Transcatheter Aortic Valve Replacement: Comprehensive Review and Present Status

Aortic stenosis is the most common valvular heart disease in the developed world. About 7% of the population over age 65 years suffers from degenerative aortic stenosis. The prognosis of patients with symptomatic severe aortic stenosis is dismal without valve replacement. Even though the American College of Cardiology recommends aortic valve replacement to treat this condition as a class I recommendation, approximately one third of these patients over the age of 75 years are not referred for surgery. Typically, this is from concern about prohibitive surgical risk associated with patient frailty, comorbidities, age, and severe left ventricular dysfunction

Repertoire of virus-derived small RNAs produced by mosquito and mammalian cells in response to dengue virus infection

AbstractRNA interference (RNAi) is the major defense of many arthropods against arthropod-borne RNA viruses (arboviruses), but the role of RNAi in vertebrate immunity to arboviruses is not clear. RNA viruses can trigger RNAi in vertebrate cells, but the vertebrate interferon response may obscure this interaction. We quantified virus-derived small RNAs (vRNAs) generated by mosquito (U4.4) cells and interferon-deficient (Vero) and interferon-competent (HuH-7) mammalian cells infected with a single isolate of mosquito-borne dengue virus. Mosquito cells produced significantly more vRNAs than mammalian cells, and mosquito cell vRNAs were derived from both the positive- and negative-sense dengue genomes whereas mammalian cell vRNAs were derived primarily from positive-sense genome. Mosquito cell vRNAs were predominantly 21 nucleotides in length whereas mammalian cell vRNAs were between 12 and 36 nucleotides with a modest peak at 24 nucleotides. Hot-spots, regions of the virus genome that generated a disproportionate number of vRNAs, overlapped among the cell lines

Exploring structural variation and gene family architecture with De Novo assemblies of 15 Medicago genomes

Abstract Background Previous studies exploring sequence variation in the model legume, Medicago truncatula, relied on mapping short reads to a single reference. However, read-mapping approaches are inadequate to examine large, diverse gene families or to probe variation in repeat-rich or highly divergent genome regions. De novo sequencing and assembly of M. truncatula genomes enables near-comprehensive discovery of structural variants (SVs), analysis of rapidly evolving gene families, and ultimately, construction of a pan-genome. Results Genome-wide synteny based on 15 de novo M. truncatula assemblies effectively detected different types of SVs indicating that as much as 22% of the genome is involved in large structural changes, altogether affecting 28% of gene models. A total of 63 million base pairs (Mbp) of novel sequence was discovered, expanding the reference genome space for Medicago by 16%. Pan-genome analysis revealed that 42% (180 Mbp) of genomic sequences is missing in one or more accession, while examination of de novo annotated genes identified 67% (50,700) of all ortholog groups as dispensable – estimates comparable to recent studies in rice, maize and soybean. Rapidly evolving gene families typically associated with biotic interactions and stress response were found to be enriched in the accession-specific gene pool. The nucleotide-binding site leucine-rich repeat (NBS-LRR) family, in particular, harbors the highest level of nucleotide diversity, large effect single nucleotide change, protein diversity, and presence/absence variation. However, the leucine-rich repeat (LRR) and heat shock gene families are disproportionately affected by large effect single nucleotide changes and even higher levels of copy number variation. Conclusions Analysis of multiple M. truncatula genomes illustrates the value of de novo assemblies to discover and describe structural variation, something that is often under-estimated when using read-mapping approaches. Comparisons among the de novo assemblies also indicate that different large gene families differ in the architecture of their structural variation

Genome And Secretome Analysis Of The Hemibiotrophic Fungal Pathogen, Moniliophthora Roreri, Which Causes Frosty Pod Rot Disease Of Cacao: Mechanisms Of The Biotrophic And Necrotrophic Phases

Background: The basidiomycete Moniliophthora roreri is the causal agent of Frosty pod rot (FPR) disease of cacao (Theobroma cacao), the source of chocolate, and FPR is one of the most destructive diseases of this important perennial crop in the Americas. This hemibiotroph infects only cacao pods and has an extended biotrophic phase lasting up to sixty days, culminating in plant necrosis and sporulation of the fungus without the formation of a basidiocarp.Results: We sequenced and assembled 52.3 Mb into 3,298 contigs that represent the M. roreri genome. Of the 17,920 predicted open reading frames (OFRs), 13,760 were validated by RNA-Seq. Using read count data from RNA sequencing of cacao pods at 30 and 60 days post infection, differential gene expression was estimated for the biotrophic and necrotrophic phases of this plant-pathogen interaction. The sequencing data were used to develop a genome based secretome for the infected pods. Of the 1,535 genes encoding putative secreted proteins, 1,355 were expressed in the biotrophic and necrotrophic phases. Analysis of the data revealed secretome gene expression that correlated with infection and intercellular growth in the biotrophic phase and invasive growth and plant cellular death in the necrotrophic phase.Conclusions: Genome sequencing and RNA-Seq was used to determine and validate the Moniliophthora roreri genome and secretome. High sequence identity between Moniliophthora roreri genes and Moniliophthora perniciosa genes supports the taxonomic relationship with Moniliophthora perniciosa and the relatedness of this fungus to other basidiomycetes. Analysis of RNA-Seq data from infected plant tissues revealed differentially expressed genes in the biotrophic and necrotrophic phases. 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The Usefulness of Gridded Climate Data Products in Characterizing Climate Variability and Assessing Crop Production

A sparse rain gauge network in dryland regions has been a major challenge for accessing high quality observed data needed to understand variability and trends in climate. Gridded estimates of weather parameters produced through data assimilation algorithms that integrate satellite and irregularly distributed on-ground observations from multiple observing networks are a potential alternative. Questions remain about the application of such climate data sources for assessing climate variability and crop productivity. This study assessed the usefulness and limitations of gridded data from four different sources i.e. AgMERRA, CHIRPS, NASA Power, and TAMSAT in estimating climate impacts on crop productivity using Agricultural Production Systems Simulator (APSIM). The study used data for 11 locations from Africa and India. The agreement between these data sets and observed data both in the amount and distribution of rainfall was evaluated before and after bias correction statistically. A deviation of more than 100 mm per season was observed in 13%, 20%, 25%, and 40% of the seasons in CHIRPS, AgMERRA, NASA Power, and TAMSAT data sets respectively. The differences were reduced significantly when data sets were bias-corrected. The number of rainy days is better estimated by TAMSAT and CHIRPS with a deviation of 4% and 6% respectively while AgMERRA and NASA Power overestimated by 28% and 67% respectively. The influence of these differences on crop growth and productivity was estimated by simulating maize yields with APSIM. Simulated crop yields with all gridded data sets were poorly correlated with observed data. The normalized root-mean-square error (NRMSE) of maize yield simulated with observed and gridded data was <30% for two locations in the case of AgMERRA and CHIRPS and three locations in the case of NASA Power. The NRMSE was > 30% for all locations with TAMSAT data. When yields were simulated with data after bias correction using the linear scaling technique, results were slightly improved. The results of our study thus indicate that the gridded data sets are usefully applied for characterizing climate variability, i.e. trends and seasonality in rainfall, however their use in driving crop model simulations of smallholder farm level production should be carefully interpreted

Development of Morphologically engineered Flower-like Hafnium-Doped ZnO with Experimental and DFT Validation for Low-Temperature and Ultrasensitive Detection of NOX Gas

This is the final version. Available on open access from the American Chemical Society via the DOI in this recordSubstitutional doping and different nanostructures of ZnO have rendered it an effective sensor for the detection of volatile organic compounds in real-time atmosphere. However, the low selectivity of ZnO sensors limits their applications. Herein, hafnium (Hf)-doped ZnO (Hf-ZnO) nanostructures are developed by the hydrothermal method for high selectivity of hazardous NOX gas in the atmosphere, substantially portraying the role of doping concentration on the enhancement of structural, optical, and sensing behavior. ZnO microspheres with 5% Hf doping showed excellent sensing and detected 22 parts per billion (ppb) NOX gas in the atmosphere, within 24 s, which is much faster than ZnO (90 s), and rendered superior sensing ability (S = 67) at a low temperature (100 °C) compared to ZnO (S = 40). The sensor revealed exceptional stability under humid air (S = 55 at 70% RH), suggesting a potential of 5% Hf-ZnO as a new stable sensing material. Density functional theory (DFT) and other characterization analyses revealed that the high sensing activity of 5% Hf-ZnO is attributed to the accessibility of more adsorption sites arising due to charge distortion, increased oxygen vacancies concentration, Lewis acid base, porous morphology, small particle size (5 nm), and strong bond interaction amidst NO2 molecule with ZnO-Hf-Ovacancy sites, resulting from the substitution of the host cation (Zn2+) with doping cation (Hf4+).Korea government (Ministry of Education)Engineering and Physical Sciences Research Council (EPSRC

Thermal analysis of water in reinforced plasma-polymerised poly(2-hydroxyethyl acrylate) hydrogels

Thermal analysis of water in reinforce hydrogels of plasma-polymerised poly(2-hydroxyethyl acrylate) (plPHEA) grafted onto macroporous poly(methyl methacrylate) (PMMA) are explained in a simple thermodynamic framework based on the transition diagram. Water in bulk PHEA was also analysed for comparison with plPHEA. These two hydrophilic polymers were prepared with a broad range of water mass fractions from 0.05 to 0.72. Thermal transition diagrams of water/PHEA and water/plPHEA were determined showing less undercooling of water crystallisation in plPHEA than in PHEA. Kinetics of water crystallisation for high and low water contents were studied in both hydrophilic systems following several thermal treatments. Water crystallises much faster in plPHEA than in PHEA for high water contents. For low water contents, crystallisation becomes possible holding at 30 degrees C for some time due to water segregation in both PHEA systems. However, much less water is segregated from the water/plPHEA mixture due to the influence of the hydrophobic component.This work was supported by a Marie Curie Host Fellowship and by the Spanish Science and Technology Ministry through the MAT2001-2678-C02-01 and MAT2002-04239-C03-03 projects. CIBER-BBN is an initiative funded by the VI National R&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions and financed by the Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Serrano Aroca, Á.; Monleón Pradas, M.; Gómez Ribelles, JL.; Rault, J. (2015). Thermal analysis of water in reinforced plasma-polymerised poly(2-hydroxyethyl acrylate) hydrogels. European Polymer Journal. 72:523-534. https://doi.org/10.1016/j.eurpolymj.2015.05.032S5235347

Hybrid assembly with long and short reads improves discovery of gene family expansions

BACKGROUND: Long-read and short-read sequencing technologies offer competing advantages for eukaryotic genome sequencing projects. Combinations of both may be appropriate for surveys of within-species genomic variation. METHODS: We developed a hybrid assembly pipeline called "Alpaca" that can operate on 20X long-read coverage plus about 50X short-insert and 50X long-insert short-read coverage. To preclude collapse of tandem repeats, Alpaca relies on base-call-corrected long reads for contig formation. RESULTS: Compared to two other assembly protocols, Alpaca demonstrated the most reference agreement and repeat capture on the rice genome. On three accessions of the model legume Medicago truncatula, Alpaca generated the most agreement to a conspecific reference and predicted tandemly repeated genes absent from the other assemblies. CONCLUSION: Our results suggest Alpaca is a useful tool for investigating structural and copy number variation within de novo assemblies of sampled populations

A piece of the human heart: variance of protein phosphorylation in left ventricular samples from end-stage primary cardiomyopathy patients

Cardiomyocyte contraction is regulated by phosphorylation of sarcomeric proteins. Throughout the heart regional and transmural differences may exist in protein phosphorylation. In addition, phosphorylation of sarcomeric proteins is altered in cardiac disease. Heterogeneity in protein phosphorylation may be larger in hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM) as it may be caused by multiple mutations in genes encoding different sarcomeric proteins. Moreover, HCM is characterized by asymmetric remodelling of the heart. In the present study we assessed if local differences in sarcomeric protein phosphorylation are more evident in primary HCM or DCM than in non-failing donors. Thereto, phosphorylation of the two main target proteins of the beta-adrenergic receptor pathway, troponin I (cTnI) and myosin binding protein C (cMyBP-C) was analysed in different parts in the free left ventricular wall of end–stage failing HCM and DCM patients and donors obtained during transplant surgery. Intra-patient variability in protein phosphorylation within tissue samples of approximately 2 g wet weight was comparable between donor, HCM and DCM samples and could partly be attributed to the precision of the technique. Thus, our data indicate that within the precision of the measurements small, biopsy-sized cardiac tissue samples are representative for the region of the free left ventricular wall from which they were obtained

Meghdoot—A Mobile App to Access Location-Specific Weather-Based Agro-Advisories Pan India

Timely agricultural advisories to farmers can enhance their decision-making and reduce production risk under challenging weather conditions. To enhance access to relevant climate information services in India, a mobile application called Meghdoot was designed to deliver weather information and crop-specific advisories, as a joint initiative of the India Meteorological Department (IMD), Indian Institution for Tropical Meteorology (IITM), Indian Council for Agricultural Research (ICAR) and the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). Building on IMD’s District Agrometeorological Advisory Service (DAAS) which issues crop-specific weather-based agro-advisories twice a week for all districts in India, the Meghdoot app makes available observed weather recordings, forecasts, and warnings generated by IMD and IITM. This working paper describes the concept design, the framework and a preliminary user analysis of the Meghdoot mobile application. Meghdoot mobile app is available on Google Play (Google Play Store) as well as Apple App Store. Since its inception more than two years ago, Meghdoot has received a good response with 200,000+ downloads/installs and an average rating of 3.3/5.0 by 863 app users (as of July 26, 2021) on Google Play(Google Play Store)