Mosaicism and the genetic architecture of congenital heart disease

Congenital heart disease (CHD) is characterized by structural defects of the heart and great vessels. It is the most common birth defect, affecting an estimated 1% of live births, and is the leading cause of mortality among birth defects. Despite recent progress in genetic research, more than 50% of CHD cases remain unexplained. An estimated 23% are due to aneuploidies and copy number variants and up to 30% has been attributed to de novo variation, though that number ranges between 3-30% depending on CHD complexity. The contribution of somatic mosaicism, or de novo genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood due to limitations in sample size, detection method, and validation rate. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined. We developed a computational method, Expectation-Maximization-based detection of Mosaicism (EM-mosaic), to analyze mosaicism in exome sequences of 2530 CHD proband-parent trios. EM-mosaic accurately detected 309 mosaic mutations in blood, with 85 of 94 (90%) candidates tested independently confirmed. We found twenty-five likely damaging mosaics in plausible CHD-risk genes, affecting 1% of our cohort. Variants in these genes predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The frequency of protein-coding mosaic variants detectable in blood was 0.122 or roughly 1 in 8 individuals. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction. CHD patients often present with comorbid cardiac and extracardiac anomalies that further their impact quality of life. Neurodevelopmental disorders (NDDs) are especially prevalent in CHD cases compared to the general population, yet the underlying genetic causes remain poorly explained. Further, patients with single ventricle defects undergoing surgery often later develop arrhythmias and experience worsening ventricular function. We used a statistical approach to dissect the association between de novo variation and these clinical outcomes and found that pleiotropic mutations contribute a large fraction of the risk of acquiring NDD and abnormal ventricular function phenotypes in CHD patients. We developed a proof-of-concept rare variant risk score that combines information from de novo, rare transmitted, and copy- number variants and show that prediction of outcomes such as NDD can be improved, especially in complex CHD cases

Micromechanical model for isolated polymer-colloid clusters under tension

Binary polymer-colloid (PC) composites form the majority of biological load-bearing materials. Due to the abundance of the polymer and particles, and their simple aggregation process, PC clusters are used broadly by nature to create biomaterials with a variety of functions. However, our understanding of the mechanical features of the clusters and their load transfer mechanism is limited. Our main focus in this paper is the elastic behavior of close-packed PC clusters formed in the presence of polymer linkers. Therefore, a micromechanical model is proposed to predict the constitutive behavior of isolated polymer-colloid clusters under tension. The mechanical response of a cluster is considered to be governed by a backbone chain, which is the stress path that transfers most of the applied load. The developed model can reproduce the mean behavior of the clusters and is not dependent on their local geometry. The model utilizes four geometrical parameters for defining six shape descriptor functions which can affect the geometrical change of the clusters in the course of deformation. The predictions of the model are benchmarked against an extensive set of simulations by coarse-grained-Brownian dynamics, where clusters with different shapes and sizes were considered. The model exhibits good agreement with these simulations, which, besides its relative simplicity, makes the model an excellent add-on module for implementation into multiscale models of nanocomposites.National Science Foundation (U.S.) (CAREER Award DMR-1054671)MIT International Science and Technology Initiatives (MISTI-Germany)United States. Dept. of Transportation. UTC Center for Highway Pavement Preservatio

Age groups and spread of influenza: implications for vaccination strategy

<p>Abstract</p> <p>Background</p> <p>The unpredictable nature of the potentially devastating impact of 2009 pH1N1 influenza pandemic highlights the need for pandemic preparedness planning, where modeling studies could be most useful for simulations of possible future scenarios.</p> <p>Methods</p> <p>A compartmental model with pre-symptomatic and asymptomatic influenza infections is proposed which incorporates age groups as well as intervention measures such as age-specific vaccination, in order to study spread of influenza in a community.</p> <p>Results</p> <p>We derive the basic reproduction number and other effective reproduction numbers under various intervention measures. For illustration, we make use of the Pneumonia and Influenza (P&I) mortality data and vaccination data of the very young (age 0-2) and the very old (age >64) during 2004-2005 Taiwan winter influenza season to fit our model and to compute the relevant reproduction numbers. The reproduction number for this winter flu season is estimated to be slightly above one (~1.0001).</p> <p>Conclusions</p> <p>Comparatively large errors in fitting the P&I mortality data of the elderly (>64) were observed shortly after winter school closings in January, which may indicate the impact of younger, more active age groups transmitting influenza to other age groups outside of the school settings; in particular, to the elderly in the households. Pre-symptomatic infections seemed to have little effect on the model fit, while asymptomatic infection by asymptomatic infectives has a more pronounced impact on the model fit for the elderly mortality, perhaps indicating a larger role in disease transmission by asymptomatic infection. Simulations indicate that the impact of vaccination on the disease incidence might not be fully revealed in the change (or the lack thereof) in the effective reproduction number with interventions, but could still be substantial. The estimated per contact transmission probability for susceptible elderly is significantly higher than that of any other age group, perhaps highlighting the vulnerability of the elderly due to close contacts with their caretakers from other age groups. The relative impact of targeting the very young and the very old for vaccination was weakened by their relative inactivity, thus giving evidence of the lack of impact of vaccinating these two groups on the overall transmissibility of the disease in the community. This further underscores the need for morbidity-based strategy to prevent elderly mortality.</p

Hemophagocytosis causes a consumptive anemia of inflammation

IFN-γ stimulates blood-eating macrophages (hemophagocytes) by acting directly on macrophages to promote phagocytosis and uptake of blood cells

On the use of nanocellulose as reinforcement in polymer matrix composites

AbstractNanocellulose is often being regarded as the next generation renewable reinforcement for the production of high performance biocomposites. This feature article reviews the various nanocellulose reinforced polymer composites reported in literature and discusses the potential of nanocellulose as reinforcement for the production of renewable high performance polymer nanocomposites. The theoretical and experimentally determined tensile properties of nanocellulose are also reviewed. In addition to this, the reinforcing ability of BC and NFC is juxtaposed. In order to analyse the various cellulose-reinforced polymer nanocomposites reported in literature, Cox–Krenchel and rule-of-mixture models have been used to elucidate the potential of nanocellulose in composite applications. There may be potential for improvement since the tensile modulus and strength of most cellulose nanocomposites reported in literature scale linearly with the tensile modulus and strength of the cellulose nanopaper structures. Better dispersion of individual cellulose nanofibres in the polymer matrix may improve composite properties

Genome-Wide Transcript Profiling of Endosperm without Paternal Contribution Identifies Parent-of-Origin–Dependent Regulation of AGAMOUS-LIKE36

Seed development in angiosperms is dependent on the interplay among different transcriptional programs operating in the embryo, the endosperm, and the maternally-derived seed coat. In angiosperms, the embryo and the endosperm are products of double fertilization during which the two pollen sperm cells fuse with the egg cell and the central cell of the female gametophyte. In Arabidopsis, analyses of mutants in the cell-cycle regulator CYCLIN DEPENDENT KINASE A;1 (CKDA;1) have revealed the importance of a paternal genome for the effective development of the endosperm and ultimately the seed. Here we have exploited cdka;1 fertilization as a novel tool for the identification of seed regulators and factors involved in parent-of-origin–specific regulation during seed development. We have generated genome-wide transcription profiles of cdka;1 fertilized seeds and identified approximately 600 genes that are downregulated in the absence of a paternal genome. Among those, AGAMOUS-LIKE (AGL) genes encoding Type-I MADS-box transcription factors were significantly overrepresented. Here, AGL36 was chosen for an in-depth study and shown to be imprinted. We demonstrate that AGL36 parent-of-origin–dependent expression is controlled by the activity of METHYLTRANSFERASE1 (MET1) maintenance DNA methyltransferase and DEMETER (DME) DNA glycosylase. Interestingly, our data also show that the active maternal allele of AGL36 is regulated throughout endosperm development by components of the FIS Polycomb Repressive Complex 2 (PRC2), revealing a new type of dual epigenetic regulation in seeds

Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms

In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4&lt;10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable

The contribution of dynamic stromal remodeling during mammary development to breast carcinogenesis

Breast cancer is a heterogeneous disease whose prognosis varies depending upon the developmental stage of the breast tissue at diagnosis. Notably, breast cancers associated with pregnancy exhibit increased rates of metastasis and poorer long-term survival compared to those diagnosed after menopause. However, postmenopausal breast cancers associated with obesity exhibit a more aggressive behavior and confer decreased overall patient survival compared to those diagnosed in non-obese individuals. Since the mammary gland is a dynamic tissue that undergoes significant changes throughout a woman's lifetime, especially during pregnancy and following menopause, we present evidence to support the notion that changes occurring throughout development within the mammary stromal compartment may account for some of the biological differences in breast cancer subtypes and behaviors

The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data

This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete release of the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, which reached its goal of surveying over 10,000 nearby galaxies. The complete release of the MaNGA Stellar Library (MaStar) accompanies this data, providing observations of almost 30,000 stars through the MaNGA instrument during bright time. DR17 also contains the complete release of the Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) survey which publicly releases infra-red spectra of over 650,000 stars. The main sample from the Extended Baryon Oscillation Spectroscopic Survey (eBOSS), as well as the sub-survey Time Domain Spectroscopic Survey (TDSS) data were fully released in DR16. New single-fiber optical spectroscopy released in DR17 is from the SPectroscipic IDentification of ERosita Survey (SPIDERS) sub-survey and the eBOSS-RM program. Along with the primary data sets, DR17 includes 25 new or updated Value Added Catalogs (VACs). This paper concludes the release of SDSS-IV survey data. SDSS continues into its fifth phase with observations already underway for the Milky Way Mapper (MWM), Local Volume Mapper (LVM) and Black Hole Mapper (BHM) surveys