A Genome Wide Association Study of arabinoxylan content in 2-row spring barley grain

In barley endosperm arabinoxylan (AX) is the second most abundant cell wall polysaccharide and in wheat it is the most abundant polysaccharide in the starchy endosperm walls of the grain. AX is one of the main contributors to grain dietary fibre content providing several health benefits including cholesterol and glucose lowering effects, and antioxidant activities. Due to its complex structural features, AX might also affect the downstream applications of barley grain in malting and brewing. Using a high pressure liquid chromatography (HPLC) method we quantified AX amounts in mature grain in 128 spring 2-row barley accessions. Amounts ranged from ~ 5.2 μg/g to ~ 9 μg/g. We used this data for a Genome Wide Association Study (GWAS) that revealed three significant quantitative trait loci (QTL) associated with grain AX levels which passed a false discovery threshold (FDR) and are located on two of the seven barley chromosomes. Regions underlying the QTLs were scanned for genes likely to be involved in AX biosynthesis or turnover, and strong candidates, including glycosyltransferases from the GT43 and GT61 families and glycoside hydrolases from the GH10 family, were identified. Phylogenetic trees of selected gene families were built based on protein translations and were used to examine the relationship of the barley candidate genes to those in other species. Our data reaffirms the roles of existing genes thought to contribute to AX content, and identifies novel QTL (and candidate genes associated with them) potentially influencing the AX content of barley grain. One potential outcome of this work is the deployment of highly associated single nucleotide polymorphisms markers in breeding programs to guide the modification of AX abundance in barley grain

A Program for At-Risk High School Students Informed by Evolutionary Science

Improving the academic performance of at-risk high school students has proven difficult, often calling for an extended day, extended school year, and other expensive measures. Here we report the results of a program for at-risk 9th and 10th graders in Binghamton, New York, called the Regents Academy that takes place during the normal school day and year. The design of the program is informed by the evolutionary dynamics of cooperation and learning, in general and for our species as a unique product of biocultural evolution. Not only did the Regents Academy students outperform their comparison group in a randomized control design, but they performed on a par with the average high school student in Binghamton on state-mandated exams. All students can benefit from the social environment provided for at-risk students at the Regents Academy, which is within the reach of most public school districts

International Consensus Statement on Rhinology and Allergy: Rhinosinusitis

Background: The 5 years since the publication of the first International Consensus Statement on Allergy and Rhinology: Rhinosinusitis (ICAR‐RS) has witnessed foundational progress in our understanding and treatment of rhinologic disease. These advances are reflected within the more than 40 new topics covered within the ICAR‐RS‐2021 as well as updates to the original 140 topics. This executive summary consolidates the evidence‐based findings of the document. Methods: ICAR‐RS presents over 180 topics in the forms of evidence‐based reviews with recommendations (EBRRs), evidence‐based reviews, and literature reviews. The highest grade structured recommendations of the EBRR sections are summarized in this executive summary. Results: ICAR‐RS‐2021 covers 22 topics regarding the medical management of RS, which are grade A/B and are presented in the executive summary. Additionally, 4 topics regarding the surgical management of RS are grade A/B and are presented in the executive summary. Finally, a comprehensive evidence‐based management algorithm is provided. Conclusion: This ICAR‐RS‐2021 executive summary provides a compilation of the evidence‐based recommendations for medical and surgical treatment of the most common forms of RS

Lateralized learning for robustness against adversarial attacks in a visual classification system

Deep learning is an important field of machine learning. It is playing a critical role in a variety of applications ranging from self-driving cars to security and surveillance. However, deep networks have deep flaws. For example, they are highly vulnerable to adversarial attacks. One reason may be the homogeneous nature of their knowledge representation, which allows a single disruptive pattern to cause miss-classification. Biological intelligence has lateral asymmetry, which allows heterogeneous, modular learning at different levels of abstraction, enabling different representations of the same object. This work aims to incorporate lateralization and modular learning at different levels of abstraction in an evolutionary machine learning system. The results of image classification tasks show that the lateralized system efficiently learns hierarchical distributions of knowledge, demonstrating performance that is similar to (or better than) other state-of-the-art deep systems as it reasons using multiple representations. Crucially, the novel system outperformed all the state-of-the-art deep models for the classification of normal and adversarial images by 0.43% - 2.56% and 2.15% - 25.84%, respectively. Lateralisation enabled the system to exhibit robustness beyond previous work, which advocates for the creation of data sets that enable components of objects and the objects themselves to be learned specifically or in an end-to-end manner.</p