Definitions, Foundations and Associations of Physical Literacy: A Systematic Review

Background: The concept of physical literacy has stimulated increased research attention in recent years—being deployed in physical education, sport participation, and the promotion of physical activity. Independent research groups currently operationalize the construct differently. Objective The purpose of this systematic review was to conduct a systematic review of the physical literacy construct,as reflected in contemporary research literature. Methods: Five databases were searched using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for systematic reviews. Inclusion criteria were English language, peer reviewed, published by March 2016, and seeking to conceptualize physical literacy. Articles that met these criteria were analysed in relation to three core areas: properties/attributes, philosophicalfoundations and theoretical associations with other constructs. A total of 50 published articles met the inclusion criteria and were analysed qualitatively using inductive thematic analysis.Results: The thematic analysis addressed the three core areas. Under definitions, core attributes that define physical literacy were identified, as well as areas of conflict between different approaches currently being adopted. One relatively clear philosophical approach was prominent in approximately half of the papers, based on a monist/holistic ontology and phenomenological epistemology. Finally, theanalysis identified a number of theoretical associations, including health, physical activity and academic performance.Conclusions: Current literature contains different representations of the physical literacy construct. The costs and benefits of adopting an exclusive approach versus pluralism are considered. Recommendations for both researchers and practitioners focus on identifying and clearly articulating the definitions, philosophical assumptions and expected outcomes prior to evaluating the effectiveness of this emerging concept

MicroRNA Expression Characterizes Oligometastasis(es)

Cancer staging and treatment presumes a division into localized or metastatic disease. We proposed an intermediate state defined by ≤ 5 cumulative metastasis(es), termed oligometastases. In contrast to widespread polymetastases, oligometastatic patients may benefit from metastasis-directed local treatments. However, many patients who initially present with oligometastases progress to polymetastases. Predictors of progression could improve patient selection for metastasis-directed therapy.Here, we identified patterns of microRNA expression of tumor samples from oligometastatic patients treated with high-dose radiotherapy.Patients who failed to develop polymetastases are characterized by unique prioritized features of a microRNA classifier that includes the microRNA-200 family. We created an oligometastatic-polymetastatic xenograft model in which the patient-derived microRNAs discriminated between the two metastatic outcomes. MicroRNA-200c enhancement in an oligometastatic cell line resulted in polymetastatic progression.These results demonstrate a biological basis for oligometastases and a potential for using microRNA expression to identify patients most likely to remain oligometastatic after metastasis-directed treatment

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research