Hazards of Healthy Living: Bottled Water and Salad Vegetables as Risk Factors for Campylobacter Infection

Campylobacter is the most common cause of bacterial gastroenteritis worldwide, yet the etiology of this infection remains only partly explained. In a retrospective cohort study, we compared 213 sporadic campylobacter case-patients with 1,144 patients with negative fecal samples. Information was obtained on food history, animal contact, foreign travel, leisure activities, medical conditions, and medication use. Eating chicken, eating food from a fried chicken outlet, eating salad vegetables, drinking bottled water, and direct contact with cows or calves were all independently associated with infection. The population-attributable fractions for these risk factors explained nearly 70% of sporadic campylobacter infections. Eating chicken is a well-established risk factor, but consuming salad and bottled water are not. The association with salad may be explained by cross-contamination of food within the home, but the possibility that natural mineral water is a risk factor for campylobacter infection could have wide public health implications

All-codon scanning identifies p53 cancer rescue mutations

In vitro scanning mutagenesis strategies are valuable tools to identify critical residues in proteins and to generate proteins with modified properties. We describe the fast and simple All-Codon Scanning (ACS) strategy that creates a defined gene library wherein each individual codon within a specific target region is changed into all possible codons with only a single codon change per mutagenesis product. ACS is based on a multiplexed overlapping mutagenesis primer design that saturates only the targeted gene region with single codon changes. We have used ACS to produce single amino-acid changes in small and large regions of the human tumor suppressor protein p53 to identify single amino-acid substitutions that can restore activity to inactive p53 found in human cancers. Single-tube reactions were used to saturate defined 30-nt regions with all possible codon changes. The same technique was used in 20 parallel reactions to scan the 600-bp fragment encoding the entire p53 core domain. Identification of several novel p53 cancer rescue mutations demonstrated the utility of the ACS approach. ACS is a fast, simple and versatile method, which is useful for protein structure–function analyses and protein design or evolution problems

Where does the time go? Patterns of physical activity in adolescent youth.

OBJECTIVES: To explore daily patterns of physical activity in early adolescent youth, and identify whether patterns differed across varying activity levels. DESIGN: Cross-sectional observational study. METHODS: Adolescent youth (n=715, 11.8-14.4 years) were asked to wear an Actigraph accelerometer for a 9-day period. Average daily and hourly minutes spent in moderate-vigorous physical activity (MVPA) were calculated for each participant. Participants were grouped into sex-specific quartiles (Q) based on average daily MVPA accumulation (Q4 most active, Q1 least active). Principal components analysis was used to identify, from hourly MVPA data, distinct time blocks for Weekday and Weekend days. Mixed between-within ANOVA's were conducted separately by gender to assess the impact of Quartile grouping on minutes of MVPA across the distinct time blocks. RESULTS: Males accumulated significantly more minutes of MVPA daily than females (55.3±21.6min, versus 47.4±18.1min). Principal Components Analysis revealed three distinct time components for MVPA during weekdays, and weekend days. The total difference between Q4 and Q1 was greatest 'Weekend Afternoons' for Males (22min), and 'Weekend Midday' for females (12.8min); with Q4 accumulating significantly more MVPA in these time periods than the other three Quartiles (p<0.05). CONCLUSIONS: This study points to the weekend midday and afternoon periods as particular time blocks to target for intervening with inactive youth. Future research should examine the reasons why some youth choose to be active during these particular periods while others do not, with a view to developing appropriate strategies for intervention

Predicting Positive p53 Cancer Rescue Regions Using Most Informative Positive (MIP) Active Learning

Many protein engineering problems involve finding mutations that produce proteins with a particular function. Computational active learning is an attractive approach to discover desired biological activities. Traditional active learning techniques have been optimized to iteratively improve classifier accuracy, not to quickly discover biologically significant results. We report here a novel active learning technique, Most Informative Positive (MIP), which is tailored to biological problems because it seeks novel and informative positive results. MIP active learning differs from traditional active learning methods in two ways: (1) it preferentially seeks Positive (functionally active) examples; and (2) it may be effectively extended to select gene regions suitable for high throughput combinatorial mutagenesis. We applied MIP to discover mutations in the tumor suppressor protein p53 that reactivate mutated p53 found in human cancers. This is an important biomedical goal because p53 mutants have been implicated in half of all human cancers, and restoring active p53 in tumors leads to tumor regression. MIP found Positive (cancer rescue) p53 mutants in silico using 33% fewer experiments than traditional non-MIP active learning, with only a minor decrease in classifier accuracy. Applying MIP to in vivo experimentation yielded immediate Positive results. Ten different p53 mutations found in human cancers were paired in silico with all possible single amino acid rescue mutations, from which MIP was used to select a Positive Region predicted to be enriched for p53 cancer rescue mutants. In vivo assays showed that the predicted Positive Region: (1) had significantly more (p<0.01) new strong cancer rescue mutants than control regions (Negative, and non-MIP active learning); (2) had slightly more new strong cancer rescue mutants than an Expert region selected for purely biological considerations; and (3) rescued for the first time the previously unrescuable p53 cancer mutant P152L

Reality and Rationality

This volume of articles (most published, some new) is a follow-up to the late Wesley C. Salmon's widely read collection Causality And Explanation (OUP 1998). It contains both published and unpublished articles, and focuses on two related areas of inquiry: First, is science a rational enterprise? Secondly, does science yield objective information about our world, even the aspects that we cannot observe directly? Salmon's own take is that objective knowledge of the world is possible, and his work in these articles centers around proving that this can be so. Salmon's influential standing in the field ensures that this volume will be of interest to both undergraduates and professional philosophers, primarily in the philosophy of science