Endothelin 1 levels in relation to clinical presentation and outcome of Henoch Schonlein purpura

<p>Abstract</p> <p>Background</p> <p>Henoch Schonlein purpura (HSP) is a common vasculitis of small vessels whereas endothelin-1 (ET-1) is usually reported elevated in vasculities and systematic inflammation. The aim of the present study was to investigate whether ET-1 levels are correlated with the clinical presentation and the outcome of HSP.</p> <p>Methods</p> <p>The study sample consisted of thirty consecutive patients with HSP. An equal number of healthy patients of similar age and the same gender were served as controls. The patients' age range was 2–12.6 years with a mean ± SD = 6.3 ± 3 years. All patients had a physical examination with a renal, and an overall clinical score. Blood and urinary biochemistry, immunology investigation, a skin biopsy and ET-1 measurements in blood and urine samples were made at presentation, 1 month later and 1 year after the appearance of HSP. The controls underwent the same investigation with the exception of skin biopsy.</p> <p>Results</p> <p>ET-1 levels in plasma and urine did not differ between patients and controls at three distinct time points. Furthermore the ET-1 were not correlated with the clinical score and renal involvement was independent from the ET-1 measurements. However, the urinary ET-1 levels were a significant predictor of the duration of the acute phase of HSP (HR = 0.98, p = 0.032, CI0.96–0.99). The ET-1 levels did not correlate with the duration of renal involvement.</p> <p>Conclusion</p> <p>Urinary ET-1 levels are a useful marker for the duration of the acute phase of HSP but not for the length of renal involvement.</p

Capturing wheat phenotypes at the genome level

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence

Supplementary File for Capturing wheat phenotypes at the genome level

Supplementary S1: Yield and related traits in bread wheat. Table S1: Examples of genomic regions, candidate and cloned genes for yield and related traits in bread wheat. Supplementary S2: Drought tolerance. Table S2: Examples of genomic regions and candidate genes for drought tolerance. Supplementary S3: Heat tolerance. Table S3. Examples of genomic regions and candidate genes for heat tolerance. Supplementary S4: salinity tolerance in bread wheat. Table S4. Examples of genomic regions and candidate genes for salinity tolerance in bread wheat. Supplementary S5: Frost tolerance. Supplementary S6: Disease resistance. Table S5. Examples of genomic regions, candidate and cloned genes mapped for disease resistance in wheat species. Supplementary S7 insect and mite resistance. Table S6. Examples of genomic regions and candidate genes mapped for insect and mite resistance. Supplementary S8: Quality traits. Table S7. Examples of genomic regions, candidate and cloned genes for quality traits.Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.Peer reviewe

Globally, songs and instrumental melodies are slower and higher and use more stable pitches than speech: A Registered Report

Both music and language are found in all known human societies, yet no studies have compared similarities and differences between song, speech, and instrumental music on a global scale. In this Registered Report, we analyzed two global datasets: (i) 300 annotated audio recordings representing matched sets of traditional songs, recited lyrics, conversational speech, and instrumental melodies from our 75 coauthors speaking 55 languages; and (ii) 418 previously published adult-directed song and speech recordings from 209 individuals speaking 16 languages. Of our six preregistered predictions, five were strongly supported: Relative to speech, songs use (i) higher pitch, (ii) slower temporal rate, and (iii) more stable pitches, while both songs and speech used similar (iv) pitch interval size and (v) timbral brightness. Exploratory analyses suggest that features vary along a “musi-linguistic” continuum when including instrumental melodies and recited lyrics. Our study provides strong empirical evidence of cross-cultural regularities in music and speech

Wheat Long Noncoding RNAs from Organelle and Nuclear Genomes Carry Conserved microRNA Precursors Which May Together Comprise Intricate Networks in Insect Responses

Long noncoding RNAs (lncRNAs) are a diverse class of noncoding RNAs that are typically longer than 200 nucleotides but lack coding potentials. Advances in deep sequencing technologies enabled a better exploration of this type of noncoding transcripts. The poor sequence conservation, however, complicates the identification and annotation of lncRNAs at a large scale. Wheat is among the leading food staples worldwide whose production is threatened by both biotic and abiotic stressors. Here, we identified putative lncRNAs from durum wheat varieties that differ in stem solidness, a major source of defense against wheat stem sawfly, a devastating insect pest. We also analyzed and annotated lncRNAs from two bread wheat varieties, resistant and susceptible to another destructive pest, orange wheat blossom midge, with and without infestation. Several putative lncRNAs contained potential precursor sequences and/or target regions for microRNAs, another type of regulatory noncoding RNAs, which may indicate functional networks. Interestingly, in contrast to lncRNAs themselves, microRNAs with potential precursors within the lncRNA sequences appeared to be highly conserved at the sequence and family levels. We also observed a few putative lncRNAs that have perfect to near-perfect matches to organellar genomes, supporting the recent observations that organellar genomes may contribute to the noncoding transcript pool of the cell

Omics, epigenetics, and genome editing techniques for food and nutritional security

The incredible success of crop breeding and agricultural innovation in the last century greatly contributed to the Green Revolution, which significantly increased yields and ensures food security, despite the population explosion. However, new challenges such as rapid climate change, deteriorating soil, and the accumulation of pollutants require much faster responses and more effective solutions that cannot be achieved through traditional breeding. Further prospects for increasing the efficiency of agriculture are undoubtedly associated with the inclusion in the breeding strategy of new knowledge obtained using high-throughput technologies and new tools in the future to ensure the design of new plant genomes and predict the desired phenotype. This article provides an overview of the current state of research in these areas, as well as the study of soil and plant microbiomes, and the prospective use of their potential in a new field of microbiome engineering. In terms of genomic and phenomic predictions, we also propose an integrated approach that combines high-density genotyping and high-throughput phenotyping techniques, which can improve the prediction accuracy of quantitative traits in crop species