Power-Based Droop Control in DC Microgrids Enabling Seamless Disconnection From Upstream Grids

This paper proposes a local power-based droop controller for distributed energy resource converters in dc microgrids that are connected to upstream grids by grid-interface converters. During normal operation, the grid-interface converter imposes the microgrid bus voltage, and the proposed controller allows power flow regulation at distributed energy resource converters\u2019 output. On the other hand, during abnormal operation of the grid-interface converter (e.g., due to faults in the upstream grid), the proposed controller allows bus voltage regulation by droop control. Notably, the controller can autonomously convert from power flow control to droop control, without any need of bus voltage variation detection schemes or communication with other microgrid components, which enables seamless transitions between these two modes of operation. Considering distributed energy resource converters employing the power-based droop control, the operation modes of a single converter and of the whole microgrid are defined and investigated herein. The controller design is also introduced. Furthermore, the power sharing performance of this control approach is analyzed and compared with that of classical droop control. The experimental results from a laboratory-scale dc microgrid prototype are reported to show the final performances of the proposed power-based droop control

metaQuantome : an integrated, quantitative metaproteomics approach reveals connections between taxonomy and protein function in complex microbiomes

Microbiome research offers promising insights into the impact of microorganisms on biological systems. Metaproteomics, the study of microbial proteins at the community level, integrates genomic, transcriptomic, and proteomic data to determine the taxonomic and functional state of a microbiome. However, standard metaproteomics software is subject to several limitations, commonly supporting only spectral counts, emphasizing exploratory analysis rather than hypothesis testing and rarely offering the ability to analyze the interaction of function and taxonomy -that is, which taxa are responsible for different processes. Here we present metaQuantome, a novel, multifaceted software suite that analyzes the state of a microbiome by leveraging complex taxonomic and functional hierarchies to summarize peptide-level quantitative information, emphasizing label-free intensity-based methods. For experiments with multiple experimental conditions, metaQuantome offers differential abundance analysis, principal components analysis, and clustered heat map visualizations, as well as exploratory analysis for a single sample or experimental condition. We benchmark metaQuantome analysis against standard methods, using two previously published datasets: (1) an artificially assembled microbial community dataset (taxonomy benchmarking) and (2) a dataset with a range of recombinant human proteins spiked into an Escherichia coli background (functional benchmarking). Furthermore, we demonstrate the use of metaQuantome on a previously published human oral microbiome dataset. In both the taxonomic and functional benchmarking analyses, metaQuantome quantified taxonomic and functional terms more accurately than standard summarization- based methods. We use the oral microbiome dataset to demonstrate metaQuantome's ability to produce publication- quality figures and elucidate biological processes of the oral microbiome. metaQuantome enables advanced investigation of metaproteomic datasets, which should be broadly applicable to microbiome-related research. In the interest of accessible, flexible, and reproducible analysis, metaQuantome is open source and available on the command line and in Galaxy

Inheritance, Biochemical Abnormalities, and Clinical Features of Feline Mucolipidosis II: The First Animal Model of Human I-Cell Disease

Mucolipidosis II (ML II), also called I-cell disease, is a unique lysosomal storage disease caused by deficient activity of the enzyme N-acetylglucosamine-1-phosphotransferase, which leads to a failure to internalize enzymes into lysosomes. We report on a colony of domestic shorthair cats with ML II that was established from a half-sibling male of an affected cat. Ten male and 9 female kittens out of 89 kittens in 26 litters born to clinically normal parents were affected; this is consistent with an autosomal recessive mode of inheritance. The activities of three lysosomal enzymes from affected kittens, compared to normal adult control cats, were high in serum (11-73 times normal) but low in cultured fibroblasts (9-56% of normal range) that contained inclusion bodies (I-cells), reflecting the unique enzyme defect in ML II. Serum lysosomal enzyme activities of adult obligate carriers were intermediate between normal and affected values. Clinical features in affected kittens were observed from birth and included failure to thrive, behavioral dullness, facial dysmorphia, and ataxia. Radiographic lesions included metaphyseal flaring, radial bowing, joint laxity, and vertebral fusion. In contrast to human ML II, diffuse retinal degeneration leading to blindness by 4 months of age was seen in affected kittens. All clinical signs were progressive and euthanasia or death invariably occurred within the first few days to 7 months of life, often due to upper respiratory disease or cardiac failure. The clinical and radiographic features, lysosomal enzyme activities, and mode of inheritance are homologous with ML II in humans. Feline ML II is currently the only animal model in which to study the pathogenesis of and therapeutic interventions for this unique storage diseas

Instrumentation and Measurement Strategy for the NOAA SENEX Aircraft Campaign as Part of the Southeast Atmosphere Study 2013

Natural emissions of ozone-and-aerosol-precursor gases such as isoprene and monoterpenes are high in the southeastern US. In addition, anthropogenic emissions are significant in the southeastern US and summertime photochemistry is rapid. The NOAA-led SENEX (Southeast Nexus) aircraft campaign was one of the major components of the Southeast Atmosphere Study (SAS) and was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants. During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. Here we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign. The aircraft, its capabilities and standard measurements are described. The instrument payload is summarized including detection limits, accuracy, precision and time resolutions for all gas-and-aerosol phase instruments. The inter-comparisons of compounds measured with multiple instruments on the NOAA WP-3D are presented and were all within the stated uncertainties, except two of the three NO 2 measurements. The SENEX flights included day- and nighttime flights in the southeastern US as well as flights over areas with intense shale gas extraction (Marcellus, Fayetteville and Haynesville shale). We present one example flight on 16 June 2013, which was a daytime flight over the Atlanta region, where several crosswind transects of plumes from the city and nearby point sources, such as power plants, paper mills and landfills, were flown. The area around Atlanta has large biogenic isoprene emissions, which provided an excellent case for studying the interactions between biogenic and anthropogenic emissions. In this example flight, chemistry in and outside the Atlanta plumes was observed for several hours after emission. The analysis of this flight showcases the strategies implemented to answer some of the main SENEX science questions

Integration of Global Signaling Pathways, cAMP-PKA, MAPK and TOR in the Regulation of FLO11

The budding yeast, Saccharomyces cerevisiae, responds to various environmental cues by invoking specific adaptive mechanisms for their survival. Under nitrogen limitation, S. cerevisiae undergoes a dimorphic filamentous transition called pseudohyphae, which helps the cell to forage for nutrients and reach an environment conducive for growth. This transition is governed by a complex network of signaling pathways, namely cAMP-PKA, MAPK and TOR, which controls the transcriptional activation of FLO11, a flocculin gene that encodes a cell wall protein. However, little is known about how these pathways co-ordinate to govern the conversion of nutritional availability into gene expression. Here, we have analyzed an integrative network comprised of cAMP-PKA, MAPK and TOR pathways with respect to the availability of nitrogen source using experimental and steady state modeling approach. Our experiments demonstrate that the steady state expression of FLO11 was bistable over a range of inducing ammonium sulphate concentration based on the preculturing condition. We also show that yeast switched from FLO11 expression to accumulation of trehalose, a STRE response controlled by a transcriptional activator Msn2/4, with decrease in the inducing concentration to complete starvation. Steady state analysis of the integrative network revealed the relationship between the environment, signaling cascades and the expression of FLO11. We demonstrate that the double negative feedback loop in TOR pathway can elicit a bistable response, to differentiate between vegetative growth, filamentous growth and STRE response. Negative feedback on TOR pathway function to restrict the expression of FLO11 under nitrogen starved condition and also with re-addition of nitrogen to starved cells. In general, we show that these global signaling pathways respond with specific sensitivity to regulate the expression of FLO11 under nitrogen limitation. The holistic steady state modeling approach of the integrative network revealed how the global signaling pathways could differentiate between multiple phenotypes

Genome-Wide Progesterone Receptor Binding: Cell Type-Specific and Shared Mechanisms in T47D Breast Cancer Cells and Primary Leiomyoma Cells

Progesterone, via its nuclear receptor (PR), exerts an overall tumorigenic effect on both uterine fibroid (leiomyoma) and breast cancer tissues, whereas the antiprogestin RU486 inhibits growth of these tissues through an unknown mechanism. Here, we determined the interaction between common or cell-specific genome-wide binding sites of PR and mRNA expression in RU486-treated uterine leiomyoma and breast cancer cells.ChIP-sequencing revealed 31,457 and 7,034 PR-binding sites in breast cancer and uterine leiomyoma cells, respectively; 1,035 sites overlapped in both cell types. Based on the chromatin-PR interaction in both cell types, we statistically refined the consensus progesterone response element to G•ACA• • •TGT•C. We identified two striking differences between uterine leiomyoma and breast cancer cells. First, the cis-regulatory elements for HSF, TEF-1, and C/EBPα and β were statistically enriched at genomic RU486/PR-targets in uterine leiomyoma, whereas E2F, FOXO1, FOXA1, and FOXF sites were preferentially enriched in breast cancer cells. Second, 51.5% of RU486-regulated genes in breast cancer cells but only 6.6% of RU486-regulated genes in uterine leiomyoma cells contained a PR-binding site within 5 kb from their transcription start sites (TSSs), whereas 75.4% of RU486-regulated genes contained a PR-binding site farther than 50 kb from their TSSs in uterine leiomyoma cells. RU486 regulated only seven mRNAs in both cell types. Among these, adipophilin (PLIN2), a pro-differentiation gene, was induced via RU486 and PR via the same regulatory region in both cell types.Our studies have identified molecular components in a RU486/PR-controlled gene network involved in the regulation of cell growth, cell migration, and extracellular matrix function. Tissue-specific and common patterns of genome-wide PR binding and gene regulation may determine the therapeutic effects of antiprogestins in uterine fibroids and breast cancer

Differential Impact of Tetratricopeptide Repeat Proteins on the Steroid Hormone Receptors

Tetratricopeptide repeat (TPR) motif containing co-chaperones of the chaperone Hsp90 are considered control modules that govern activity and specificity of this central folding platform. Steroid receptors are paradigm clients of Hsp90. The influence of some TPR proteins on selected receptors has been described, but a comprehensive analysis of the effects of TPR proteins on all steroid receptors has not been accomplished yet.We compared the influence of the TPR proteins FK506 binding proteins 51 and 52, protein phosphatase-5, C-terminus of Hsp70 interacting protein, cyclophillin 40, hepatitis-virus-B X-associated protein-2, and tetratricopeptide repeat protein-2 on all six steroid hormone receptors in a homogeneous mammalian cell system. To be able to assess each cofactor's effect on the transcriptional activity of on each steroid receptor we employed transient transfection in a reporter gene assay. In addition, we evaluated the interactions of the TPR proteins with the receptors and components of the Hsp90 chaperone heterocomplex by coimmunoprecipitation. In the functional assays, corticosteroid and progesterone receptors displayed the most sensitive and distinct reaction to the TPR proteins. Androgen receptor's activity was moderately impaired by most cofactors, whereas the Estrogen receptors' activity was impaired by most cofactors only to a minor degree. Second, interaction studies revealed that the strongly receptor-interacting co-chaperones were all among the inhibitory proteins. Intriguingly, the TPR-proteins also differentially co-precipitated the heterochaperone complex components Hsp90, Hsp70, and p23, pointing to differences in their modes of action.The results of this comprehensive study provide important insight into chaperoning of diverse client proteins via the combinatorial action of (co)-chaperones. The differential effects of the TPR proteins on steroid receptors bear on all physiological processes related to steroid hormone activity

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks