A user-friendly decision support tool to assist one-health risk assessors.

One-Health risk assessments are integral to developing efficient responses to disease threats, including global pandemics. However, short timeframes, inadequate disease-specific information and an insufficient skill-base make it hard for inexperienced assessors to distinguish between a large portfolio of approaches. The wrong choice can detract from the disease response. Here, we present an interactive decision support tool to help with this choice. A workshop with participants from diverse professional backgrounds provided six themes that should be considered when deciding on the best approach. Questions based on these themes were then developed to populate a decision tree which guides users to their most appropriate approach. One-Health risk assessment tools and literature were used as examples of the different approaches. The tool provides links to these examples and short descriptions of the approaches. Answers are easily changed, facilitating exploration though different approaches. The simple data structure of the tool means it is easy to update with more resources and approaches. It provides a valuable source of guidance and information for less experienced risk assessors.

Estimating the amount of Chronic Wasting Disease infectivity passing through abattoirs and field slaughter.

Chronic Wasting Disease (CWD) is a highly infectious, naturally occurring, transmissible spongiform encephalopathy (TSE, or prion disease) affecting many cervid species. CWD has been widely circulating in North America since it was first reported in 1967. In 2016, the first European case of prion disease in deer was reported and confirmed in Norway. There have since been several confirmed several cases in reindeer and moose and in one red deer in Norway, and recently in a moose in Finland. There is concern over the susceptibility of certain species, especially domestic livestock, to CWD. Recently, a study was presented showing transmission to cynomolgus macaques. Although preliminary, these results raise concerns that CWD may be transmissible to humans. This quantitative risk assessment estimates, by stochastic simulation, the titre of infectivity (herein referred to as "infectivity"), that would pass into the human food chain and environment (in the UK) as a result of a single CWD positive red deer passing through an abattoir, or being field dressed. The model estimated that around 11,000 mouse i.c. log ID50 units would enter the human food chain through the farmed route or wild route. The model estimated that there are around 83,000 mouse i.c. log ID50 units in a deer carcase, compared to around 22,000 in a sheep carcase infected with scrapie, mainly due to the size difference between a red deer and a sheep. For farmed deer, the model estimated that 87% of total carcase infectivity would become animal by-product category 3 material, with only 13% going to the food chain and a small amount to wastewater via the abattoir floor. For wild deer, the model estimated that on average, 85% of total carcase infectivity would be buried in the environment, with 13% going to the food chain and 2% to category 3 material which may be used as a protein source in other industries. Results indicate that if CWD was found in the UK there would be a risk of prions entering the human food chain and the environment. However, it is unclear if humans would be susceptible to CWD following consumption of contaminated meat, or what the environmental impact would be. This risk assessment highlights the need for further research in order to quantify the infectivity in all tissue types, in particular blood, gastrointestinal (GI) tract and skeletal muscle.

The importance of the derivative in sex-hormone cycles: a reason why behavioural measures in sex-hormone studies are so mercurial.

To study the dynamic changes in cognition across the human menstrual cycle, twenty, healthy, naturally-cycling women undertook a lateralized spatial figural comparison task on twelve occasions at approximately 3-4 day intervals. Each session was conducted in laboratory conditions with response times, accuracy rates, eye movements, salivary estrogen and progesterone concentrations and Profile of Mood states questionnaire data collected on each occasion. The first two sessions of twelve for the response variables were discarded to avoid early effects of learning thereby providing 10 sessions spread across each participant's complete menstrual cycle. Salivary progesterone data for each participant was utilized to normalize each participant's data to a standard 28 day cycle. Data was analysed categorically by comparing peak progesterone (luteal phase) to low progesterone (follicular phase) to emulate two-session repeated measures typical studies. Neither a significant difference in reaction times or accuracy rates was found. Moreover no significant effect of lateral presentation was observed upon reaction times or accuracy rates although inter and intra individual variance was sizeable. We demonstrate that hormone concentrations alone cannot be used to predict the response times or accuracy rates. In contrast, we constructed a standard linear model using salivary estrogen, salivary progesterone and their respective derivative values and found these inputs to be very accurate for predicting variance observed in the reaction times for all stimuli and accuracy rates for right visual field stimuli but not left visual field stimuli. The identification of sex-hormone derivatives as predictors of cognitive behaviours is of importance. The finding suggests that there is a fundamental difference between the up-surge and decline of hormonal concentrations where previous studies typically assume all points near the peak of a hormonal surge are the same. How contradictory findings in sex-hormone research may have come about are discussed.

A method for predicting maximal strength in collegiate women athletes.

The purpose of this study was to develop a regression equation capable of accurately predicting a 1 repetition maximum bench press in collegiate women athletes. The findings of this study could benefit future women athletes by providing coaches and trainers with an easy method of determining maximum upper body strength in women athletes. Sixty-five University of Georgia NCAA Division 1 women athletes from 9 different sports were measured prior to the start of their season utilizing 2 repetition tests to fatigue (25 kg: REPS55; 31.8 kg: REPS70) and a 1 repetition maximum (1RM) bench press test in random order. Other independent variables that were used with a submaximal weight to predict 1RM were total body weight, lean body mass (LBM), height, and percent body fat. The variables of REPS70 and LBM were the best predictors of 1RM utilizing Pearson product correlations (r = 0.909, p = 0.000; r = 0.445, p = 0.000) and multiple regression results (R(2) = 0.834, p = 0.000) for this population. The results from this study indicate muscular endurance repetitions using an absolute weight of 31.8 kg in conjunction with LBM can be used to accurately predict 1RM bench press strength in collegiate women athletes.