The lethal sex gap: COVID-19.

While Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is disrupting lives across the globe for everyone, it has a more devastating impact on the health of older adults, especially that of older men. This pandemic has highlighted the crucial importance of considering an individual\u27s age and biological sex in the clinic in addition to other confounding diseases (Kuchel, G.A, J Am Geriatr Soc, 67, 203, 2019, Tannenbaum, C., Nature, 575 451-458, 2009) As an interdisciplinary team of scientists in immunology, hematology, genomics, bioinformatics, and geriatrics, we have been studying how age and sex shape the human immune system. Herein we reflect on how our recent findings on the alterations of the immune system in aging might contribute to our current understanding of COVID-19 infection rate and disease risk

Sexual-dimorphism in human immune system aging.

Differences in immune function and responses contribute to health- and life-span disparities between sexes. However, the role of sex in immune system aging is not well understood. Here, we characterize peripheral blood mononuclear cells from 172 healthy adults 22-93 years of age using ATAC-seq, RNA-seq, and flow cytometry. These data reveal a shared epigenomic signature of aging including declining naïve T cell and increasing monocyte and cytotoxic cell functions. These changes are greater in magnitude in men and accompanied by a male-specific decline in B-cell specific loci. Age-related epigenomic changes first spike around late-thirties with similar timing and magnitude between sexes, whereas the second spike is earlier and stronger in men. Unexpectedly, genomic differences between sexes increase after age 65, with men having higher innate and pro-inflammatory activity and lower adaptive activity. Impact of age and sex on immune phenotypes can be visualized at https://immune-aging.jax.org to provide insights into future studies

The lethal sex gap: COVID-19

While Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is disrupting lives across the globe for everyone, it has a more devastating impact on the health of older adults, especially that of older men. This pandemic has highlighted the crucial importance of considering an individual’s age and biological sex in the clinic in addition to other confounding diseases (Kuchel, G.A, J Am Geriatr Soc, 67, 203, 2019, Tannenbaum, C., Nature, 575 451-458, 2009) As an interdisciplinary team of scientists in immunology, hematology, genomics, bioinformatics, and geriatrics, we have been studying how age and sex shape the human immune system. Herein we reflect on how our recent findings on the alterations of the immune system in aging might contribute to our current understanding of COVID-19 infection rate and disease risk

Labeotropheus fuelleborniStandardized

Landmark and semilandmark data for Labeotropheus mandibles. This data had been superimposed together with data from Metriaclima zebra, and their F2 hybrids. Size effects have been minimized/standardized for Labeotropheus separately using a multiple regression (see Standard6 in the IMP suite of software). Data is in IMP format with the last column on the right representing centroid size. The 30 columns left of centroid size represent the xy coordinates of regular landmarks

metriaclimaZebraStandardized

Landmark and semilandmark data for Metriaclima mandibles. This data had been superimposed together with data from Labeotropheus, and their F2 hybrids. Size effects have been minimized/standardized for Labeotropheus separately using a multiple regression (see Standard6 in the IMP suite of software). Data is in IMP format with the last column on the right representing centroid size. The 30 columns left of centroid size represent the xy coordinates of regular landmarks

standardizedF2s

Landmark and semilandmark data for F2 hybrids. This data had been superimposed together with data from Metriaclima zebra,and Labeotropheus. Size effects have been minimized/standardized for each of F2 Labeotrophues and Metriaclima separately using a multiple regression (see Standard6 in the IMP suite of software). Data is in IMP format with the last column on the right representing centroid size. The 30 columns left of centroid size represent the xy coordinates of regular landmarks

A multivariate genome-wide association study of wing shape in Drosophila melanogaster

Due to the complexity of genotype–phenotype relationships, simultaneous analyses of genomic associations with multiple traits will be more powerful and informative than a series of univariate analyses. However, in most cases, studies of genotype–phenotype relationships have been analyzed only one trait at a time. Here, we report the results of a fully integrated multivariate genome-wide association analysis of the shape of the Drosophila melanogaster wing in the Drosophila Genetic Reference Panel. Genotypic effects on wing shape were highly correlated between two different laboratories. We found 2396 significant SNPs using a 5% false discovery rate cutoff in the multivariate analyses, but just four significant SNPs in univariate analyses of scores on the first 20 principal component axes. One quarter of these initially significant SNPs retain their effects in regularized models that take into account population structure and linkage disequilibrium. A key advantage of multivariate analysis is that the direction of the estimated phenotypic effect is much more informative than a univariate one. We exploit this fact to show that the effects of knockdowns of genes implicated in the initial screen were on average more similar than expected under a null model. A subset of SNP effects were replicable in an unrelated panel of inbred lines. Association studies that take a phenomic approach, considering many traits simultaneously, are an important complement to the power of genomics.This work was supported by National Institute of General Medical Sciences grant 1R01 GM-094424-01 to I.D. and D.H., U.S. National Science Foundation Division of Environmental Biology grants (www.nsf.gov) 0129219 to D.H. and E.J.M. and 1556774 to D.H., and a Natural Sciences and Engineering Research Council of Canada Discovery Award to I.D.Peer reviewe

Determination of PV Generator I-V/P-V Characteristic Curves Using a DC-DC Converter Controlled by a Virtual Instrument

A versatile measurement system for systematic testing and measurement of the evolution of the I-V characteristic curves of photovoltaic panels or arrays (PV generators) is proposed in this paper. The measurement system uses a circuit solution based on DC-DC converters that involves several advantages relative to traditional methods: simple structure, scalability, fast response, and low cost. The measurement of the desired characteristics of PV generators includes high speed of response and high fidelity. The prototype system built is governed by a microcontroller, and experimental results prove the proposed measurement system useful. A virtual instrument (VI) was developed for full system control from a computer. The developed system enables monitoring the suitable operation of a PV generator in real time, since it allows comparing its actual curves with those provided by the manufacturer.This work is a contribution of the DPI2010-17123 Project supported by the Spanish Ministry of Education and Science and the TEP-6124 Project supported by the Regional Govern- ment of Andalusia (Spain). Both Projects are also supported by the European Union Regional Development Fund

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks

<div><p>Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. <b>AVAILABILITY:</b> QuIN’s web server is available at <a href="http://quin.jax.org" target="_blank">http://quin.jax.org</a> QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: <a href="https://github.com/UcarLab/QuIN/" target="_blank">https://github.com/UcarLab/QuIN/</a>.</p></div