Thursday, 31 May 2018

Canadians only - official petition to block the federal buyout of the #KinderMorgan pipeline

PLEASE SIGN AND SHARE WIDELY: , which has no potential buyers and whose product has no market. Stop the use of public money to buy out a Texas oil company. … #cdnpoli #bcpoli House of Commons E-petitions Please note that e-mail addresses from the Government of Canada may not be used to create, support, or sign an e-petition. Subscribe to RSS Feed E-1722 (OIL AND GAS) 42nd Parliament Initiated by harald Hommel from North Saanich, British Columbia, on May 31, 2018, at 4:22 p.m. (EDT) keywords Oil and gasTrans Mountain pipeline The Petition is open for signature until September 28, 2018, at 4:22 p.m. (EDT)  Petition details PETITION TO THE GOVERNMENT OF CANADA Whereas: The Trudeau administration has announced it will spend $4.5 billion of public funds on acquiring the existing Trans Mountain pipeline from Kinder Morgan; This $4.5 billion is not inclusive of construction costs for the expansion, projected to increase the cost of the deal to over $11 billion; The pipeline was valued at $550 million by Kinder Morgan in 2007; The expansion still has to pass the National Energy Board's 157 conditions and over a dozen court challenges before it can be built; During the election, Trudeau promised to overhaul the Harper administration’s deeply flawed pipeline approval process, respect Indigenous rights, and end fossil fuel subsidies; A diluted bitumen spill would devastate local ecosystems and economies on the West Coast, or any area surrounding the 800 bodies of water its path crosses; There is no proven way to clean up a diluted bitumen spill in a marine environment; Shipping out unprocessed diluted bitumen to refineries in other countries ships out Canadian jobs; and The Trans Mountain expansion will: lock in oil-sands production growth that cannot be reconciled with Canada’s greenhouse gas emissions reduction commitments, increase the risk of a diluted bitumen spill, violate the rights of Indigenous communities along the pipeline route, threaten Indigenous communities reliant on the marine environment for their livelihood and cultural practices. We, the undersigned, residents of Canada, call upon the Government of Canada to immediately halt any plans to purchase the Trans Mountain pipeline or otherwise support its expansion.  Sponsor Elizabeth May Saanich—Gulf Islands Green Party British Columbia  History Open for signature : May 31, 2018, at 4:22 p.m. (EDT) Closed for signature : September 28, 2018, at 4:22 p.m. (EDT)  Signatures (436) Province / Territory Signatures Alberta 8 British Columbia 297 Manitoba 5 New Brunswick 9 Newfoundland and Labrador 5 Northwest Territories 9 Nova Scotia 9 Ontario 75 Prince Edward Island 7 Quebec 7 Saskatchewan 4 Yukon 1

Flavonoids may slow lung function decline due to aging Science News from research organizations Date: May 21, 2018 Source: American Thoracic Society Summary: A type of flavonoid found in dark-pigmented fruits like red grapes and blueberries may slow the lung function decline that occurs with aging. Share: FULL STORY Previous research has shown that the plant-produced chemicals known as flavonoids have beneficial antioxidant and anti-inflammatory properties. Anthocyanins, the type of flavonoid investigated in the current study, have been detected in lung tissue shortly after being ingested, and in animals models of chronic obstructive pulmonary disease (COPD). The plant chemicals appear to reduce mucus and inflammatory secretions. However, "the epidemiological evidence on the association between flavonoids and lung function is very scant," said lead study author Vanessa Garcia-Larsen, PhD, assistant professor in the Human Nutrition Division of the Department of International Health at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. "So we wanted to investigate whether dietary intake and anthocyanins are associated with lung function decline in middle-age adults." The researchers analyzed data from 463 adults (average age: 44) who participated in the second and third European Community Respiratory Health Surveys from 2002 to 2012. Those included in the current study completed a dietary questionnaire and underwent spirometry at enrollment and upon follow-up. A common lung function test, spirometry measures the amount of air that a person can forcefully exhale in one second (FEV1), the total amount of air a person can exhale after taking a deep breath (FVC) and the ratio of the two, FEV1/FVC. Participants were then grouped into quartiles based on the amount of anthocyanins they consumed. The study found individuals in the highest, compared to the lowest, quartile of anthocyanin intake had: a slower rate of annual decline in FEV1 than those in the lowest quartile: -9.8 milliliters per year (mL/yr) vs. -18.9 mL/yr. a slower rate of annual decline in FVC than those in the lowest quartile: -9.8 mL/yr vs. -22.2 mL/yr. a slower rate of annual decline in FEV1/FVC: -0.02/yr. The researchers also analyzed the association between anthocyanin consumption and lung function in smokers, those who had never smoked and those who quit. The association between high consumption of the flavonoids and reduced lung function decline appeared to be stronger among both never smokers and those who had quit than in the general study population. Among smokers, the study did not find an association between anthocyanin intake and lung function. The study adjusted for a wide range of factors, including characteristics of participants' diets, gender, height, body mass index and socioeconomic status. Another strength of the study was its inclusion of participants from two countries, Norway and England. The study was limited by its relatively small size and the fact that diets were self-reported. "Our study suggests that the general population could benefit from consuming more fruits rich in these flavonoids like berries, particularly those who have given up smoking or have never smoked, Dr. Larsen said. "For smokers, quitting remains the best thing they can do to protect their health." The first European Community Respiratory Health Survey began in 1990 in response to a worldwide increase in asthma prevalence. The scope of the surveys has expanded to include information about the associations between behavioral and environmental factors that might also affect the development of COPD. Story Source: Materials provided by American Thoracic Society. Note: Content may be edited for style and length. Cite This Page: MLA APA Chicago American Thoracic Society. "Flavonoids may slow lung function decline due to aging." ScienceDaily. ScienceDaily, 21 May 2018. .

Intake of Raw Fruits and Vegetables Is Associated With Better Mental Health Than Intake of Processed Fruits and Vegetables

ORIGINAL RESEARCH ARTICLE Front. Psychol., 10 April 2018 | Kate L. Brookie, Georgia I. Best and Tamlin S. Conner* Department of Psychology, University of Otago, Dunedin, New Zealand Background: Higher intakes of fruits and vegetables, rich in micronutrients, have been associated with better mental health. However, cooking or processing may reduce the availability of these important micronutrients. This study investigated the differential associations between intake of raw fruits and vegetables, compared to processed (cooked or canned) fruits and vegetables, and mental health in young adults. Methods: In a cross-sectional survey design, 422 young adults ages 18–25 (66.1% female) living in New Zealand and the United States completed an online survey that assessed typical consumption of raw vs. cooked/canned/processed fruits and vegetables, negative and positive mental health (depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing), and covariates (including socio-economic status, body mass index, sleep, physical activity, smoking, and alcohol use). Results: Controlling for covariates, raw fruit and vegetable intake (FVI) predicted reduced depressive symptoms and higher positive mood, life satisfaction, and flourishing; processed FVI only predicted higher positive mood. The top 10 raw foods related to better mental health were carrots, bananas, apples, dark leafy greens like spinach, grapefruit, lettuce, citrus fruits, fresh berries, cucumber, and kiwifruit. Conclusions: Raw FVI, but not processed FVI, significantly predicted higher mental health outcomes when controlling for the covariates. Applications include recommending the consumption of raw fruits and vegetables to maximize mental health benefits. Introduction “You are what you eat” is a well-known adage that is increasingly supported by evidence linking healthy diets to optimal physical and mental health (Rooney et al., 2013; Robberecht et al., 2017). An important driver of the relationship between diet and health is high fruit and vegetable intake (FVI) (Lampe, 1999; Trichopoulou et al., 2003). Fruits and vegetables contain a variety of micronutrients critical to physical and mental function (Kaplan et al., 2007). Antioxidants such as vitamin C and carotenoids are said to play a pivotal role in protecting the body against oxidative stress, which is responsible for the causation and progression of neurodegenerative diseases, chronic inflammatory disease, atherosclerosis, some cancers, and some forms of depression (Byers and Perry, 1992; Irshad and Chaudhuri, 2002; Raison and Miller, 2011). Furthermore, the water-soluble vitamins (vitamin C, and B vitamins), and certain minerals (calcium, magnesium, and zinc), are important for optimal cognitive and emotional functioning (Huskisson et al., 2007; Kaplan et al., 2007). There is now good evidence that higher FVI is related to better mental health. Research has established that people who eat more fruits and vegetables have a lower incidence of mental disorders, including lower rates of depression, perceived stress, and negative mood (Trichopoulou et al., 2003; Mikolajczyk et al., 2009; Jacka et al., 2010, 2011, 2017; Ford et al., 2013; Gopinath et al., 2016; Bishwajit et al., 2017; Li et al., 2017). People who eat more fruits and vegetables also have a higher likelihood of optimal mental states, such as greater happiness (Lesani et al., 2016), positive mood (Ford et al., 2013; White et al., 2013), life satisfaction (Blanchflower et al., 2013; Mujcic and Oswald, 2016), and socio-emotional flourishing, which captures feelings of meaning, purpose, and fulfillment in life (Conner et al., 2015, 2017a). Importantly, these associations between FVI and various mental health indicators appear to be (i) dose-dependent (to various points) whereby higher intakes of fruit and vegetables (FV) are associated with increasingly higher mental health scores (e.g., Blanchflower et al., 2013), (ii) robust when controlling for demographic, economic/social, and health covariates (e.g., gender, income, education, BMI, smoking, exercise; Blanchflower et al., 2013; Mujcic and Oswald, 2016; Bishwajit et al., 2017), and (iii) bolstered by longitudinal and intervention research that has shown causal relationships between higher FVI and mental health (Carr et al., 2013; Mujcic and Oswald, 2016; Conner et al., 2017a; Jacka et al., 2017). For example, using longitudinal data from 12, 389 people in the Household, Income, and Labor Dynamics in Australia (HILDA) Survey, Mujcic and Oswald (2016) found that a shift from “low” to “high” intake of FV across a period of 2 years resulted in significant improvement in life satisfaction, showing an average gain comparable to moving from unemployment to employment. Interventions have also shown that increasing fruit and/or vegetable consumption improves depressive symptoms among clinically-depressed adults (Jacka et al., 2017), improves feelings of vigor in young men with low baseline levels of vitamin C and a higher baseline mood disturbance (Carr et al., 2013), and increases flourishing in young adults with a low baseline consumption of FV (Conner et al., 2017a). Some research has indicated that positive mood states can also shift people toward healthier food choices (Gardner et al., 2014), and negative mood states such as stress can shift people toward unhealthier food choices and overeating (Singh, 2014); however, the longitudinal and experimental research designs outlined above provide convincing evidence that FVI can also have a direct and causal impact on subsequent psychological well-being. While it is clear that there is a relationship between FVI and mental health, it is still unknown whether the ways that fruits and vegetables are prepared and consumed—that is, whether they are eaten raw, cooked, or from cans—might have distinctly different effects on mental health. There is evidence from the nutrition literature that the nutrient content in FV is reduced with cooking and canning. Cooking fruits and vegetables can alter the bioavailability of nutrients, which may have been hypothesized to play an influential role in the neurotransmission systems involved in mood and well-being (Kaplan et al., 2007). Water-soluble nutrients such as vitamin C and B vitamins are particularly vulnerable to heat degradation (Nicoli et al., 1999; Lee and Kader, 2000; Rickman et al., 2007a,b), which means that cooking would reduce the amount of mental health-conferring micronutrients from foods like spinach, bell peppers/capsicum, and green beans. Some evidence also suggests that cooking can reduce the quantity and activity of antioxidants (Nicoli et al., 1999; Zhang and Hamauzu, 2004), which is considered another mechanism linking FVI to mental health (Kaplan et al., 2007). However, other research indicates that cooking can actually enhance the bioavailability and activity of antioxidants (Dewanto et al., 2002; Turkmen et al., 2005; Miglio et al., 2008), and, that fat-soluble nutrients such as vitamins A, D, E, and K are less susceptible to damage by heat and processing than water-soluble nutrients, thus limiting the deleterious effects of cooking on nutrient profiles (Rickman et al., 2007b; Yuan et al., 2009). The effects of cooking on nutrient profiles may also differ between types of fruits and vegetables; for example, cooking tomatoes enhances the bioavailability of nutrients such as lycopene and antioxidants, whereas cooking broccoli loses many of its vital nutrients (Dewanto et al., 2002; Vallejo et al., 2002; Yuan et al., 2009). Further, eating canned FVI may also confer a nutrient profile similar to cooked FVI. Evidence has shown that longer storage times for canned fruits and vegetables can reduce the bioavailability of nutrients (Rickman et al., 2007a). Other forms of processing like freezing may not be as deleterious on nutrient content (Hebrero et al., 1988; Asami et al., 2003), but may depend on how people consume the frozen produce; for example, frozen berries eating in smoothies might retain their nutrient density, whereas frozen vegetables, which typically requires thawing and cooking, might have reduced nutrient content. Overall, the nutritional evidence regarding processing (cooking, canning, freezing), and nutrient loss in fruits and vegetables is nuanced. Yet for key micronutrients that have been linked to mental health such as vitamin C and carotenoids (Boehm et al., 2013; Carr et al., 2013), cooking and canning would most likely lead to a degradation in nutrients, thereby limiting their beneficial impact on mental health. There is some evidence of differential associations with mental health depending on whether FV is consumed raw or in processed forms. We found three correlational studies that measured raw and cooked FVI separately and reported their associations with mental health; all three found that raw FVI was the stronger predictor of some (but not all) mental health outcomes than cooked FVI (Appleton et al., 2007; Mikolajczyk et al., 2009; El Ansari et al., 2014). In one study of 10,602 men living in France and Ireland, higher intakes of raw fruits and vegetables were significant predictors of less depressed mood (b = −0.10 and b = −0.13, respectively), while cooked vegetables were not (b = −0.02) (Appleton et al., 2007). In another a study of 3,706 undergraduate students across the United Kingdom, only consumption of salads/raw vegetables was negatively associated with stress in men; whereas raw fruit, raw vegetables, and cooked vegetables all significantly related to lower stress levels in women (El Ansari et al., 2014). Finally, in a study of 1,800 European students, there was a stronger inverse relationship between the consumption of salad and stress (b = −1.121) than that of cooked vegetables and stress (b = −0.82) in women; however, there were no differences between salads vs. cooked vegetables in regards to depressive symptoms (b = −1.69 vs. b = −1.69, both significant) (Mikolajczyk et al., 2009). The differential effects of raw vs. processed FVI on mental health could help to explain the results of a recent intervention study by Conner et al. (2017a). In that study, participants were randomized to either receive fresh FV for 2 weeks (a parcel of fresh carrots, kiwifruit or oranges, and apples), receive daily text-message reminders to increase FVI for 2 weeks (plus given a voucher to purchase FV), or a diet-as-usual control group. Both the intervention groups reported significant increases in FVI; however, only the group that directly received FV reported improved well-being. The authors proposed that this difference might be accounted for by the nature in which the FV were consumed. The group who received fresh FV indicated they were more likely to consume their produce raw, while the reminder group indicated higher rates of cooked FV. Although Conner et al. (2017a) did not measure preparation and eating methods except informally through a retrospective questionnaire, they speculated that the ways in which their participants chose to eat their produce may have influenced the extent to which FVI affected their participants' well-being. In spite of the preliminary evidence for the differential role of raw vs. processed FVI, it is still not completely clear whether consumption of raw FVI is superior to cooked or processed FVI in regards to mental health benefits. Although some preliminary evidence suggests an advantage of raw FVI over processed FVI (Appleton et al., 2007; Mikolajczyk et al., 2009; El Ansari et al., 2014; Conner et al., 2017a), research has not expressly tested the differential associations between raw vs. cooked/processed FVI on mental health outcomes, and, prior studies have largely been restricted to negative aspects of mental health such as depression (except Conner et al., 2017a). The aim of the current study was to investigate whether raw FVI is more strongly associated with a range of mental health outcomes than processed FVI in a cross-sectional survey of over 400 young adults. We contrasted consumption of raw fruit and raw vegetables with relatively more processed forms of these foods (cooked, frozen, canned or tinned, as a group) in order to investigate the benefits of FV in an unmodified state (raw), compared to FV that has undergone a level of processing that may cause changes to the nutrient quality and quantity. Six aspects of mental health were measured to capture both negative and positive aspects of the illness-wellness continuum: depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing. A wide range of demographic and health covariates were also measured. It was hypothesized that stronger associations would occur between raw FVI and mental health than between cooked or processed FVI and mental health, and that these associations for raw FVI and mental health would remain significant when controlling for the covariates. It was also hypothesized that there would be stronger relationships between raw FVI and the presence of positive mental health rather than absence of negative mental health, given the patterns in recent literature. Overall, evidence of a stronger association between raw FVI and mental health outcomes (vs. cooked/processed FVI and mental health outcomes) could have implications for public health policy recommendations to consume more fruits and vegetables in their raw and unprocessed forms. Materials and Methods This was a cross-sectional, correlational design. Because fruit and vegetable consumption varies by age (Billson et al., 1999; University of Otago and Ministry of Health, 2011), our study focused on a single age group of young adults ages 18–25. Young adults typically have the lowest fruit and vegetable consumption of all age groups (Thompson et al., 1999; University of Otago and Ministry of Health, 2011) and they are at high risk for mental health disorders (Johnston et al., 2014). Participants and Procedure Table 1 presents the participant characteristics of the sample. The participants were 422 young adults between 18 and 25 years old. Participants were recruited either as part of their undergraduate psychology course at a large New Zealand university (N = 105), or through Amazon's Mechanical Turk (MTURK, N = 317) an online crowdsourcing marketplace that allows researchers to source large groups of people to complete online surveys in exchange for payment. Participants needed to be 18–25 years old, and MTurk participants were required to be living in the United States, Australia, or the United Kingdom due to similar dietary patterns to the local New Zealand sample allowing for ease of comparison. However, too few participants were recruited from Australia and the United Kingdom. As such, the final MTurk sample included only individuals from the United States. All participants were provided with an electronic information sheet about the questionnaire, which was broadly advertised as a questionnaire about lifestyle factors with no specific reference to the aims of investigating diet or mental health. This study was approved by the University of Otago Human Ethics Committee (Category B) (#D17/158) and all participants provided informed consent by way of electronic signature. Upon completing the 25-min online questionnaire, Psychology Students were remunerated with course credits for completing a brief worksheet based on their participation and MTURK participants received a small cash payment of US$1.50. MTURK participants were required to complete various attention checks embedded in the questionnaire to ensure accurate and meaningful answers were being obtained (N = 76 did not pass attention checks and were not allowed to continue with the survey). Data were collected between the months of March and June 2017. TABLE 1 Table 1. Descriptive Statistics for the Sample (n = 422). Measures Demographics The first section of the questionnaire contained demographic covariate measures of age, gender (male, female, or gender diverse), ethnicity (Caucasian, Asian, Black, Hispanic, Mixed, other), student/employment status, and childhood and current socio-economic status (SES). Childhood SES was measured with three items (“My family usually had enough money for things when I was growing up;” “I grew up in a relatively wealthy neighborhood;” “I felt relatively wealthy compared to the other kids in my high school”); current SES was measured with three items (“I have enough money to buy things I want;” “I don't need to worry too much about paying my bills;” “I don't think I'll have to worry about money too much in the future”) (based on Griskevicius et al., 2011). Participants stated how much they agreed with each item using a Likert scale that ranged from 1 (Strongly Disagree) to 7 (Strongly Agree). Lifestyle Factors and Other Health Behaviors The second section contained a range of health and lifestyle covariate measures. Participants rated the quantity and quality of their sleep using two items from the Basic Nordic Sleep Questionnaire (Partinen and Gislason, 1995), asking “In a typical week, how many hours per night do you usually sleep?” and “How refreshed do you feel when waking up from sleep?” with five response options ranging from “Never refreshed” to “Very refreshed.” A single item was used to measure physical activity, asking how many days in a typical week an individual completes at least 30 min of exercise that was “enough to raise your breathing rate” (Milton et al., 2011). A number of examples of physical exercise were provided (e.g., cycling) as well as exclusions (e.g., housework). Participants entered their height and weight (responses available in both imperial and metric units) which was used to compute BMI (Nuttall, 2015). Participants indicated (yes/no) if they had any known health conditions from a list of 10 conditions including diabetes (Type 1 or Type 2), hypertension, history of cancer, osteoporosis, disordered eating behavior, cardiovascular disease, anemia, Chronic Fatigue Syndrome, Irritable Bowel Syndrome or Crohn's Disease, or “other,” and they indicated (yes/no) whether they had any food allergies from a list (i.e., dairy, eggs, peanuts, tree nut, wheat, soy, shellfish or fish, or other). Alcohol consumption was assessed by asking how many days in a typical week they consumed alcohol, and on those days when consuming alcohol, how many standard drinks they typically consumed, which were multiplied to derive a weekly alcohol consumption estimate. Participants also answered whether they currently used prescription anti-depressant or mood stabilizing medication, and whether they regularly took any vitamin or mineral supplements. Smoking status was assessed by asking how often participants smoked with five options: “I don't smoke now,” “Less than once a month,” “At least once a month,” “At least once a week,” and “At least once a day.” Dietary Assessment The second section of the survey also contained a range of dietary assessment questions, but the four categories relevant to this report are: raw vegetables; cooked/frozen/canned/tinned vegetables (processed vegetables); raw fruits; and cooked/canned/tinned fruits (processed fruits). Table 2 lists the dietary questions. For each food category, participants estimated the number of days per week they ate that food (0–7 days/week). If they reported eating that food at least 1 day per week, then they reported the number of servings they typically consumed on days when they ate that food (1–7+ servings/day, serving defined for each food category) and the types of foods they typically consumed from a checklist of commonly consumed foods in that category (e.g., carrots, lettuce, etc.). These three questions provided quantitative information regarding the intake of various food groups and also more richly descriptive information about the types of foods they typically ate within each food category. This method of dietary assessment has been used in similar previous research (Lesani et al., 2016; Mujcic and Oswald, 2016). In addition, an index of four unhealthy foods (chocolate, candy/lollies, French fries/hot chips, and soda; see Table 2) was measured as a covariate as well as several other food groups not discussed in the present report (legumes, juices). TABLE 2 Table 2. Food survey questions (and response items). Following the dietary assessment, participants were asked additional questions about their dietary habits including how they typically purchase and prepare their food with six possible responses (“I mainly purchase and prepare my food myself,” “I mainly buy and cook food as a flat, apartment, or in a group,” “My parents mainly prepare my food” or “I mainly prepare and purchase my food with my partner,” “I mainly eat at my University Residence Hall/Dormitory,” or “other”), and, whether they restrict or exclude certain foods based on health or ethical reasons to measure vegetarian status. Mental Health Measures Depressive Symptoms Depressive symptoms were measured using the Centre for Epidemiological Depression Scale (CESD; Radloff, 1977). Participants rated 20 statements about feelings of depression “in the last week including today,” with the response options “Rarely or none of the time (<1 day),” “Some or a little of the time (1–2 days),” “Occasionally or a moderate amount of the time (3–4 days),” and “Most or all of the time (5–7 days),” corresponding to an item score of 0, 1, 2, or 3. Responses were summed, reverse scoring as needed (α = 0.929). Anxiety Anxiety was measured using the 7 item Hospital Anxiety and Depression Scale—Anxiety Subscale (HADS-A; Zigmond and Snaith, 1983). Anxiety symptoms felt “in the last week including today,” were rated with response options of “Not at all,” “From time to time, occasionally,” “A lot of the time,” and “Most of the time,” corresponding to an item score of 0, 1, 2, or 3. Responses were summed, reverse scoring as needed (α = 0.854). Negative and Positive Mood Negative and positive mood was measured using a scale based on the affective circumplex (Barrett and Russell, 1999). The scale consisted of 24 mood items that varied by valence (negative/positive) and activation (high/medium/low). The negative mood items were hostile, stressed, irritable, angry, anxious, annoyed, nervous, tense, hopeless, unhappy, dejected, and sad. The positive mood items were enthusiastic, excited, energetic, joyful, happy, cheerful, pleasant, good, relaxed, calm, content, and satisfied. Items were randomized and presented in the same order for all participants. Participants responded to the question “Typically, do you feel…” for each item using a Likert scale anchored at 0 (None of the time), 1 (A little of the time), 2 (Some of the time), 3 (A good bit of the time), and 4 (Most of the time). Responses were averaged for a measure of negative mood (α = 0.945) and positive mood (α = 0.953). Life Satisfaction Life Satisfaction was measured with the Satisfaction with Life Scale (SWLS; Diener et al., 1985). Participants rated five statements for how they “personally feel at this time in [their] life,” e.g., “In most ways, my life is close to ideal” and “If I could live my life over, I would change almost nothing.” Responses were made on a Likert scale from 1 (Strongly disagree) to 7 (Strongly agree), which were summed (α = 0.905). Flourishing Flourishing was measured with the Flourishing Scale (Diener et al., 2010). Participants rated their agreement with eight statements related to well-being, including “I am engaged and interested in my daily activities” and “I lead a purposeful and meaningful life” on a Likert scale from 1 (Strongly disagree) to 7 (Strongly agree), which were summed (α = 0.922). Data Preparation Six participants were excluded due to incomplete data and two participants were excluded due to suspected errors in responding, which resulted in a final sample size of 422 participants. Gender was dummy coded using two variables with male gender as the reference group (male, female, and gender diverse coded as 0, 1, 0, and 0, 0, 1, respectively). Ethnicity was dummy coded using three variables with Caucasian ethnicity as the reference group (Caucasian, Asian, Black, all others, as 0, 1, 0, 0, and 0, 0, 1, 0, and 0, 0, 0, 1), respectively. Student status was dummy coded as 0 for non-students and 1 for any full- or part-time students. Childhood and current SES items were averaged to produce a total SES score (α = 0.844). BMI was computed by dividing weight by kilograms by the square of height in meters (Nuttall, 2015). Smoking was dummy coded to indicate non/infrequent smokers (0) vs. regular smokers who smoked at least once per week or more (1). Health condition, food allergy, and food restriction variables were dummy coded to indicate absence (0) or presence (1) of any major health condition, food allergy, or vegetarianism, respectively. Average daily servings of food groups were calculated by multiplying days per week consumed by servings per day consumed, and then dividing by seven to get an average daily intake estimate. This computation was done for each food category separately. We also created a combined raw fruit and vegetable daily intake (raw FVI) variable by summing the daily raw fruit and daily raw vegetable serving estimates together, and a combined processed fruit and vegetable intake (processed FVI) variable by summing the daily cooked/canned fruit and daily cooked/canned/frozen vegetable estimates together. Lastly, we created a combined unhealthy food index by summing the daily servings for chocolate, candy, French fries, and soda, however, due to low reliability (α = 0.276), the items were analyzed separately. Statistical Analyses Firstly, between-person (cross-sectional) relationships were tested using bivariate correlation coefficients in SPSS to investigate whether average raw and processed FVI, as well as unhealthy food intake, were associated with mental health outcomes. Secondly, a series of hierarchical regression analyses were conducted to predict the six mental health outcomes—depressive symptoms, anxiety, negative mood, positive mood, life satisfaction, and flourishing—from raw FVI and processed FVI as simultaneous predictors, controlling for the demographic and health covariates. All continuous variables were centered for analysis. In the first step, we entered the two fruit and vegetable variables (raw FVI and processed FVI, both centered) as simultaneous predictors plus their quadratic terms to test for any non-linear associations with the mental health outcomes. Non-significant quadratic terms were dropped from the final models for simplicity. In the second step, we entered covariates to isolate the unique associations between FVI and mental health. Covariates were included in the model if they correlated with either the predictors (raw FVI or processed FVI) and/or any of the mental health outcome measures. The covariate related to food preparation was dummy coded 1 if their parents prepared their food and 0 for all others because this was the only contrast that covaried with the predictor(s)/outcome(s). Lastly, we conducted exploratory analyses to determine which individual types of raw or processed fruits and vegetables were most strongly associated with mental health. Unadjusted bivariate correlations were computed between endorsement of a given food (0 vs. 1) and each of the six mental health measures to investigate whether particular food items were more strongly related to mental health outcomes than others. Results Descriptive Data The descriptive statistics can be found in Table 1. Overall, the sample was predominantly female (66.1%) and a majority identified as Caucasian (67.5%). The combined childhood and adult mean SES score (4.12) fell within a middle range, suggesting that participants perceived themselves as no better or worse off than others. The average BMI (24.85) was at the higher end of a healthy range (18–25). In regards to food consumption, healthy food items (fruits, vegetables) were eaten more frequently than the unhealthy foods. Participants reported eating ~3.2 daily servings of FV, which mostly consisted of raw fruit (1.2 servings), raw vegetables (1.0 servings), and processed vegetables (0.9 servings). Processed fruits were not frequently eaten (0.1 servings). The mean depressive symptoms score was 1.5 points above the 16-point cut-off for CES-D scores indicating possible risk for clinical depression. The mean anxiety score was below the 8-point cut-off on the HADS-A and therefore indicative of normal levels of anxiety. Positive mood was higher than negative mood, but life satisfaction was at the lower end of the average range for American college students (20–24) (Pavot and Diener, 1993) and flourishing was in the lower 25% compared to American college students (Diener et al., 2010). There were several significant differences between the MTURK and Psychology participants (data available from authors). Those recruited from MTURK (vs. Psychology) tended to be more male (36.0 vs. 21.0%), more ethnically diverse (66.6 vs. 70.5% Caucasian), older age (22.3 vs. 19.5 years), lower SES (4.0 vs. 4.6), have greater BMI (25.38 vs. 23.25), and feel less satisfied with their lives (21.2 vs. 23.7). Because of this difference, sample was included as a covariate in the regression analyses (coded Psychology = 0; MTurk = 1). Table 3 presents the inter-correlations among the fruit and vegetable measures, the unhealthy foods measures, and the mental health measures. The correlation between raw FVI and processed FVI was 0.265, p < 0.001. The correlation between raw fruits and raw vegetables was 0.422, p < 0.001. The correlation between processed fruits and processed vegetables was 0.103, p < 0.05. There were few associations between the fruit and vegetable measures and unhealthy foods. Consumption of processed FVI, particularly processed fruits, was associated with more unhealthy foods like candy and French fries. The unhealthy foods correlated with each other, with the exception of chocolate. All of the mental health measures were significantly correlated with each other above |r| 0.50, all ps < 0.001. TABLE 3 Table 3. Inter-correlations among the fruit, vegetables, unhealthy foods, and mental health measures. Bivariate Correlations Between Fruit and Vegetable Intake and Mental Health, Without Adjustment for Covariates The bivariate correlations between FVI and measures of mental health are presented in Table 4. Correlations between the unhealthy foods and mental health are also presented for completeness. Raw fruits and vegetables had the strongest associations with most of the mental health measures. Raw FVI was associated with fewer depressive symptoms and higher positive mood, life satisfaction, and flourishing. Raw fruits were additionally associated with reduced negative mood. By contrast, processed FVI was only associated with positive mood but not with any of the other mental health variables. The size of the correlations was significantly stronger for raw FVI than processed FVI for depressive symptoms (Z = −3.065, p = 0.001 one tailed), positive mood (Z = 1.912, p = 0.028 one tailed), life satisfaction (Z = 2.351, p = 0.009 one tailed), and flourishing (Z = 2.879, p = 0.002 one tailed) using the difference test between two dependent correlations with one variable in common (Lee and Preacher, 2013). The coefficients did not differ for anxiety (Z = −1.573, p = 0.058 one tailed) or negative mood (Z = −1.456, p = 0.073 one tailed). The unhealthy foods composite index was not related to the mental health variables, although higher soda consumption was correlated with more depressive symptoms and lower life satisfaction. TABLE 4 Table 4. Bivariate correlations between intake of fruit, vegetables, unhealthy foods, and mental health. Regression Models Using Fruit and Vegetable Intake to Predict Mental Health, Adjusting for Covariates Results from the regression analyses are presented in Table 5. Raw FVI, but not processed FVI, significantly predicted lower depressive symptoms and higher positive mood, life satisfaction, and flourishing when controlling for the covariates. There was also a significant quadratic pattern between raw FVI and positive mood, as shown in Figure 1. The inflection point occurred at 6.5 servings per day. This indicates that incremental improvements in positive mood were observed up to six and a half servings of raw FVI a day, after which increasing servings of raw FVI was associated with no additional benefits to positive mood. A quadratic regression term predicting depression from raw FVI was significant in the first step, but was no longer significant when demographic and lifestyle covariates were included. Lastly, it is notable that raw FVI predicted all three of the positive mental health measures (positive mood, life satisfaction, and flourishing) and only one of the negative mental health measures (depressive symptoms), which is consistent with predictions that FVI will be more strongly related to positive than negative mental health. TABLE 5 Table 5. Regression models predicting mental health variables from fruit and vegetable intake, demographic covariates, and health related covariates. FIGURE 1 Figure 1. The curvilinear relationship between consumption of raw fruits and vegetables and positive mood, adjusted for covariates. Single Food Item Analyses The unadjusted bivariate correlations between endorsement of a given food and each of the six mental health measures are presented in Tables 6, 7. In terms of raw vegetables, what could be considered “salad fixings” were most significantly related to aspects of mental health. These included vegetables like carrots, dark leafy greens (kale, spinach), lettuce, cucumber, red onion, cabbage, celery, tomato, and mushrooms. In terms of processed vegetables, pumpkin, mixed frozen vegetables, potatoes/sweet potatoes, broccoli, and eggplant were significantly related to positive mood, and several of these were also related to flourishing. Raw bananas and apples were the strongest predictors of most mental health measures and almost all other raw fruits such as grapefruit, berries, kiwifruit, stone fruit (peaches, apricots), pear, frozen berries (eaten raw), and grapes were related to positive mood and flourishing. TABLE 6 Table 6. Correlations between types of raw and processed vegetables, and mental health. TABLE 7 Table 7. Correlations between types of raw and processed fruits, and mental health. Discussion This study provided evidence that the consumption of raw fruits and vegetables has a stronger relationship with mental health than the consumption of cooked or canned (processed) fruits and vegetables. Although this was only a correlational design, the patterns were robust when controlling for demographic and health covariates, and they paralleled the findings of recent intervention research showing significant effects of increasing fresh FVI on mental well-being (e.g., through kiwifruit, Carr et al., 2013; through carrots, kiwifruit/oranges, apples, Conner et al., 2017a). Our study findings add to this literature by showing that when tested side-by-side, the consumption of raw fruits and vegetables significantly outperformed more processed forms of FVI in the prediction of mental health. While we did not test the mechanisms that may explain the stronger link between raw FVI and mental health, a likely factor is that raw fruits and vegetables deliver a greater amount of nutrients than cooked or canned fruits and vegetables. This idea is somewhat supported by the literature, with evidence indicating that cooking, canning, and processing can significantly decrease the nutrient content of some forms of produce (Nicoli et al., 1999; Lee and Kader, 2000; Zhang and Hamauzu, 2004; Rickman et al., 2007a). Raw fruits and vegetables may provide greater levels of micronutrients than processed fruits and vegetables, which could explain their stronger association with improved mental well-being. However, as outlined previously, evidence of significantly diminished nutrient levels in cooked and processed produce is varied, and appears to be individualized from nutrient to nutrient (Dewanto et al., 2002; Turkmen et al., 2005; Miglio et al., 2008). Further research is required to determine how processing affects nutrient levels in fruit and vegetables, and whether this actually translates to biologically significant differences in subsequent levels of micronutrients that are provided to the body. Findings have several applications for the promotion of health and well-being. First, future experimental research should examine the effects of increasing raw fruit and vegetables on mental well-being, given that greater mood-conferring benefits are likely to be seen with a predominantly raw based fruit and vegetable supplementation program. If our patterns are confirmed in intervention studies, it would suggest that heath policies could focus on promoting the consumption of raw and unprocessed produce for optimal well-being. Such interventions will require educating individuals on ways to prepare and consume fruits and vegetables that are likely to retain the greatest levels of nutrients. Furthermore, there may be additional barriers in developing raw plant food interventions. Previous qualitative research has shown that people view raw produce as less convenient due to its perishable nature than canned/processed/frozen produce (Brug et al., 1995; Hartman et al., 2013). Another limiting factor is cost and availability. Research has also suggested that people eat raw fruits and vegetables as snacks, whereas people incorporate more cooked/canned/processed produce into main meals (Brookie et al., 2017), and that sometimes raw fruits and vegetables are not considered satiating enough for a main meal (Brug et al., 1995; Hartman et al., 2013). Moreover, some people are less open to eating plant foods (i.e., people low in openness to experience, Conner et al., 2017b). As such, any policy or intervention aimed at increasing the consumption of raw fruits and vegetables may benefit from addressing accessibility and affordability, considering variation in food preferences, increasing healthy snacking on fruits and vegetables (with a high likelihood that these will be raw), and highlighting the ways in which raw FV can be incorporated into main meals that are satiating and fulfilling. Given the correlational design, we cannot be sure that food consumption is directly and causally driving improvements in mental health. As mentioned previously, mood states (both positive and negative) have the ability to influence subsequent food choices. However, the preliminary results achieved in the current study mean that more controlled experimental research—that would investigate directionality—is warranted. This study had other limitations aside from the correlational design. We used a non-validated food recall measure. However, this was based on previously designed and published measures suited to larger population studies (e.g., Lesani et al., 2016; Mujcic and Oswald, 2016). Additionally, there are inherent limitations associated with this type of dietary recall, including possible errors in estimation and memory recall, as well as inaccuracy in estimating serving sizes (Thompson and Byers, 1994). Future research should consider using gold standard methods such as a weighed dietary record. Finally, the current study did not measure some additional factors that could influence micronutrient availability. We did not measure different ways of preparing cooked foods that might affect nutrient content (boiling vs. steaming) nor did we separate the consumption of cooked vs. canned foods. Further, factors such as soil deficiencies, fat consumption, storage methods, and the quality of produce can all influence the availability and absorption of micronutrients within the body. While these factors were beyond the scope of the current study, it is important to keep in mind that the way in which nutrients journey from the food to the brain is influenced by a multitude of factors, beyond raw vs. processed. While the mood-conferring benefits of raw FV provide sufficient rationale for interventions, it should also be considered that the levels of poor mental health within this young adult sample require urgent attention. Young adults are considered at high risk of having poor mental health (Johnston et al., 2014), and the current sample was no exception. The mean depression score for the sample (M = 17.53) was above the 16-point clinical cut-off point on the CES-D, suggesting that young adults typically experience some symptoms of depression. The fact that this clinically significant level of depression was seen in the American MTurk participants (M = 18.07) and nearly seen for the New Zealand Psychology participants (M = 15.90) suggests that this phenomenon of young adult mental ill-health is pervasive, and does not necessarily reflect geographical or cultural environments. Given that young adults have high vulnerability to suffering from mental illness, and they also have the lowest fruit and vegetable consumption, the current results reaffirm young adults as an important population to target for mental health interventions, including those designed to improve diet. Conclusions The current findings showed that consumption of raw fruits and vegetables differentially predicted better mental health than the consumption of processed fruits and vegetables even when controlling for demographic, socioeconomic, and health covariates. The cooking and processing of FV has the potential to diminish nutrient levels, which likely limits the delivery of nutrients that are essential for optimal emotional functioning. In term of application, our results suggest that policies, promotions, and interventions that are designed to increase raw fruit and vegetable consumption may provide an accessible adjuvant approach to improving mental health in the young adult population, who remain vulnerable to developing mental disorders. Author Contributions KB: Conceived the idea and co-wrote the manuscript; GB: Collected data and co-wrote the manuscript; TC: Conceived the idea, co-wrote the manuscript, and provided supervisory support to KB and GB. All authors gave their approval for the final manuscript. Funding This study was funded by the Department of Psychology at the University of Otago. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgments This authors wish to acknowledge Louise Mainvil for her nutrition advice. 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The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. *Correspondence: Tamlin S. Conner,

Traditional knowledge sheds light on changing East Greenland climate and polar bear hunt Posted on May 31, 2018 in Featured News, Science // 0 Comments Frontiers in Marine Science: Traditional knowledge sheds light on climate change and polar bear ecology in East GreenlandThe study provides a valuable baseline for monitoring future changes as well as the polar bear population. Image: Shutterstock Inuit polar bear hunters report changes in their subsistence hunting patterns as well as polar bear ecology over the past decade, due to changing ice conditions and a quota system started in 2006. — By Anna Sigurdsson Inuit polar bear subsistence hunters from two East Greenland regions report changes to their hunting patterns as well as polar bear distribution and behavior due to decreasing sea ice and the introduction of hunting quotas in 2006. The hunters have observed large climate changes in their hunting areas — including warmer weather, less sea ice and disappearing glaciers — which the majority say have affected the polar bear hunt. More hunters are now using boats than dog sledges due to loss of sea ice. The hunters also note that more polar bears are coming into their communities looking for food, and that the bears are eating more seal parts than previously. Published in Frontiers in Marine Science, the study is the first in nearly 20 years to document traditional knowledge on polar bear catches and ecology in East Greenland — providing a valuable baseline for monitoring future changes as well as the polar bear population. Inuit hunters have a strong understanding of the Arctic environment and can share information passed down from older generations as well as from their personal experiences. This is very valuable to management and conservation efforts. Although traditional ecological knowledge about polar bears has been collected extensively in West Greenland, no comprehensive interview studies on polar bears have been carried out in East Greenland for close to two decades. Thus, current perspectives of polar bear hunters in this area are not well documented. “Our research was motivated by the importance of obtaining local perspectives from subsistence hunters in East Greenland about the subpopulation of polar bears,” says author Kristin L. Laidre, principal scientist at the Polar Science Center, University of Washington, USA. “There had not been an interview study for several decades so a new interview survey was important to conduct, especially before starting an assessment of the subpopulation.” Related: Combining genomics with farmers’ traditional knowledge to improve wheat production In interviews conducted by the Greenland Institute of Natural Resources, researchers gathered Inuit perspectives on polar bear subsistence quotas and hunting strategies from 25 full-time polar bear hunters in Tasiilaq and Ittoqqortoormiit. The aim was to gain an understanding of how climate change is affecting the polar bear subsistence hunt, and to document observed changes in polar bear distribution, abundance and biology over the last two decades. All interviewed hunters reported that they had observed changes to sea ice conditions. They noted, for example, that there is less ice, that the sea ice does not form or that it forms later than before, and that it is now more dangerous. Fifteen Tasiilaq hunters also said that the glaciers are disappearing very quickly. All Tasiilaq hunters noted changes in the weather, marked by worsened weather, warmer temperatures, more storms and more wind. Similarly, 89% of Ittoqqortoomiit hunters reported changing weather with warmer temperatures and more humidity. Seventy-three percent of Tasiilaq hunters and 88% of Ittoqqortoormiit hunters said that climate changes had affected the polar bear hunt. Furthermore, 100% of interviewed Tasiilaq hunters and 80% of Ittoqqortoomiit hunters reported that they hunt more with boats than with dog sledges compared to 10-15 years ago, due to decreasing sea-ice mass and larger extents of open water. One hunter said that he had gotten rid of his sledge, since he had no use for it anymore. Neither Ittoqqortoormiit nor Tasiilaq hunters reported major changes in the bears’ body condition, which is consistent with previous reports from indigenous people in other areas. However, Tasiilaq hunters noted that polar bears are consuming more seal parts than before, such as bones and skin. In addition, 81% of Tasiilaq hunters and 78% of Ittoqqortoormiit hunters noted that more polar bears are coming into towns and settlements compared to 10-15 years ago. Moreover, hunters from both regions noted that more bears were caught near settlements than previously. While some hunters explained this as a result of the hunting quotas increasing the abundance of polar bears, others mentioned decreasing sea ice as a possible reason. Two hunters suggested that polar bears are coming closer to the towns because they have less to eat and are searching for food. The researchers report that 40% of Tasiilaq respondents had caught between 10-19 polar bears in their lifetime, while 67% of Ittoqqortoormiit respondents had lifetime catches of more than 20 bears. The general consensus in Tasiilaq is that the quotas are necessary, whereas hunters in Ittoqqortoomiit do not view the quotas as necessary. Hunters in both areas would like to see a small portion of the quota used for trophy hunting, which is currently illegal in Greenland. The researchers point out that understanding the impact of management decisions and the decreasing sea ice is essential for polar bear conservation and management, as well as for the human communities that rely on hunting polar bears. Thus, this research provides an important baseline for monitoring future changes and for managing the polar bear population. “This information can be used to directly guide scientific lines of inquiry, improve management decisions, and overall ensure that traditional ecological knowledge is considered in the conservation and management of polar bears,” concludes Laidre. The research is part of a special article collection on the impact of climate change on subsistence users of living marine resources. Original article: Traditional Knowledge About Polar Bears (Ursus maritimus) in East Greenland: Changes in the Catch and Climate Over Two Decades REPUBLISHING GUIDELINES: Open access and sharing research is part of Frontiers’ mission. Unless otherwise noted, you can republish articles posted in the Frontiers news blog — as long as you include a link back to the original research. Selling the articles is not allowed.

Stem cells from adults function just as well as those from embryos Posted on May 14, 2018 in Featured News, Health Frontiers in Cardiovascular Medicine: Stem cells from adults function just as well as embryonic stem cellsInduced pluripotent stem cells (iPSCs) could be a viable alternative to embryonic stem cells in regenerative medicine. Image: Shutterstock Stem cells from elderly donors can be used for personalized treatment of age-related chronic and degenerative diseases, concludes a new review — By Emma Duncan Donor age does not appear to influence the functionality of stem cells derived from adult body tissues, concludes a new review. The analysis of research on induced pluripotent stem cells (iPSCs) finds that not only are typical signs of aging reversed in iPSCs, but cells derived from both older and younger donors show the same ability to differentiate into mature body cells. This validates iPSCs as a viable alternative to embryonic stem cells in personalized regenerative medicine. Published in Frontiers in Cardiovascular Medicine, the study highlights the enormous potential of iPSCs derived from elderly patients to treat their age-related diseases — and indicates future areas of research for this relatively new field. “As average life expectancy continues to rise, so does the rate of age-related chronic and degenerative diseases,” explains Dr. Nicolle Kränkel from Charité, a medical university in Germany. “Organ replacement and other cell-based treatments could increase longevity and improve the quality of life for elderly people with heart disease, kidney failure and even Alzheimer’s disease. Our analysis of current knowledge on iPSCs indicates that stem cells derived from older patients are suitable for personalized regenerative therapies as well as for modeling genetic disease.” Unlike most cells in the body, stem cells have the potential to develop into different cell types. Their discovery opened the possibility of growing specific cells to treat damaged tissues and organs, as well as genetic diseases. Stem cells can be derived from two sources: embryos and adult tissues. It was commonly believed that embryonic stem cells (ESCs) are the only reliable source, as these “young” cells have not accumulated the same level of cell damage as older cells. However, embryonic stem cells also have limitations. These include ethical concerns, immunological rejection of transplanted tissue derived from ESCs, and limited availability of donated material. The 2006 discovery of induced pluripotent stem cells — which can be derived directly from a patient — offers an attractive alternative. Their use has already been proved in a young patient: a boy suffering from a rare genetic disease, in which the skin blisters and tears off, recovered completely after receiving a skin transplant grown from his own gene-corrected stem cells. Related: Paraplegic rats walk and regain feeling after stem cell treatment However, questions remained about the impact of donor age on iPSC functionality — an especially relevant point given that the elderly stand to benefit the most from these stem cells. Kränkel and colleagues therefore critically analyzed the available research to date, to summarize what is known and identify future research needs. The analysis revealed that the age of the donor may reduce the efficiency at which their body cells can be reprogrammed into iPSCs. However, once generated, the stem cells appear to be rejuvenated – with typical signs of aging reversed. “iPSCs show improved functionality compared to the donor’s regular body cells, and can be differentiated into mature body cells with a similar efficiency to younger stem cell donors,” says Kränkel. “This means that stem cells from an elderly patient can be developed into other cells and returned to the patient for treatment.” Despite this promising conclusion, it is still a matter of debate as to whether cells from older donors have accumulated more damaging mutations than those of younger donors. “This seems logical,” says Elisabeth Strässler, co-author of the study. “There is also the issue of whether such mutations persist during the transformation to stem cells, or whether they are repaired.” Other important questions also remain unanswered. “The field of iPSC research is still rather ‘young’ and more research is necessary. This includes whether iPSC-derived cells might form tumors once transplanted back into a patient; consensus on which tests should be mandatory for assessing genetic stability and stem cell function; and defined protocols to better compare results from different labs,” concludes Kränkel. Original article: Age Is Relative — Impact of Donor Age on Induced Pluripotent Stem Cell-Derived Cell Functionality REPUBLISHING GUIDELINES: Open access and sharing research is part of Frontier’s mission. Unless otherwise noted, you can republish articles posted in the Frontiers news blog — as long as you include a link back to the original research. Selling the articles is not allowed.

OPEN WEBINAR IN ENGLISH Feminist pedagogies and training for gender equality:  a paradox?

What makes the principles of feminist pedagogies feminist? Especially when they can in fact be applied in training in ways that contradict gender justice and social transformation. Moreover, if gender training intends to disrupt dominant understandings of “gender”, how does this harmonise with what is commonly understood as feminist pedagogies? KIT Royal Tropical Institute and UN Women Training Centre are pleased to invite you to the public open webinar Feminist pedagogies and training for gender equality: a paradox?, where our team of trainers Maitrayee Mukhopadhyay, Franz Wong and Leticia Berrizbeitia will discuss these tensions in gender training using the Professional Development Programme for Gender Trainers as an illustration of how such paradoxes may arise and how they can be navigated. This event will also act as an informative session on the programme that is currently receiving applications for its second edition. Two sessions will be held on Wednesday 6 June 2018: Register for 7:30 AM AST session Click here to convert the time zone to your city Register for 10:00 AM AST session Click here to convert the time zone to your city About the Professional Development Programme for Gender Trainers After the success of the pilot program that took place between October 2017 and April 2018, the Royal Tropical Institute (KIT) and UN Women Training Centre are pleased to announce the opening of the second edition of the Professional Development Programme for Gender Trainers. This training includes different activities such as moderated on-line learning, remote monitoring of the participants tasks, as well as 2 face-to-face workshops in KIT facilities in Amsterdam. The second edition will take place from 22 October 2018 until the 30 April 2019, encompassing a total period of six-months. The first cohort was made up of 25 participants from 20 different countries, 15 of whom were part of or were linked to an international organisation. The programme was evaluated in a highly postive way by the participants, who agreed that the learning objectives were met and who would recommend the course to others working in training. Learn more and apply here!

31 May New publication: ‘Second is best: Dutch colonization on the “Wild Coast”‘ Posted at 10:01h in News Items, Spotlight on the Caribbean by Yayah Siegers 0 Comments Share ‘Second is best: Dutch colonization on the “Wild Coast”‘, by Jessica Roitman, in Lou Roper (ed.), The Torrid Zone: Colonization and Cultural Interaction in the Seventeenth- Century Caribbean, pp. 61-75. Columbia, SC: University of South Carolina Press, 2018. The Dutch wasted a great deal of effort on the area between the Orinoco and Amazon Deltas in the 17th century. While various trading posts and forts did manage to survive, at least 15 attempts at setting up colonies failed, and there may even have been more than these. Thus, this dismal history resulted in only one successful Dutch plantation colony on the Wild Coast: Suriname, seized from England, which was modestly successful because the infrastructure for successful plantation agriculture had already been put in place by the English. This infrastructure included not only the clearing of the land and the construction of houses, barns, sugar mills, and the laying of roads; it also meant that some sort of accommodation had been reached with the Amerindians. Lastly, it implied that there were enough ‘seasoned’ colonists – settlers with the immunities to the endemic diseases, knowledge of the region, and experience in practicing agriculture in the area – to keep the colonies going. If you are interested in the article, please contact Jessica Roitman: ln.vltik@namtior.

Monica H. Green, “Medieval Gynecological Texts: A Handlist,” in Women’s Healthcare in the Medieval West: Texts and Contexts (2000), Appendix, pp. 1-36

Wednesday, 30 May 2018

Food as Medicine Beets

HerbalEGram: Volume 13, Issue 1, January 2016 (Beta vulgaris, Chenopodiaceae) Editor’s Note: Each month, HerbalEGram highlights a conventional food and briefly explores its history, traditional uses, nutritional profile, and modern medicinal research. We also feature a nutritious recipe for an easy-to-prepare dish with each article to encourage readers to experience the extensive benefits of these whole foods. With this series, we hope our readers will gain a new appreciation for the foods they see at the supermarket and frequently include in their diets. The basic materials for this series were compiled by dietetic interns from Texas State University (TSU) in San Marcos and the University of Texas at Austin (UT) through the American Botanical Council’s (ABC’s) Dietetic Internship Program, led by ABC Education Coordinator Jenny Perez. We would like to acknowledge Jenny Perez, ABC Special Projects Director Gayle Engels, and ABC Chief Science Officer Stefan Gafner, PhD, for their contributions to this project. By Hannah Baumana and Lindsey Dureeb a HerbalGram Assistant Editor b ABC Dietetics Intern (TSU, 2013) History and Traditional Use Range and Habitat The garden, or sugar, beet (Beta vulgaris, Chenopodiaceae) is an annual vegetable which forms a dense cluster of dark green leaves attached to a large, bulbous root.1 Both greens (aerial parts) and roots are edible. Beets typically are grown in the spring and fall; they thrive in cool seasons. In warmer climates, beets are grown in the winter as well. The leaves can grow up to 18 inches tall, though they are best harvested at two to three inches. The plant produces red-tinged green flowers. Though red beetroots are most commonly available commercially, golden and “candy cane” red and white roots also exist. The United States, France, Poland, Germany, and Russia currently are the leading producers of beets.2 Selective breeding has produced several different varietals of Beta vulgaris, including sugar beet (used for sugar extraction), mangel-wurzel (used as livestock fodder), and Swiss chard (B. vulgaris subsp. cicla).1 Current research suggests that these varietals may help post-exercise muscle recovery, improve blood pressure, and combat dyslipidemia. Phytochemicals and Constituents Beets are nutritionally diverse, low in calories, cholesterol-free, and fat-free. Beet greens also are edible and contain calcium, vitamin A and carotenoids, vitamin C, and iron. 100 grams of beet greens contain 50% of the United States Department of Agriculture’s (USDA’s) Recommended Daily Allowance for vitamin C.2 Beetroots are a good source of folic acid, fiber, potassium, and manganese.3 They are also rich in niacin, vitamin B-6, pantothenic acid, iron, copper, magnesium, and manganese. Like carrots, the color of beetroots indicates the different nutrient compounds contained within. Red beets contain phytochemicals called betalains*, which can also be found in Swiss chard, rhubarb (Rheum rhabarbarum, R. rhaponticum, Polygonaceae), and prickly pear cactus (Opuntia ficus-indica, Cactaceae).4 Betanin, one of the most-studied betalains, has been shown to provide anti-inflammatory support in vitro and in animal models. Red beets contain 300-600 mg/kg of betanin, which gives this variety its signature ruby-red color. This is slightly unusual, since most red-colored foods owe their pigmentation to anthocyanins, another prevalent group of compounds with antioxidant actions. However, betanin has exceptionally high antioxidant activity, exhibiting 1.5-2 times more activity than its anthocyanin counterparts. Golden, or yellow, beetroots have greater concentrations of lutein than red beets. In the human body, lutein is found in high concentrations in the retina of the eye, and may help protect the eye from abnormal light sensitivity and degenerative diseases such as cataracts and macular degeneration. Beet greens contain higher levels of lutein and zeaxanthin, a similar carotenoid that also promotes healthy vision. Historical and Commercial Uses Beets were first cultivated in the Mediterranean region and have a history of use that dates back over 4,000 years.5 Modern cultivated beets are descendants from a wild plant called the sea beet (B. vulgaris subsp. maritima), which grew wild in North Africa and on the Mediterranean coast.1 Initially, humans consumed only the greens, and the root was used for medicinal purposes or animal fodder. Greek and Roman authors, including Theophrastus (3rd century BCE), Hippocrates (4th century BCE), Dioscorides (1st century CE), and Pliny the Elder (1st century CE), noted a wide variety of ailments they claimed could be cured or prevented by beetroot and greens consumption.6 The primary medicinal use of the beet was to detoxify the blood and cleanse the kidneys, liver, bowel, and gallbladder. Beets also were believed to contain aphrodisiac qualities, and carvings of beets were found on excavated frescoes from Greek brothels.7 Other conditions thought to be treated using beets included leprosy, wounds and skin disorders, dandruff, digestive issues, and earaches.6 Trade throughout Europe spread the growth of beets beyond the Mediterranean area, and the roots eventually evolved into the sweeter, more edible modern plant.4 The popularity of beets increased around the 16th century due to this careful cultivation. The high sugar content of the root made beets a significant economic crop in Europe in the 19th century as an alternative sweetener in the place of sugarcane (Saccharum officinarum, Poaceae). Currently, about 20-30% of the world’s sugar production comes from sugar beets.7 Today, the root and greens are consumed as a food product.8 The root can be prepared by boiling, roasting, baking, or pickling. Raw roots often are added to salads and soups. The greens can be prepared as any other bitter green, such as collard greens (Brassica oleracea, var. acephala, Brassicaceae). Beet juice and extract also are used as natural alternatives to red food dye and in various cosmetic products.9 Modern Research Current research shows that supplementation with beet juice has been shown to play a role in human exercise tolerance and recovery. One human study concluded that beet juice supplementation reduced the negative effects associated with muscle hypoxia after exercise.10 Muscle hypoxia occurs when adequate oxygen is not available for normal muscle activity. This impairs exercise tolerance and energy production from muscles. Another clinical trial reported that supplementation of beetroot juice for three days prior to strenuous exercise reduced the amount of oxygen spent and increased exercise endurance by reducing the time of muscle failure onset.11 This effect remained true during moderate exercise as well. Beets can affect blood pressure and dyslipidemia (a high level of cholesterol, triglycerides, or both in the blood), due to their high nitrate concentration. Dietary nitrates are converted to nitrites, which are known vasodilators (compounds which cause blood vessels to expand), in the body upon ingestion. Consumption of beet juice thus increases the concentration of plasma nitrites in the blood, which decreases blood pressure in healthy adults. When studying this effect, scientists also concluded that beet juice is protective against endothelial (related to the inner lining of arteries) damage, finding a decrease in systolic blood pressure by 6 mmHg after supplementation with beetroot juice.12 The nitrates in beets also aid in smooth muscle relaxation, further adding to its value as an exercise supplement.2 Professional and amateur athletes are increasingly adding beetroot juice to their exercise regimen, claiming an increase in stamina and decision-making speed following a promising 2015 study.13 Researchers concluded that after a week of supplementation with beet juice, healthy male subjects showed increased reaction time and athletic performance during a sprinting exercise.14 Another study showed a significant decrease in blood pressure, with a change of 10.4 mmHg systolic and 8 mmHg diastolic measurements, due to the high nitrate concentration in beets. This study also suggested that beets can prevent endothelial dysfunction and inhibit platelet aggregation. These effects were attributed to the ingestion of nitrates that are converted to nitrites and then reduced to nitric oxide in the stomach.15 Supplementation of beetroot, combined with hawthorn (Crataegus spp, Rosaceae) berry, increased plasma nitrate and nitrite concentrations, and significantly reduced triglyceride levels in 72% of participants with elevated triglycerides.16 Health Considerations Eating a moderate amount of red beetroots or products colored with red beet extract may cause some individuals to experience a temporary reddening of the urine.4 This is known as “beeturia” and is not harmful. However, it may also be an indication of abnormal iron levels in the body or of a problem with iron metabolism, as those with these pre-existing conditions are more likely to experience “beeturia.” Both root and greens of beets contain a high amount of oxalates, which may exacerbate conditions such as kidney stones. However, since beets also contain a high ratio of minerals to oxalates, the amount of bioavailability may be lower than foods with similar oxalic contents.17,18 * Betalains were first named as a unique set of pigments in 1968 by Andre Dreiding and the late Professor Tom J. Mabry, PhD, of the Department of Botany at the University of Texas at Austin. A world-renowned phytochemist and scholar, Mabry passed away in November 2015. Among his many academic distinctions and memberships, he was a former member of the ABC Advisory Board. Nutrient Profile3 Macronutrient Profile: (Per 100g [approx. 3/4 cup] raw beetroot) 43 calories 1.61 g protein 9.56 g carbohydrate 0.17 g fat Secondary Metabolites: (Per 100g [approx. 3/4 cup] raw beetroot) Excellent source of: Folate: 109 mcg (27.25% DV) Very good source of: Manganese: 0.32 mg (16% DV) Dietary Fiber: 2.8 g (11.2% DV) Good source of: Potassium: 325 mg (9.3% DV) Vitamin C: 4.9 mg (8.17% DV) Magnesium: 23 mg (5.75% DV) Also provides: Iron: 0.8 mg (4.44% DV) Phosphorus: 40 mg (4% DV) Vitamin B6: 0.07 mg (3.5% DV) Riboflavin: 0.04 mg (2.35% DV) Zinc: 0.35 mg (2.33% DV) Thiamin: 0.03 mg (2% DV) Niacin: 0.33 mg (1.65% DV) Calcium: 16 mg (1.6% DV) DV = Daily Value as established by the US Food and Drug Administration, based on a 2,000 calorie diet. Recipe: Roasted Beets with Orange-Balsamic Glaze Ingredients: 1/2 pound fresh beets 2 tablespoons olive oil Salt and pepper to taste 1/2 cup balsamic vinegar 2 tablespoons freshly-squeezed orange juice 2 teaspoons sugar Directions: 1. Heat oven to 350°F. Wash beets, scrubbing off any excess dirt, and trim off greens, if present. 2. Place beets in the middle of a large sheet of aluminum foil. Coat with olive oil, then sprinkle with salt. Wrap beets in the foil and roast for about 1 hour, checking every 15 minutes after 1 hour of cooking time, until beets are easily pierced with a knife. 3. Peel the skin off beets while they are still warm, but cool enough to handle. Take care with preparing cooked beets, as their vibrant red color will stain some surfaces and fabrics. 4. Prepare the glaze by combining vinegar, orange juice, and sugar in a small saucepan over medium-high heat. Bring to a boil, then turn heat down to maintain a simmer until the mixture has thickened and coats the back of a spoon. 5. To serve, thinly slice beets, then drizzle with glaze. References Beta vulgaris. Missouri Botanical Garden website. Available here. Accessed December 15, 2015. Murray M. The Encyclopedia of Healing Foods. New York, NY: Atria Books; 2005. Basic Report: 11080, Beets, raw. Agricultural Research Service, United States Department of Agriculture website. Available here. Accessed December 15, 2015. Mateljan G. World’s Healthiest Foods: Essential Guide for the Healthiest Way of Eating. Seattle, WA: George Mateljan Foundation; 2006. Vegetable Profile: Beets. University of Maryland College of Agriculture and Natural Resources website. Available here. Accessed January 4, 2016. Biancardi E, Panella LW, Lewellen RT. Beta maritima: The Origin of Beets. New York, NY: Springer-Verlag; 2012. Avey, T. The History Kitchen: Discover the History of Beets. October 8, 2014. Available here. Accessed December 15, 2015. First beets yielded only greens. Texas A&M Agrilife Extension website. Available here. Accessed January 4, 2016. Gliszczynska-Swiglo A, Szymusiak H, Malinowska P. Betanin, the main pigment of red beet: molecular origin of its exceptionally high free radical-scavenging activity. Food Addit Contam. 2006;23(11):1079-1087. Vanhatalo A, Fulford J, Bailey S, et al. Dietary nitrate reduces muscle metabolic perturbation and improves exercise tolerance in hypoxia. J Physiol. 2011;589(22):5517-5528. Bailey S, Winyard P, Vanhatalo A, et al. Dietary nitrate supplementation reduces the O2 cost of low-intensity exercise and enhances tolerance to high-intensity exercise in humans. J Appl Physiol. 2009;107(4):1144-1155. Kapil V, Milsom A, Okorie M, et al. Inorganic nitrate supplementation lowers blood pressure in humans. Role for nitrite-derived NO. Hypertension. 2010;65:274-281. Gray N. Faster sprints and better decisions: Beetroot juice backed for increased sports performance. September 21, 2015. Available here. Accessed January 4, 2016. Thompson C, Wylie LJ, Fulford J, et al. Dietary nitrate improves sprint performance and cognitive function during prolonged intermittent exercise. European Journal of Applied Physiology. 2015;115(9):1825-1834. Webb A, Patel N, Loukogeorgakis S, et al. Acute blood pressure lowering, vasoprotective, and antiplatelet properties of dietary nitrate via bioconversion to nitrite. Hypertension. 2008;51:784-790. Zand J, Lanza F, Garg H, et al. All-natural nitrite and nitrate containing dietary supplement promotes nitric oxide production and reduces triglycerides in humans. J Nut Res. 2011;21(4):262-269. Liebman M, Al-Wahsh IA. Probiotics and other key determinants of dietary oxalate absorption. Adv Nutr. 2011;2:254-260. Available here. Accessed December 23, 2015. Hanson CF, Frankos VH, Thompson WO. Bioavailability of oxalic acid from spinach, sugar beet fibre and a solution of sodium oxalate consumed by female volunteers. Food Chem Toxicol. 1989;27(3):181-4.

Re: Autophagy-stimulating Activities of Resveratrol Might Contribute to Mitigation of Alzheimer's Disease

Resveratrol Autophagy Alzheimer's Disease Date: 05-15-2018 HC# 101754-592 Kou X, Chen N. Resveratrol as a natural autophagy regulator for prevention and treatment of Alzheimer's disease. Nutrients. 2017;9(9):927. doi: 10.3390/nu9090927. Resveratrol is a polyphenol best known for its occurrence in grape (Vitis vinifera, Vitaceae) skin and seeds. Research shows that it may be useful to prevent and treat degenerative brain disorders such as Alzheimer's disease (AD). The purpose of this report is to review the molecular mechanisms of resveratrol in regulating autophagy and microRNAs (miRNAs) during AD. The report begins with an extensive review of the molecular mechanisms of AD as currently understood to enhance readers' understanding of how resveratrol may play a role in preventing/treating AD. Autophagy in AD The primary pathological markers of AD are accumulations of misfolded proteins, including amyloid-β (Aβ) plaques and neurofibrillary tangles formed of highly phosphorylated Tau protein, in the brain. The autophagy-lysosome system digests long-lived and abnormal protein complexes and organelles. Hence, autophagy is needed for healthy neural function; however, it decreases in aging. Declining autophagy leads to increased reactive oxygen species (ROS), cell death, and neurodegeneration. Abnormal accumulation of autophagic vacuoles is apparent in neurons in some neurodegenerative diseases and in a mouse model of AD. The level of autophagy-related Beclin1 is significantly reduced in brain tissue of patients with AD. In a mouse model of AD, lower Beclin1 levels lead to Aβ accumulation and neurodegeneration. Autophagy is regulated by multiple signal pathways; for example, the mammalian target of rapamycin (mTOR) pathway negatively regulates autophagy, so substances inhibiting mTOR can increase autophagy in neurons. Upregulating autophagy may provide a protective effect and is a target for AD treatment. MicroRNAs in AD miRNAs are small, non-coding RNAs that can reduce messenger RNA (mRNA) stability and protein expression by targeting specific mRNAs. They are involved in neurodevelopment and synaptic plasticity. miRNAs also have a role in the production of pro-inflammatory cytokines in AD, while reduced production of some miRNAs can increase the production of Aβ. Aβ peptide aggregation results from imbalanced Aβ production and disordered Aβ clearance. It may be involved in the development and progression of AD. [Note: It remains controversial whether Aβ plaque accumulation is a cause or a consequence of AD.] There is also some limited evidence that decline in miRNAs may increase production of phosphorylated Tau protein. Autophagy-related miRNAs are thought to be involved in the early stage of AD, while others may be involved in the late stage of AD and other degenerative diseases. Resveratrol and AD In vitro, resveratrol can reduce Aβ-induced cytotoxicity and cell apoptosis. Several in vivo studies suggest that resveratrol may be beneficial in preventing/treating AD. In a mouse model of AD, resveratrol treatment prevented neurodegeneration and cognitive decline. In a rat model of AD, resveratrol improved memory, putatively by increasing antioxidant activity. In amyloid precursor protein (APP)-transgenic mice, resveratrol decreased Aβ levels and brain amyloid deposition. In humans, consumption of red wine, rich in resveratrol, reduced symptoms of dementia. Resveratrol has some of the same effects as caloric restriction, which in rodent models may mitigate AD by improving glucose metabolism. The mechanisms of action of resveratrol are multifold, including increasing autophagic and lysosomal clearance of Aβ. Specifically, resveratrol can activate autophagy via its effects on both sirtuin 1 (SIRT1)-mediated transcriptional regulation and mTOR-dependent signaling pathways. Resveratrol can scavenge free radicals and suppress glial activation. For example, nuclear factor kappa-B (NF-κB) induces inflammatory responses, and its activity is increased with aging. Resveratrol treatment can suppress Aβ-induced activation of NF-κB in vitro. Also, resveratrol decreases lipopolysaccharide (LPS)-induced production of inflammatory cytokines and increases release of anti-inflammatory interleukin-10. Resveratrol can also modulate miRNAs. Resveratrol can reduce LPS-induced upregulation of pro-inflammatory miR-155 and upregulate anti-inflammatory miR-663. The authors briefly describe three clinical publications, relating to two human trials, which evaluated resveratrol treatment for AD. It is not clear how these articles were chosen or whether they are the only articles available. One trial evaluated 119 patients with mild to moderate AD who were treated with escalating doses of 500-2000 mg/day resveratrol or placebo for 52 weeks. The primary publication from this trial reported that resveratrol reduced Aβ in the plasma and cerebral spinal fluid compared with placebo, indicating that resveratrol can cross the blood-brain barrier; however, decline in brain volume was quicker in the resveratrol group. A second publication regarding a subset of the participants in that study [incorrectly cited in this review] reported reduced markers of neurodegeneration and reduced decline in cognitive tests in the resveratrol group. The third study evaluated 18 patients with mild cognitive impairment who were treated with 150 mg resveratrol for 48 weeks and concluded that resveratrol improved cognition and innate immune function. No significant adverse effects were reported. The authors conclude that resveratrol may be able to prevent/treat AD by improving autophagic activity, thereby reducing Tau hyperphosphorylation (which leads to neurofibrillary tangles), neuroinflammation, and Aβ accumulation. However, the exact molecular mechanisms are unknown. The study was funded by the National Natural Science Foundation of China; the Natural Science Foundation from Science and Technology Department of Hubei Province, China; a grant from the Donghu Scholar Program from Wuhan Sports University to author Kou; the Chutian Scholar Program, Hubei Superior Discipline Group of Physical Education and Health Promotion, and Outstanding Youth Scientific and Technological Innovation Team from Hubei Provincial Department of Education; and a grant from the Innovative Start-Up Foundation from Wuhan Sports University to author Chen. The authors declare no conflict of interest. —Heather S. Oliff, PhD