Technical-Tactical Performance from Data Providers: A Systematic Review in Regular Football Leagues

In recent years, the number of technology companies providing data to football teams has multiplied. At first, the provided information focused more on physical fitness parameters, but today, ever more data is being generated on technical-tactical performance. The objective of this study was to review the studies on technical-tactical variables based on the information offered by data providers from every country’s regular elite league championship. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards. A total of 31 studies were selected. LaLiga (27.91%) and the Premier League (18.60%) were the most studied competitions. Amisco was the company with the largest number of studies (54.84%). Descriptive studies (58.06%) predominated over comparative (22.58%) and predictive analyses (19.05%). “Style of play”, “contextual variables” (descriptive analysis), and “demarcation” (comparative analysis) were the most used objectives in the 28 studies reviewed.

Altered expression of miR-142, miR-155, miR-499a and of their putative common target MDM2 in systemic lupus erythematosus

Aim: To evaluate genetic and expression variability of three miRNAs potentially involved in systemic lupus erythematosus (SLE) and to identify any miRNA’s target gene. Materials & methods: Gene polymorphisms and expression levels of three miRNAs have been evaluated in a cohort of SLE patients and controls. Results: miR-142 and miR-499a were significantly down-expressed in patients (p = 0.005 and p = 0.02, respectively). A trend for down-expression of miR-155 was also observed (p = 0.07). The lower expression of miR-142 was associated with the rs2632516 polymorphism variant allele (p = 0.002). Predictive analyses identified a target gene common to the three miRNAs, MDM2, whose higher expression was seen in patients compared with controls (p = 0.03). Conclusion: The three miRNAs and MDM2 might be involved in SLE.

Choice of methods can determine which behavioral determinates are identified for targeting in future behavior change interventions: Increasing antibiotic adherence in Pakistan

When developing a behavioral intervention, formative research should be conducted to determine which behavioral barriers and facilitators to target. This is often done using qualitative interviews, but quantitative surveys may also be used. The current study examines the consequences of applying descriptive (rank order and t-tests) versus predictive (regression) quantitative analyses on intervention development, specifically for increasing antibiotic course completion. For demonstrative purposes, 1892 adults in Pakistan completed a cross-sectional survey that measures a comprehensive set of barriers/facilitators to their course completion. The descriptive and predictive analyses disagreed regarding which barriers/facilitators to prioritize. Reasons to prefer predictive analyses are discussed.

Enterprise Digital Twin

Enterprises constantly aim to maximise their objectives while operating in a competitive and dynamic environment. This necessitates an enterprise to be efficient, adaptive, and amenable for transformation. However, understanding a complex enterprise and identifying effective control measure, adaptation choice, or transformation option to realise specific objective is not a trivial task. The digital twin that imitates the real enterprise provides an environment to conduct the necessary interrogative and predictive analyses to evaluate various control measures, adaptation choices, and transformation options in a safe and cost-effective manner without compromising the analysis precision. This chapter reflects on the core concept of the digital twin, evaluates the state-of-the-art modelling and analysis technologies, and presents a pragmatic approach to develop high-fidelity digital twin for large complex enterprises.

Current State of and Future Opportunities for Prediction in Microbiome Research: Report from the Mid-Atlantic Microbiome Meet-up in Baltimore on 9 January 2019

ABSTRACT Accurate predictions across multiple fields of microbiome research have far-reaching benefits to society, but there are few widely accepted quantitative tools to make accurate predictions about microbial communities and their functions. More discussion is needed about the current state of microbiome analysis and the tools required to overcome the hurdles preventing development and implementation of predictive analyses. We summarize the ideas generated by participants of the Mid-Atlantic Microbiome Meet-up in January 2019. While it was clear from the presentations that most fields have advanced beyond simple associative and descriptive analyses, most fields lack essential elements needed for the development and application of accurate microbiome predictions. Participants stressed the need for standardization, reproducibility, and accessibility of quantitative tools as key to advancing predictions in microbiome analysis. We highlight hurdles that participants identified and propose directions for future efforts that will advance the use of prediction in microbiome research.