models (DEMs) from multiple time points allows their combination for analysing vegetation changes. The combination of models (e.g., SRTM and TanDEM-X) can contain errors, which can, due to their synergistic effects, yield incorrect results. We used a high-resolution LiDAR-derived digital surface model (DSM) to evaluate the accuracy of canopy height estimates of the aforementioned global DEMs. In addition, we subtracted SRTM and TanDEM-X data at 90 and 30 m resolutions, respectively, to detect deforestation caused by bark beetle disturbance and evaluated the associations of their difference with terrain characteristics. The study areas covered three Central European mountain ranges and their surrounding areas: Bohemian Forest, Erzgebirge, and Giant Mountains. We found that vertical bias of SRTM and TanDEM-X, relative to the canopy height, is similar with negative values of up to −2.5 m and LE90s below 7.8 m in non-forest areas. In forests, the vertical bias of SRTM and TanDEM-X ranged from −0.5 to 4.1 m and LE90s from 7.2 to 11.0 m, respectively. The height differences between SRTM and TanDEM-X show moderate dependence on the slope and its orientation. LE90s for TDX-SRTM differences tended to be smaller for east-facing than for west-facing slopes, and varied, with aspect, by up to 1.5 m in non-forest areas and 3 m in forests, respectively. Finally, subtracting SRTM and NASA DEMs from TanDEM-X and Copernicus DEMs, respectively, successfully identified large areas of deforestation caused by hurricane Kyril in 2007 and a subsequent bark beetle disturbance in the Bohemian Forest. However, local errors in TanDEM-X, associated mainly with forest-covered west-facing slopes, resulted in erroneous identification of deforestation. Therefore, caution is needed when combining SRTM and TanDEM-X data in multitemporal studies in a mountain environment. Still, we can conclude that SRTM and TanDEM-X data represent suitable near global sources for the identification of deforestation in the period between the time points of their acquisition.

scholarly journals Associations of Binge Drinking With Vascular Brain Injury and Atrophy in Older American Indians: The Strong Heart Study

2021 ◽  
Vol 33 (7-8_suppl) ◽  
pp. 51S-59S
Author(s):  
Jordan P. Lewis ◽  
Astrid M. Suchy-Dicey ◽  
Carolyn Noonan ◽  
Valarie Blue Bird Jernigan ◽  
Jason G. Umans ◽  
...  
Keyword(s):  
Brain Injury ◽  
Binge Drinking ◽  
American Indians ◽  
Multiple Time ◽  
Heart Study ◽  
Neurological Risk ◽  
The Us ◽  
Large Cohort Study ◽  
Magnetic Resonance Imaging Mri ◽  
Multiple Time Points

Objectives: American Indians (AIs) generally consume less alcohol than the US general population; however, the prevalence of alcohol use disorder is higher. This is the first large cohort study to examine binge drinking as a risk factor for vascular brain injury (VBI). Methods: We used linear and Poisson regression to examine the association of self-reported binge drinking with VBI, measured via magnetic resonance imaging (MRI), in 817 older AIs who participated in the Strong Heart and Cerebrovascular Disease and Its Consequences in American Indians studies. Results: Any binge drinking at multiple time-points was associated with increased sulcal (β = 0.360, 95% CI [0.079, 0.641]) and ventricle dilatation (β = 0.512, 95% CI [0.174, 0.850]) compared to no binge drinking. Discussion: These observed associations are consistent with previous findings. Identifying how binge drinking may contribute to VBI in older AIs may suggest modifiable health behaviors for neurological risk reduction and disease prevention.

scholarly journals Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Henriette Miko ◽  
Yunjiang Qiu ◽  
Bjoern Gaertner ◽  
Maike Sander ◽  
Uwe Ohler
Keyword(s):  
Time Series ◽  
Histone Modifications ◽  
Gene Activation ◽  
Expectation Maximization Algorithm ◽  
Chromatin State ◽  
Open Chromatin ◽  
Multiple Time ◽  
Enhancer Activity ◽  
Chromatin States ◽  
Multiple Time Points

Abstract Background Co-localized combinations of histone modifications (“chromatin states”) have been shown to correlate with promoter and enhancer activity. Changes in chromatin states over multiple time points (“chromatin state trajectories”) have previously been analyzed at promoter and enhancers separately. With the advent of time series Hi-C data it is now possible to connect promoters and enhancers and to analyze chromatin state trajectories at promoter-enhancer pairs. Results We present TimelessFlex, a framework for investigating chromatin state trajectories at promoters and enhancers and at promoter-enhancer pairs based on Hi-C information. TimelessFlex extends our previous approach Timeless, a Bayesian network for clustering multiple histone modification data sets at promoter and enhancer feature regions. We utilize time series ATAC-seq data measuring open chromatin to define promoters and enhancer candidates. We developed an expectation-maximization algorithm to assign promoters and enhancers to each other based on Hi-C interactions and jointly cluster their feature regions into paired chromatin state trajectories. We find jointly clustered promoter-enhancer pairs showing the same activation patterns on both sides but with a stronger trend at the enhancer side. While the promoter side remains accessible across the time series, the enhancer side becomes dynamically more open towards the gene activation time point. Promoter cluster patterns show strong correlations with gene expression signals, whereas Hi-C signals get only slightly stronger towards activation. The code of the framework is available at https://github.com/henriettemiko/TimelessFlex. Conclusions TimelessFlex clusters time series histone modifications at promoter-enhancer pairs based on Hi-C and it can identify distinct chromatin states at promoter and enhancer feature regions and their changes over time.

scholarly journals Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidates for targeted treatment

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hua Sun ◽  
Song Cao ◽  
R. Jay Mashl ◽  
Chia-Kuei Mo ◽  
Simone Zaccaria ◽  
...  
Keyword(s):  
Human Tumors ◽  
Multiple Time ◽  
Cancer Treatments ◽  
Whole Genome Duplications ◽  
Patient Derived Xenograft ◽  
Genome Duplications ◽  
Genomic Characterization ◽  
Cancer Types ◽  
Multiple Time Points ◽  
Pdx Models

AbstractDevelopment of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs’ recapitulation of human tumors.

scholarly journals Polygenic Score for Smoking Is Associated With Externalizing Psychopathology and Disinhibited Personality Traits but Not Internalizing Psychopathology in Adolescence

2021 ◽  
pp. 216770262110021
Author(s):  
Brian M. Hicks ◽  
D. Angus Clark ◽  
Joseph D. Deak ◽  
Mengzhen Liu ◽  
C. Emily Durbin ◽  
...  
Keyword(s):  
Personality Traits ◽  
Behavioral Control ◽  
Behavioral Disinhibition ◽  
Multiple Time ◽  
Normal Range ◽  
Polygenic Score ◽  
Externalizing Psychopathology ◽  
Internalizing Psychopathology ◽  
Multiple Time Points ◽  
Related Personality

We examined whether a polygenic score (PGS) for smoking measured genetic risk for general behavioral disinhibition by estimating its associations with externalizing and internalizing psychopathology and related personality traits at multiple time points in adolescence (ages 11, 14, and 17 years; N = 3,225). The smoking PGS had strong associations with the stable variance across time for all the externalizing measures (mean standardized β = 0.27), agreeableness (β = −0.22, 95% confidence interval [CI] = [−0.28, −0.16]), and conscientiousness (β = −0.19, 95% CI = [−0.24, −0.13]) but was not significantly associated with internalizing measures (mean β = 0.06) or extraversion (β = 0.01, 95% CI = [−0.05, 0.07]). After controlling for smoking at age 17 years, the associations with externalizing, low agreeableness, and low conscientiousness remained statistically significant. The smoking PGS measures genetic influences that contribute to a spectrum of phenotypes related to behavioral disinhibition, including externalizing psychopathology and normal-range personality traits related to behavioral control but not internalizing psychopathology.

scholarly journals 157. patient to Environment Transmission of Multidrug-resistant Bacteria Within Intensive Care Units

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S207-S208
Author(s):  
Matthew J Ziegler ◽  
Brendan Kelly ◽  
Michael Z David ◽  
Lauren Dutcher ◽  
Pam C Tolomeo ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Multidrug Resistant ◽  
Resistant Bacteria ◽  
Multiple Time ◽  
Extended Spectrum Beta Lactamase ◽  
Environmental Transmission ◽  
Body Culture ◽  
Clinical Culture ◽  
Multiple Time Points

Abstract Background Identifying risk factors for environmental contamination with multidrug-resistant organisms (MDROs) is essential to prioritize methods for prevention of hospital transmission. Methods Patients admitted to an ICU with an MDRO detected on clinical culture in the prior 30 days were enrolled. Patients (4 body sites) and high-touch objects (HTO) (3 composite sites) in ICU rooms were sampled. Environmental transmission was defined by shared MDRO species cultured on patient and HTO cultures obtained on multiple time points during the patient’s stay. Risk factors for environmental transmission were identified with logistic regression. Results Forty-five patients were included (median 2 days of longitudinal sampling [IQR 1–4 days]). Enrollment anatomic cultures included extended-spectrum beta-lactamase-producing Enterobacterales (ESBLE) (n=12, 27%), carbapenem-resistant organisms (CRO) (n=4, 9%), methicillin-resistant S.aureus (MRSA) (n=11, 24%), vancomycin-resistant Enterococci (VRE) (n=4, 9%), and C.difficile (CDIFF) (n=14, 31%). Patient colonization during serial sampling was common with CRO (n=21, 47%), ESBLE (n=16, 36%), and VRE (n=16, 36%) and less so with MRSA (n=7, 16%) and CDIFF (n=5, 11%). Detection of MDROs on environmental surfaces was also common with identification of CRO in 47% of patient rooms (n=21) and ESBLE in 29% (n=13); MRSA (n=2, 4%), VRE (n=9, 20%), and CDIFF (n=3, 7%) were rarer. Patient to environment transmission was observed in 40% of rooms (n=18). Thirteen (29%) rooms had foreign MDRO contamination (i.e., one not detected on a body culture), most (n=10) with CRO. Environmental MDROs were most common in bathroom/sinks (n=22), followed by surfaces near the patient (n=10), and least common surfaces often touched by staff within the room (n=6). On multivariable logistic regression, naïve to clustering by patient, recent receipt of a proton pump inhibitor (OR 2.35, 95% CI 1.00 – 5.52, P=0.049) and presence of one or more wounds (OR 2.56, 95% CI 1.05 – 6.26, P=0.038) were significantly associated with environmental transmission (OR 1.56, 95% CI 1.01 – 2.43, P=0.046) (Table 1). Conclusion MDRO contamination of patient rooms is common with detection of organisms attributed to, and foreign to, the occupant. Disclosures Michael Z. David, MD PhD, GSK (Consultant)

Meta-analysis of effect sizes reported at multiple time points: A multivariate approach

2012 ◽  
Vol 9 (5) ◽  
pp. 610-620 ◽  
Author(s):  
Thomas A Trikalinos ◽  
Ingram Olkin
Keyword(s):  
Random Effects ◽  
Treatment Effects ◽  
Multivariate Analyses ◽  
Meta Analysis ◽  
Effect Sizes ◽  
Multiple Time ◽  
Time Points ◽  
Fixed And Random Effects ◽  
Multiple Time Points ◽  
Meta Analyses

Background Many comparative studies report results at multiple time points. Such data are correlated because they pertain to the same patients, but are typically meta-analyzed as separate quantitative syntheses at each time point, ignoring the correlations between time points. Purpose To develop a meta-analytic approach that estimates treatment effects at successive time points and takes account of the stochastic dependencies of those effects. Methods We present both fixed and random effects methods for multivariate meta-analysis of effect sizes reported at multiple time points. We provide formulas for calculating the covariance (and correlations) of the effect sizes at successive time points for four common metrics (log odds ratio, log risk ratio, risk difference, and arcsine difference) based on data reported in the primary studies. We work through an example of a meta-analysis of 17 randomized trials of radiotherapy and chemotherapy versus radiotherapy alone for the postoperative treatment of patients with malignant gliomas, where in each trial survival is assessed at 6, 12, 18, and 24 months post randomization. We also provide software code for the main analyses described in the article. Results We discuss the estimation of fixed and random effects models and explore five options for the structure of the covariance matrix of the random effects. In the example, we compare separate (univariate) meta-analyses at each of the four time points with joint analyses across all four time points using the proposed methods. Although results of univariate and multivariate analyses are generally similar in the example, there are small differences in the magnitude of the effect sizes and the corresponding standard errors. We also discuss conditional multivariate analyses where one compares treatment effects at later time points given observed data at earlier time points. Limitations Simulation and empirical studies are needed to clarify the gains of multivariate analyses compared with separate meta-analyses under a variety of conditions. Conclusions Data reported at multiple time points are multivariate in nature and are efficiently analyzed using multivariate methods. The latter are an attractive alternative or complement to performing separate meta-analyses.

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