Measured and predicted resting energy expenditure in wheelchair rugby athletes

Objective: Report measured resting energy expenditure (REE) in wheelchair rugby athletes and evaluate agreement between REE and the prediction models of Chun, Cunningham, Harris-Benedict, Mifflin, Nightingale and Gorgey, and Owen.

Design: Cohort-based validation study.

Setting. Paralympic team training camp.

Participants: Fourteen internationally competitive athletes who play wheelchair rugby, 13 of whom had cervical spinal cord injuries (SCI).

Outcome Measures: A portable metabolic analyzer was used to measure REE following an overnight fast and dual-energy X-ray absorptiometry (DXA) was used to assess lean body mass for the prediction equations.

Results: REE in the current sample was 1735?±?257?kcal?×?day^?1 ranging from 1324 to 2068?kcal?×?day^{?1 Bhambhani Y. Physiology of wheelchair racing in athletes with spinal cord injury. Sports Med 2002;32(1):23–51.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]}. Bland–Altman analyses revealed negative mean bias but similar limits of agreement between measured REE and scores predicted by Chun, Cunningham, Mifflin, Nightingale and Gorgey, and Owen models in elite athletes who play wheelchair rugby.

Conclusion: Prediction models regressed on persons with and without SCI under-predicted REE of competitive wheelchair rugby athletes. This outcome may be explained by the higher REE/fat-free mass (FFM) ratio of current athletes compared to less active samples. Findings from the current study will help practitioners to determine nutrient intake needs on training days of varied intensity.     

Safety profile of the adjuvanted recombinant zoster vaccine: Pooled analysis of two large randomised phase 3 trials

Background

The ZOE-50 (NCT01165177) and ZOE-70 (NCT01165229) phase 3 clinical trials showed that the adjuvanted recombinant zoster vaccine (RZV) was ≥90% efficacious in preventing herpes zoster in adults. Here we present a comprehensive overview of the safety data from these studies.

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.