A New Phytochemical Screening Programme used for Crops grown with Organic and Conventional Methods

A broad screening programme, covering the most general phytochemical groups of compounds, was developed on the basis of Thin Layer Chromatography (TLC). A total of 46 TLC systems, comprising 26 derivatization reagents, 3 stationary phases, and 4 mobile phases, were included. The TLC systems were classified according to the groups of phytochemical compounds detected: Alcohols and phenolic compounds; Carbohydrates; N-containing compounds; Organic acids and lipids; P-containing compounds; S-containing compounds, and Terpenoids. Furthermore, one group of TLC systems detected compounds from several of the mentioned groups. The screening programme was applied in the screening of potatoes (S. tuberosum L.), peas (P. sativum L.), kale (B. oleracea L.), carrots (D. carota L.), and apples (M. domestica Borkh.), cultivated with combinations of organic and conventional methods for plant protection and nutrient supply, for phytochemical differences (biomarkers). Distinctive phytochemical differences were found between the differently cultivated samples of these crops. In peas and carrots only one biomarker was found. In peas the biomarker was related to the soil conditions, while the biomarker in carrots was related to the use of pesticides. In potato, two biomarkers related to the use of pesticides were found. Three biomarkers were found in kale. Two of these could be related to the use of pesticide, while the last was related to either fertiliser or soil conditions. Several biomarkers were found apples, but a relation to the cultivation methods was not clear. Three of the biomarkers in apples could be related to either the use of pesticides or fertiliser, while no conclusions could be drawn from the other biomarkers found. The results of the screening programme form the basis for a potential development of a kit to detect whether crops are organically- or conventionally cultivated. Furthermore, the results from this part and other parts of the project "Organic food and health – a multigenerational animal experiment" provide basis for the selection of which secondary compounds to quantify by specific chemical analysis, isolate, and/or structure elucidation

Plant Biomarker Pattern, Apples grown with various availability of organic nitrogen and with or witout the use of pesticides

In the recent years there has been an increasing focus on the quality and health value of organic plant products compared with conventional products. The use of pesticides and concentrated fertilisers in conventional agriculture implies a risk of effects on plant composition, which may affect health of the consumer (Brandt & Mølgaard, 2001). To determine if organically grown plant food could provide more or less benefits to health than conventional food, a first step is to investigate the differences in the composition and relative concentration of natural compounds in the plant products. In this project apples were grown with two levels of nitrogen availability and with or without the use of pesticides. The apples were screened for changes in the phytochemical composition and concentration. The work is affiliated to the project "Organic food and health" supported by the Danish Research Centre for Organic Farming (DARCOF). Biomarkers and biomarker patterns were presented in plants cultivated with low and high N and with pesticides. One biomarker was related to: • the type of N with and without pesticides • pesticides at high N and type of N without pesticides • pesticides at low and high N One biomarker pattern was related to: • the type of N • the type of N without pesticides • pesticides at low N and type of N without pesticides • pesticides at high N and type of N with pesticide

Gamification of the National Institutes of Health Stroke Scale (NIHSS) for simulation training—a feasibility study

Background Training prehospital personnel in identifying patients with acute stroke is key to providing rapid treatment. This study aimed to investigate whether game-based digital simulation training is a feasible alternative to standard in-person simulation training. Methods Second-year paramedic bachelor students at Oslo Metropolitan University in Norway were invited to participate in a study to compare game-based digital simulation (intervention) to standard in-person training (control). For 2 months, students were encouraged to practice the NIHSS, and both groups logged their simulations. Then, they performed a clinical proficiency test, and their results were assessed using a Bland-Altman plot with corresponding 95% limits of agreement (LoA). Results Fifty students participated in the study. Individuals in the game group (n = 23) spent an average (SD) of 42:36 min (36) on gaming and performed 14.4 (13) simulations on average, whereas the control group (n = 27) spent 9:28 min (8) simulating and performed 2.5 (1) simulations. Comparing time variables collected during the intervention period, the mean time for each simulated assessment was significantly shorter in the game group (2:57 min vs. 3:50 min, p = 0.004). In the final clinical proficiency test, the mean difference from the true NIHSS score was 0.64 (LoA: − 1.38 to 2.67) in the game group and 0.69 (LoA: − 1.65 to 3.02) in the control group. Conclusion Game-based digital simulation training is a feasible alternative to standard in-person simulation training to acquire competence in NIHSS assessment. Gamification seemed to give an incentive to simulate considerably more and to perform the assessment faster, with equal accuracy.publishedVersio

Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170.

We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.352

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe