EVA: Evaluation of Metabolic Feature Fidelity Using a Deep Learning Model Trained With Over 25000 Extracted Ion Chromatograms.

Extracting metabolic features from liquid chromatography-mass spectrometry (LC-MS) data relies on the recognition of extracted ion chromatogram (EIC) peak shapes using peak picking algorithms. Unfortunately, all peak picking algorithms present a significant drawback of generating a problematic number of false positives. In this work, we take advantage of deep learning technology to develop a convolutional neural network (CNN)-based program that can automatically recognize metabolic features with poor EIC shapes, which are of low feature fidelity and more likely to be false. Our CNN model was trained using 25095 EIC plots collected from 22 LC-MS-based metabolomics projects of various sample types, LC and MS conditions. Notably, we manually inspected all the EIC plots to assign good or poor EIC quality for accurate model training. The trained CNN model is embedded into a C#-based program, named EVA (short for evaluation). The EVA Windows Application is a versatile platform that can process metabolic features generated by LC-MS systems of various vendors and processed using various data processing software. Our comprehensive evaluation of EVA indicates that it achieves over 90% classification accuracy. EVA can be readily used in LC-MS-based metabolomics projects and is freely available on the Microsoft Store by searching "EVA Metabolomics".

Standards-based physical education in schools: The role of state laws.

Purpose: Examine the association of state physical education (PE) laws (https://class.cancer.gov) with school policies addressing motor skill development, physical activity (PA) participation, and health-enhancing physical fitness (https://www.cdc.gov/healthyyouth/data/shpps/data.htm). Methods: National school-level data on PE standards were obtained from the 2014 School Health Policies and Practices Study (SHPPS) of US schools for analytical samples of 408-410 schools in 43 states. These data were linked to Classification of Laws Associated with School Students (CLASS) data, which reflect the strength of state-PE curriculum laws and the associated state PE curriculum standards. Logistic regressions and generalized linear models with a complementary log-log link examined associations between state law and school-level standards. Results: Compared to having no state law, weak law (OR: 5.07, 95% CI: 1.02-25.27) or strong law (OR: 2.96, 95% CI: 1.04-8.37) was associated with higher odds of school PE standards addressing motor skill development, while only strong state law was associated with higher prevalence of addressing achievement and maintenance of physical fitness (coefficient: 0.63, 95% CI: 0.12, 1.14). State laws were not associated with addressing PA participation. Conclusions: Schools were more likely to address motor skills and physical fitness development when states had strong PE laws.

Human neuraminidases have reduced activity towards modified sialic acids on glycoproteins.

Multiple levels of diversity in sialic acid presentation can influence the substrate activity of sialosides for glycoside hydrolases. Few reports have investigated the specificity of human neuraminidase (hNEU) activity towards modified sialic acid residues that can occur on glycoproteins. Previously, we evaluated hNEU activity towards 9-O-acetylated sialic acid in glycolipid substrates and found that hNEU generally discriminated against 9-O-acetylated sialic acid over Neu5Ac. Here, we have investigated the substrate specificity of hNEU enzymes for a glycoprotein substrate (bovine submaxillary mucin) containing 9-O-acetylated and Neu5Gc residues. Using this model substrate, we observe a general trend for hNEU tolerance of Neu5Ac > Neu5Gc ≫ Neu5,9Ac2, consistent with our previous results with glycolipid substrates. These results expand our understanding of hNEU enzyme specificity and suggest that naturally occurring modifications of sialic acids can play a role in regulating hNEU activity.

Graduates from dual qualification courses, registered nurse and health visitor: a career history study.

BACKGROUND: Educationalists and managers internationally are challenged to find ways of preparing, recruiting early in their careers, and retaining nurses into public health roles in primary care. Public health nursing qualifications are post-initial nurse registration in the United Kingdom as in some other countries. In the mid twentieth century there were a number of innovative programmes of dual qualification: registered nurse and health visitor (the United Kingdom term for public health nurse). OBJECTIVE: To investigate the career histories of graduates from courses integrating both nursing and health visitor qualifications. DESIGN: An observational, survey study. SETTING: The United Kingdom. PARTICIPANTS: A purposive sample of graduates from integrated registered nurse and health visitor programmes, 1959-1995, from one University. METHODS: Self completed, anonymous, survey sent to graduates, with contact details known to the University and through snowballing techniques, in 2011. FINDINGS: Forty five women (56%), graduates in all four decades, returned the survey. A significant majority (82%) had taken up health visitor posts on completing the course. Over their careers, 42% of all jobs held were as health visitors. Only four never worked in a post that required a health visiting qualification. Most had undertaken paid work throughout their careers that focused on aspects of public health, often linked to child, maternal and/or family wellbeing. Many held teaching/lecturing and management posts at some point in their career. Those holding management posts were more likely to report leaving them as a result of organisational re-structuring or redundancy than those in non-management posts. CONCLUSIONS: Courses that prepare students to be both nurses and health visitors result in a majority of graduates who take up posts as health visitors on qualification and subsequently. Nurse education planners may find this evidence of value in determining ways of providing a future workforce for public health nursing.