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Pianists experience high rates of Playing-Related Musculoskeletal Disorders (PRMDs). Biomechanical factors have been investigated by both researchers and music teachers as potentially significant in PRMD development. Knowledge exchange between the fields of music and science about PRMDs may be beneficial, but differences in language use can make interdisciplinary communication challenging. One potential solution is to translate pedagogical ideas into language that is consistent with biomechanical science. Doing so could improve interdisciplinary communication and allow for scientific examination of pedagogical ideas. However, no methods for doing so have been published. To fill this gap, we developed a methodological framework with two stages for translating ideas about piano technique into scientific language: Stage 1 uses Qualitative Content Analysis to summarize pedagogical content; then, Stage 2 includes an “Analysis of Biomechanical Language,” in which researchers translate the ideas described in Stage 1. Both stages are collaborative and rely on expert consultation to produce an appropriate translation. This article outlines the framework and explains how it was used in an initial study on the Taubman Approach. Further methodological guidance to assist researchers in future studies is given based on some of the challenges encountered in the initial study. The framework and guidance here will allow researchers to carry out more studies of this kind. Because the framework is newly developed, it will likely need to be adapted further as more studies are done.

Researchers have found that many post-secondary music students suffer from physical and mental health issues. However, researchers have mainly studied these problems at the individual level, with little investigation of how music students’ work is shaped by the coordinating effects of policies, texts, and discourses at and beyond their local site. This paper describes a protocol for an international project that will explore the health of music students in the context of their daily work. Using an institutional ethnography approach, we will examine the social organization of music students’ work at three universities: two in Canada and one in Australia. This will be the first set of studies that use institutional ethnography specifically for the purpose of understanding how the social organization of music students’ work shapes their health. Data will be collected using several methods common to institutional ethnography: interviews, focus groups, observations, and collecting texts. Data analysis will begin during the data collection process and proceed in two fluid stages. The first stage will involve a detailed investigation of the pertinent work activities at each music school. The second will involve linking that work to specific social relations within and beyond the institution. After data analysis has been completed at all three sites, findings will be compared to one another to identify commonalities and differences in how students’ work is organized. Findings of the entire project may inform policy-making and lead to positive change at the institutions studied, as well as others where similar social organization may occur. The novel approach described here will provide opportunities to expand current knowledge about music students’ work and health beyond what has been learned through approaches that focus on students’ individual behaviours and attributes.

Behavioural issues can present significant challenges for music educators who work with students with exceptionalities. One key component of behaviour support in the music classroom or studio is empathy, our ability to see the world from the perspective of others. This article presents an empathy-based approach to special music education with four components: 1) Knowing the student's individual characteristics; 2) Identifying the function of behaviour; 3) Identifying lagging skills; and 4) Responding empathetically using the PACE model. It also discusses anxiety as a hidden cause of problematic behaviours and provides an example for applying the approach in context.

Les problemes de comportement représentent parfois des défis importants pour les musiciens éducateurs qui travaillent aupres d'éleves ayant des besoins particuliers. L'empathie, notre capacité a voir le monde du point de vue des autres, peut étre un élément clé du soutien comportemental en classe de musique ou studio d'enseignement privé. Cet article présente une approche de l'éducation musicale spécialisée fondée sur l'empathie se déclinant en quatre volets : 1) la détermination des caractéristiques individuelles de l'éleve; 2) la définition de la fonction du comportement; 3) l'identification des habiletés a acquérir; et 4) l'intervention axée sur l'empathie utilisant le modele PACE. Enfin, l'article aborde l'anxiété comme cause cachée des comportements problématiques et fournit un exemple concret d'application de cette approche.

Background Characterizing large genomic variants is essential to expanding the research and clinical applications of genome sequencing. While multiple data types and methods are available to detect these structural variants (SVs), they remain less characterized than smaller variants because of SV diversity, complexity, and size. These challenges are exacerbated by the experimental and computational demands of SV analysis. Here, we characterize the SV content of a personal genome with Parliament, a publicly available consensus SV-calling infrastructure that merges multiple data types and SV detection methods. Results We demonstrate Parliament’s efficacy via integrated analyses of data from whole-genome array comparative genomic hybridization, short-read next-generation sequencing, long-read (Pacific BioSciences RSII), long-insert (Illumina Nextera), and whole-genome architecture (BioNano Irys) data from the personal genome of a single subject (HS1011). From this genome, Parliament identified 31,007 genomic loci between 100 bp and 1 Mbp that are inconsistent with the hg19 reference assembly. Of these loci, 9,777 are supported as putative SVs by hybrid local assembly, long-read PacBio data, or multi-source heuristics. These SVs span 59 Mbp of the reference genome (1.8%) and include 3,801 events identified only with long-read data. The HS1011 data and complete Parliament infrastructure, including a BAM-to-SV workflow, are available on the cloud-based service DNAnexus. Conclusions HS1011 SV analysis reveals the limits and advantages of multiple sequencing technologies, specifically the impact of long-read SV discovery. With the full Parliament infrastructure, the HS1011 data constitute a public resource for novel SV discovery, software calibration, and personal genome structural variation analysis.

Escherichia coli is a model laboratory bacterium, a species that is widely distributed in the environment, as well as a mutualist and pathogen in its human hosts. As such, E. coli represents an attractive organism to study how environment impacts microbial genome structure and function. Uropathogenic E. coli (UPEC) must adapt to life in several microbial communities in the human body, and has a complex life cycle in the bladder when it causes acute or recurrent urinary tract infection (UTI). Several studies designed to identify virulence factors have focused on genes that are uniquely represented in UPEC strains, whereas the role of genes that are common to all E. coli has received much less attention. Here we describe the complete 5,065,741-bp genome sequence of a UPEC strain recovered from a patient with an acute bladder infection and compare it with six other finished E. coli genome sequences. We searched 3,470 ortholog sets for genes that are under positive selection only in UPEC strains. Our maximum likelihood-based analysis yielded 29 genes involved in various aspects of cell surface structure, DNA metabolism, nutrient acquisition, and UTI. These results were validated by resequencing a subset of the 29 genes in a panel of 50 urinary, periurethral, and rectal E. coli isolates from patients with UTI. These studies outline a computational approach that may be broadly applicable for studying strain-specific adaptation and pathogenesis in other bacteria.

Exome sequencing of 175 autism spectrum disorder parent–child trios reveals that few de novo point mutations have a role in autism spectrum disorder and those that do are distributed across many genes and are incompletely penetrant, further supporting extreme genetic heterogeneity of this spectrum disorder. Heterogeneity in the genetics of autism Although it is well accepted that genetics makes a strong contribution to autism spectrum disorder, most of the underlying causes of the condition remain unknown. Three groups present large-scale exome-sequencing studies of individuals with sporadic autism spectrum disorder, including many parent–child trios and unaffected siblings. The overall message from the three papers is that there is extreme locus heterogeneity among autistic individuals, with hundreds of genes involved in the condition, and with no single gene contributing to more than a small fraction of cases. Sanders et al . report the association of the gene SCN2A , previously identified in epilepsy syndromes, with the risk of autism. Neale et al . find strong evidence that CHD8 and KATNAL2 are autism risk factors. O'Roak et al . observe that a large proportion of the mutated proteins have crucial roles in fundamental developmental pathways, including β-catenin and p53 signalling. Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified 1 , 2 . To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents ( n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes 3 as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.

Background/Objectives: Antibiotic-resistant Staphylococcus aureus represents a growing threat in the modern world, and new antibiotic targets are needed for its successful treatment. One such potential target is the pyridoxal-5′-phosphate (PLP)-dependent cysteine desulfurase (SaSufS) of the SUF-like iron–sulfur (Fe-S) cluster biogenesis pathway upon which S. aureus relies exclusively for Fe-S synthesis. The current methods for measuring the activity of this protein have allowed for its recent characterization, but they are hampered by their use of chemical reagents which require long incubation times and may cause undesired side reactions. This problem highlights a need for the development of a rapid quantitative assay for the characterization of SaSufS in the presence of potential inhibitors. Methods: A spectrophotometric assay based on the well-documented absorbance of PLP intermediates at 340 nm was both compared to an established alanine detection assay and used to effectively measure the activity of SaSufS incubated in the absence and presence of the PLP-binding inhibitors, D-cycloserine (DCS) and L-cycloserine (LCS) as proof of concept. Methicillin-resistant S. aureus strain LAC was also grown in the presence of these inhibitors. Results: The Michaelis–Menten parameters kcat and Km of SaSufS were determined using the alanine detection assay and compared to corresponding intermediate-based values obtained spectrophotometrically in the absence and presence of the reducing agent tris(2-carboxyethyl)phosphine (TCEP). These data revealed the formation of both an intermediate that achieves steady-state during continued enzyme turnover and an intermediate that likely accumulates upon the stoppage of the catalytic cycle during the second turnover. The spectrophotometric method was then utilized to determine the half maximal inhibitory concentration (IC50) values for DCS and LCS binding to SaSufS, which are 2170 ± 920 and 62 ± 23 μM, respectively. Both inhibitors of SaSufS were also found to inhibit the growth of S. aureus. Conclusions: Together, this work offers a spectrophotometric method for the analysis of new inhibitors of SufS and lays the groundwork for the future development of novel antibiotics targeting cysteine desulfurases.

Although entirely preventable, rheumatic heart disease (RHD), a disease of poverty and social disadvantage resulting in high morbidity and mortality, remains an ever-present burden in low-income and middle-income countries (LMICs) and rural, remote, marginalised and disenfranchised populations within high-income countries. In late 2021, the National Heart, Lung, and Blood Institute convened a workshop to explore the current state of science, to identify basic science and clinical research priorities to support RHD eradication efforts worldwide. This was done through the inclusion of multidisciplinary global experts, including cardiovascular and non-cardiovascular specialists as well as health policy and health economics experts, many of whom also represented or closely worked with patient-family organisations and local governments. This report summarises findings from one of the four working groups, the Tertiary Prevention Working Group, that was charged with assessing the management of late complications of RHD, including surgical interventions for patients with RHD. Due to the high prevalence of RHD in LMICs, particular emphasis was made on gaining a better understanding of needs in the field from the perspectives of the patient, community, provider, health system and policy-maker. We outline priorities to support the development, and implementation of accessible, affordable and sustainable interventions in low-resource settings to manage RHD and related complications. These priorities and other interventions need to be adapted to and driven by local contexts and integrated into health systems to best meet the needs of local communities.