Effectiveness and reporting of nutrition interventions in cardiac rehabilitation programmes: a systematic review.

AIMS: Dietary modification is essential for the secondary prevention of cardiovascular disease. However, there are limited published evidence syntheses to guide practice in the cardiac rehabilitation (CR) setting. This systematic review's objective was to assess effectiveness and reporting of nutrition interventions to optimize dietary intake in adults attending CR. METHODS AND RESULTS: Randomized controlled trials (RCTs) of nutrition interventions within CR were eligible for inclusion and had to have measured change in dietary intake. MEDLINE, Embase, Emcare, PsycINFO, CINAHL, Scopus, and The Cochrane Library were searched from 2000 to June 2020, limited to publications in English. Evidence from included RCTs was synthesized descriptively. The risk of bias was assessed using the Cochrane Risk of Bias 2 tool. This review is registered on PROSPERO; CRD42020188723. Of 13 048 unique articles identified, 11 were eligible. Randomized controlled trials were conducted in 10 different countries, included 1542 participants, and evaluated 29 distinct dietary intake outcomes. Five studies reported statistically significant changes in diet across 13 outcomes. Most nutrition interventions were not reported in a manner that allowed replication in clinical practice or future research. CONCLUSION: There is a gap in research testing high-quality nutrition interventions in CR settings. Findings should be interpreted in the light of limitations, given the overall body of evidence was heterogenous across outcomes and study quality; 6 of 11 studies were conducted more than 10 years old. Future research should investigate strategies to optimize and maintain nutrition improvements for patients attending CR. REGISTRATION: PROSPERO; CRD42020188723.

The Prospective Association Between Physical Activity, Insomnia Symptoms, and Productivity in an Australian Population-Based Cohort.

OBJECTIVES: To investigate the joint, prospective associations of physical inactivity and insomnia symptoms and productivity using the 2013 and 2014 household income and labor dynamics in Australia Survey panel data. METHODS: The association between (i) presenteeism (yes/no, n = 5864) and (ii) absenteeism (sick leave days, n = 4324) and the mutually exclusive groups "active without insomnia," "active with insomnia," "inactive without insomnia," and "inactive with insomnia" was assessed. RESULTS: Participants "active with insomnia" or "inactive with insomnia" had greater odds of presenteeism than those "active without insomnia" (odds ratio [OR] = 1.41, 95% confidence interval [CI]: 1.07 to 1.85 and OR = 1.44, 95% CI: 1.14 to 1.83, respectively). Participants "inactive with insomnia" had a greater incidence of absenteeism than participants "active without insomnia" (incidence rate ratio [IRR] = 1.28, 95% CI: 1.07 to 1.54). CONCLUSIONS: Findings suggest improving physical activity levels and insomnia symptoms concurrently may improve productivity by reducing presenteeism and sick leave.

Development of the Home Cooking EnviRonment and Equipment Inventory Observation form (Home-CookERITM): An Assessment of Content Validity, Face Validity, and Inter-Rater Agreement.

INTRODUCTION: Quantifying Home Cooking EnviRonments has applications in nutrition epidemiology, health promotion, and nutrition interventions. This study aimed to develop a tool to quantify household cooking environments and establish its content validity, face validity, and inter-rater agreement. METHODS: The Home Cooking EnviRonment and equipment Inventory observation form (Home-CookERI™) was developed as a 24-question (91-item) online survey. Items included domestic spaces and resources for storage, disposal, preparation, and cooking of food or non-alcoholic beverages. Home-CookERITM was piloted to assess content validity, face validity, and usability with six Australian experts (i.e., dietitians, nutrition researchers, chefs, a food technology teacher, and a kitchen designer) and 13 laypersons. Pilot participants provided feedback in a 10 min telephone interview. Home-CookERI™ was modified to an 89-item survey in line with the pilot findings. Inter-rater agreement was examined between two trained raters in 33 unique Australian households. Raters were required to observe each item before recording a response. Home occupants were instructed to only assist with locating items if asked. Raters were blinded to each other's responses. Inter-rater agreement was calculated by Cohen's Kappa coefficient (κ) for each item. To optimize κ, similar items were grouped together reducing the number of items to 81. RESULTS: Home-CookERITM had excellent content and face validity with responding participants; all 24 questions were both clear and relevant (X2 (1, n = 19; 19.0, p = 0.392)). Inter-rater agreement for the modified 81-item Home-CookERI™ was almost-perfect to perfect for 46% of kitchen items (n = 37 items, κ = 0.81-1), moderate to substantial for 28% (n = 23, κ = 0.51-0.8), slight to fair for 15% (n = 12, κ = 0.01-0.5), and chance or worse for 11% of items (n = 9, κ ≤ 0.0). Home-CookERITM was further optimized by reduction to a 77-item version, which is now available to researchers. CONCLUSION: Home-CookERI™ is a comprehensive tool for quantifying Australian household cooking environments. It has excellent face and content validity and moderate to perfect inter-rater agreement for almost three-quarters of included kitchen items. To expand Home-CookERI™ applications, a home occupant self-completion version is planned for validation.

CONNJUR R: an annotation strategy for fostering reproducibility in bio-NMR-protein spectral assignment.

Reproducibility is a cornerstone of the scientific method, essential for validation of results by independent laboratories and the sine qua non of scientific progress. A key step toward reproducibility of biomolecular NMR studies was the establishment of public data repositories (PDB and BMRB). Nevertheless, bio-NMR studies routinely fall short of the requirement for reproducibility that all the data needed to reproduce the results are published. A key limitation is that considerable metadata goes unpublished, notably manual interventions that are typically applied during the assignment of multidimensional NMR spectra. A general solution to this problem has been elusive, in part because of the wide range of approaches and software packages employed in the analysis of protein NMR spectra. Here we describe an approach for capturing missing metadata during the assignment of protein NMR spectra that can be generalized to arbitrary workflows, different software packages, other biomolecules, or other stages of data analysis in bio-NMR. We also present extensions to the NMR-STAR data dictionary that enable machine archival and retrieval of the "missing" metadata.

CONNJUR Workflow Builder: a software integration environment for spectral reconstruction.

CONNJUR Workflow Builder (WB) is an open-source software integration environment that leverages existing spectral reconstruction tools to create a synergistic, coherent platform for converting biomolecular NMR data from the time domain to the frequency domain. WB provides data integration of primary data and metadata using a relational database, and includes a library of pre-built workflows for processing time domain data. WB simplifies maximum entropy reconstruction, facilitating the processing of non-uniformly sampled time domain data. As will be shown in the paper, the unique features of WB provide it with novel abilities to enhance the quality, accuracy, and fidelity of the spectral reconstruction process. WB also provides features which promote collaboration, education, parameterization, and non-uniform data sets along with processing integrated with the Rowland NMR Toolkit (RNMRTK) and NMRPipe software packages. WB is available free of charge in perpetuity, dual-licensed under the MIT and GPL open source licenses.

Parser Combinators: a Practical Application for Generating Parsers for NMR Data.

Nuclear Magnetic Resonance (NMR) spectroscopy is a technique for acquiring protein data at atomic resolution and determining the three-dimensional structure of large protein molecules. A typical structure determination process results in the deposition of a large data sets to the BMRB (Bio-Magnetic Resonance Data Bank). This data is stored and shared in a file format called NMR-Star. This format is syntactically and semantically complex making it challenging to parse. Nevertheless, parsing these files is crucial to applying the vast amounts of biological information stored in NMR-Star files, allowing researchers to harness the results of previous studies to direct and validate future work. One powerful approach for parsing files is to apply a Backus-Naur Form (BNF) grammar, which is a high-level model of a file format. Translation of the grammatical model to an executable parser may be automatically accomplished. This paper will show how we applied a model BNF grammar of the NMR-Star format to create a free, open-source parser, using a method that originated in the functional programming world known as "parser combinators". This paper demonstrates the effectiveness of a principled approach to file specification and parsing. This paper also builds upon our previous work [1], in that 1) it applies concepts from Functional Programming (which is relevant even though the implementation language, Java, is more mainstream than Functional Programming), and 2) all work and accomplishments from this project will be made available under standard open source licenses to provide the community with the opportunity to learn from our techniques and methods.

An Open-Source Sandbox for Increasing the Accessibility of Functional Programming to the Bioinformatics and Scientific Communities.

Scientists are continually faced with the need to express complex mathematical notions in code. The renaissance of functional languages such as LISP and Haskell is often credited to their ability to implement complex data operations and mathematical constructs in an expressive and natural idiom. The slow adoption of functional computing in the scientific community does not, however, reflect the congeniality of these fields. Unfortunately, the learning curve for adoption of functional programming techniques is steeper than that for more traditional languages in the scientific community, such as Python and Java, and this is partially due to the relative sparseness of available learning resources. To fill this gap, we demonstrate and provide applied, scientifically substantial examples of functional programming, We present a multi-language source-code repository for software integration and algorithm development, which generally focuses on the fields of machine learning, data processing, bioinformatics. We encourage scientists who are interested in learning the basics of functional programming to adopt, reuse, and learn from these examples. The source code is available at: https://github.com/CONNJUR/CONNJUR-Sandbox (see also http://www.connjur.org).

A Pipeline Software Architecture for NMR Spectrum Data Translation.

The problem of formatting data so that it conforms to the required input for scientific data processing tools pervades scientific computing. The CONNecticut Joint University Research Group (CONNJUR) has developed a data translation tool based on a pipeline architecture that partially solves this problem. The CONNJUR Spectrum Translator supports data format translation for experiments that use Nuclear Magnetic Resonance to determine the structure of large protein molecules.

Random phase detection in multidimensional NMR.

Despite advances in resolution accompanying the development of high-field superconducting magnets, biomolecular applications of NMR require multiple dimensions in order to resolve individual resonances, and the achievable resolution is typically limited by practical constraints on measuring time. In addition to the need for measuring long evolution times to obtain high resolution, the need to distinguish the sign of the frequency constrains the ability to shorten measuring times. Sign discrimination is typically accomplished by sampling the signal with two different receiver phases or by selecting a reference frequency outside the range of frequencies spanned by the signal and then sampling at a higher rate. In the parametrically sampled (indirect) time dimensions of multidimensional NMR experiments, either method imposes an additional factor of 2 sampling burden for each dimension. We demonstrate that by using a single detector phase at each time sample point, but randomly altering the phase for different points, the sign ambiguity that attends fixed single-phase detection is resolved. Random phase detection enables a reduction in experiment time by a factor of 2 for each indirect dimension, amounting to a factor of 8 for a four-dimensional experiment, albeit at the cost of introducing sampling artifacts. Alternatively, for fixed measuring time, random phase detection can be used to double resolution in each indirect dimension. Random phase detection is complementary to nonuniform sampling methods, and their combination offers the potential for additional benefits. In addition to applications in biomolecular NMR, random phase detection could be useful in magnetic resonance imaging and other signal processing contexts.

CONNJUR spectrum translator: an open source application for reformatting NMR spectral data.

NMR spectroscopists are hindered by the lack of standardization for spectral data among the file formats for various NMR data processing tools. This lack of standardization is cumbersome as researchers must perform their own file conversion in order to switch between processing tools and also restricts the combination of tools employed if no conversion option is available. The CONNJUR Spectrum Translator introduces a new, extensible architecture for spectrum translation and introduces two key algorithmic improvements. This first is translation of NMR spectral data (time and frequency domain) to a single in-memory data model to allow addition of new file formats with two converter modules, a reader and a writer, instead of writing a separate converter to each existing format. Secondly, the use of layout descriptors allows a single fid data translation engine to be used for all formats. For the end user, sophisticated metadata readers allow conversion of the majority of files with minimum user configuration. The open source code is freely available at http://connjur.sourceforge.net for inspection and extension.