This is the unspecified version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractThis article sets out the findings from research on the impact of a, UK based, chefs in schools teaching programme on food, provenance, health, nutrition and cookery. Professional chefs link with local schools, where they deliver up to three sessions to one class over a year.The research measured the impact of a standardised intervention package and changes in food preparation and consumption as well as measuring cooking confidence. The target group was 9 -11 year olds in four schools.The main data collection method was a questionnaire delivered two weeks before the intervention and two weeks afterwards. There was a group of four matched control schools.Those taking part in the intervention were enthused and engaged by the sessions and the impact measures indicated an intention to change. There were gains in skills and confidence to prepare and ask for the ingredients to be purchased for use in the home. Following the session with the chef, the average reported cooking confidence score increased from 3.09 to 3.35 (by 0.26 points) in the intervention group -a statistically significant improvement. In the control group this change was not statistically significant. Children's average reported vegetable consumption increased after the session with the chef, with the consumption score increasing from 2.24 to 2.46 points (0.22 points) again, a statistically significant increase with no significant changes in the control group.The research highlights the need to incorporate evaluation into school cooking initiatives as the findings can provide valuable information necessary to fine-tune interventions and to ensure consistency of the healthy eating messages.

Retailers face significant pressure to improve revenue, margins and market share by applying price optimization models. These are mathematical models that calculate how demand varies at different price levels, then combine that data with information on costs and inventory levels to recommend prices that will improve revenue and profits. These models have been around for a while-so what is different now? We have identified three important changes:-Data: availability of internal and external real time data such as traffic to a website, consumers making buy/no buy decisions and competitor pricing strategies;-Analytics: advances in machine learning and ease of access (R, Python) have enabled the development of systems that learn on the fly about consumer behavior and preferences and generate effective estimates of demand-price relationships; and-Automation: increase in computing speed enables real-time optimization of prices of hundreds of competing products sold by the same retailer.

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A challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.

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