Chemical assessment state of the science: Evaluation of 32 decision-support tools used to screen and prioritize chemicals.

The last decade has seen an increased focus on evaluating the safety and sustainability of chemicals in consumer and industrial products. In order to effectively and accurately evaluate safety and sustainability, tools are needed to characterize hazard, exposure, and risk pertaining to products and processes. Because many of these tools will be used to identify problematic chemistries, and because many have potential applications in various steps of an alternatives analysis, the limitations and capabilities of available tools should be understood by users so that, ultimately, potential chemical risk is accurately reflected. In our study, we examined 32 chemical characterization tools from government, industry, academia, and non-governmental organizations (NGOs). The tools we studied were diverse, and varied widely in their scope and assessment. As such, they were separated into five categories for comparison: 1) Screening and Prioritization; 2) Database Utilization; 3) Hazard Assessment; 4) Exposure and Risk Assessment; and 5) Certification and Labeling. Each tool was scored based on our weighted set of criteria, and then compared to other tools in the same category. Ten tools received a high score in one or more categories; 24 tools received a medium score in one or more categories, and five tools received a low score in one or more categories. Although some tools were placed into more than one category, no tool encompassed all five of the assessment categories. Though many of the tools evaluated may be useful for providing guidance for hazards - and, in some cases, exposure - few tools characterize risk. To our knowledge, this study is the first to critically evaluate a large set of chemical assessment tools and provide an understanding of their strengths and limitations.

Metabolic and thermoregulatory responses to a simulated American football practice in the heat.

Energy cost is a major factor influencing the tolerable thermal load, particularly during exercise in the heat. However, no data exist on the metabolic cost of football practice, although a value of 35% of maximal aerobic capacity (VO(2)max) has been estimated. The energy cost and thermoregulatory response of offensive linemen (OL) was measured wearing different American football ensembles during a simulated half of football practice in the heat. Five collegiate offensive linemen (133 kg, 20% fat, 42 ml x kg(-1) x min(-1) maximal oxygen uptake) completed each of four 60-minute test sessions in an environmental chamber (28 degrees C, 55% relative humidity [RH]) wearing shorts (S), helmet (H), helmet and shoulder pads (HS), and full gear (FUL). Core temperature in the digestive tract (TGI) was obtained using an ingestible sensor. During simulated football drills (e.g., repetitions of drive blocking), exercise intensity ranged from 30 to 81% VO(2)max but averaged 55%VO(2)max (6.7 METS) overall. Blood lactate remained >5 mmol x L(-1), and heart rate (HR) averaged 79%HRmax. Equipment had a significant effect on %VO(2)max but only during recovery between drills with HS (61.4 +/- 3.7%) compared with H (53.3 +/- 6.9%) and S (40.1 +/- 8.5%). The TGI was higher (p < 0.05) with HS compared with H at several time-points after 30 minutes. Football practice for OL elicits a significantly higher overall metabolic cost (>6 METS, >50%VO(2)max) than assumed in previous studies. The addition of shoulder pads increases core temperature and energy cost, especially during recovery between active drills in unacclimatized linemen.

Recovery from run training: efficacy of a carbohydrate-protein beverage?

Post-exercise nutrition is critical to facilitate recovery from training. To determine if added protein (P) or increased carbohydrate (CHO) differentially improves recovery, eight runners ingested: 6% CHO (CHO6), 8% CHO + 2% protein (CHO-P), and isocaloric 10% CHO (CHO10) following a 21-km run plus treadmill run to fatigue (RTF) at 90% VO2max. RTF was repeated after 2 h recovery. After 24 h, a 5 km time trial was performed. Insulin and blood glucose were higher (P < 0.05) following CHO10 compared to CHO-P and CHO6, but did not affect improvement from the first to second RTF (29.6% +/- 6, 40.5% +/- 8.8, 40.5% +/- 14.5) or 5 km time (1100 +/- 36.3, 1110 +/- 37.3, 1118 +/- 36.5 s). CK was not different, but perceived soreness with CHO-P (2.1 +/- 0.5) was lower than CHO10 (5.2 +/- 0.7). Additional calories from CHO or P above that provided in sports drinks does not improve subsequent performance after recovery; but less soreness suggests benefits with CHO-P.