Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: For instance, applied without consideration for social interactions, trophy hunting of pride lions may intensify infanticide by immigrant males [23,28,123] and displace distressed females to hunt in fringe habitats exacerbating conflict with humans [124,126]. Prior to making decisions about lethal management or translocations of ‘problem’ individuals, wildlife managers may be well served by simulating relevant disturbance on focal populations, quantifying social network effects and adjusting management decisions for better outcomes [41,127]. As another example, the use of social network analysis in captive animal populations is already helping researchers characterize the dynamics of harmful agonistic interactions, such as tail biting in newly mixed groups of domestic pigs [128]. These data may help parametrize simulated disturbance to social network structure in captive systems by taking into account traits such as genetic relatedness in group composition and its link to aggression and health of animal subjects. Insights from this type of assessment may, in turn, improve animal welfare and safety of farm workers [129,130]. In summary, our work confirms previous findings that although elimination of the most central network members in elephant populations decreases network connectivity at the population level, it does not lead to network fragmentation—at least in networks with the structure and at the level of simulated disturbance tested in this research. Uniquely, however, our research shows that poaching-like stress in a large number of virtual elephant populations impedes the theoretical efficiency of social diffusion. A follow-up question about the relationship between the structural network changes and population performance will require simulating a dynamic process that accounts for network reorganization after poaching. In addition, to tease apart an individual’s importance due to network position versus age-specific experience will require a method that accounts for interaction-mediated information transfer. Still, our simulation approach can be easily altered to test basic hypotheses about disturbance of social interactions in wild and captive systems. Supporting informationS1 Table. The composition of 100 virtual population according to kinship. Detailed here are the number of clan, bond and core groups, as well as individuals per population; the number of bond and core groups, and individuals per clan; the number of core groups per group; and the number of individuals per bond and core groups.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: Another strength of our research is that we adjusted for a large number of potential confounders, including socioeconomic status and lifestyle factors. However, some factors, such as physical activity, diet quality, and self reported health status at baseline, could also be mediators for the relations of weight status and weight change patterns in young and middle adulthood with mortality risk, because they could be influenced by weight status and weight changes in young adulthood. 414243Our study also has several limitations. Firstly, our approximation of middle adulthood (age range 30-80 years, interquartile range 36-56) overlapped with late adulthood (age range 40-90, interquartile range 46-66). However, in the analysis stratified by baseline age, the results remained and were even stronger in participants under 60 years old at baseline, which further confirmed that weight gain and stable obesity in younger adulthood were associated with higher mortality risk. Secondly, we used recalled and self reported weight data at age 25 years and 10 years before the baseline survey and thus misclassification bias may have been introduced. However, several validation studies and a recent meta-analysis showed that recalled early life weight could be a valid measure to use in life course epidemiological analysis. 44 Thirdly, many covariates were available only at baseline, so we could not use time varying covariates to capture changes in possible confounders over time. Fourthly, we could not differentiate intentional from unintentional weight change, and additional information on reasons of weight change may enable better interpretation of the results of future studies and thus appropriate intervention strategies. Lastly, we did not evaluate the relations of changes in other adiposity related markers such as waist circumference and fat mass with mortality owing to lack of data at different time points. Further studies with repeated data on these markers may provide a more comprehensive picture of the changes in obesity status and mortality risk. Conclusions and public health implicationsOur study found that stable obesity across adulthood and weight gain from young to middle adulthood was associated with increased risks of all cause and heart disease mortality, as was weight loss in middle to late adulthood. Future studies are needed to unravel the mechanisms underlying the association between weight change across adulthood and mortality, particularly the relations of changes in body composition to mortality. In addition, as weight loss is less achievable (only 1. 4% participants changed from the obese to the non-obese category from young to late adulthood), our results suggest that prevention of weight gain might be more important.

Output: contrast


Input: Claim: Adaptive radiation explains species diversification in new environments. [SEP] Text: 1186/1471-2148-12-212. 2149. 10. 1111/jbi. 12370. 598. 10. 1098/rspb. 2006. 3758. 2562. 10. 1111/j. 1420-9101. 2011. 02391. x. 113. 10. 1086/668599. 88. 10. 1016/S1055-7903(03)00278-1. 16. 10. 1016/j. ympev. 2008. 12. 010. 276. 10. 1016/j. ympev. 2008. 04. 024. 27. 10. 1016/j. gene. 2006. 03. 028. 146. 10. 1038/424145a. 831. 10. 1046/j. 1365-2656. 2002. 00649. x. 369. 10. 1007/s00338-010-0713-3. 347. 10. 1007/s10641-010-9606-0. 353. 10. 1007/BF00001464. 138. 147. 10. 1016/j. tree. 2006. 11. 002. 22. 10. 1111/j. 1365-294X. 2011. 05433. x. 3066. 10. 1093/nar/gkf436. 180. 10. 1111/j. 1096-0031. 2010. 00329. x. 3. 2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst Biol. 2012, 61: 539-42. 10. 1093/sysbio/sys029. 33. 10. 1093/molbev/msh123. 10. 1038/nmeth. 2109. 10. 1186/1471-2148-7-214. 290. 10. 1093/bioinformatics/btg412. 9. 10. 1046/j. 1365-294X. 2002. 01550. x. 90. 10. 1093/bioinformatics/btl446. 10. 1186/1742-9994-1-5. 4. 0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. waiver ( applies to the data made available in this 10.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Experimental disturbances reveal group-level costs of social instability. Sci. 2018;285. pmid:30429300 View 46. Puga-. Social style and resilience of macaques’ networks, a theoretical investigation. Primates. 2019;60: 233–246. View 47. . Detecting and quantifying social transmission using network-based diffusion analysis. J Anim Ecol. 2020. View 48. . Transmission in Animals: Lessons from Studies of Diffusion. Front Psychol. 2016;7: 1147. View 49. Pasquaretta C, Levé M, Claidière N, van de Social networks in primates: smart and tolerant species have more efficient networks. Sci Rep. 2014;4: 7600. View 50. Sosa S, Sueur C, Puga-Gonzalez I. Network measures in animal social network analysis: Their strengths, limits, interpretations and uses. Evol. 2020. View 51. ôrtes. Decay of interspecific avian flock networks along a disturbance gradient in Amazonia. Sci. 2014;281: 20132599. View 52. . Human disturbance causes widespread disruption of animal movement. Evol. 2021. View 53. -C. Mammal diversity will take millions of years to recover from the current biodiversity crisis. . 2018;115: 11262–11267. View 54. Approaching a state shift in Earth’s biosphere. Nature. 2012;486: 52–58. View 55. . Intense harvesting of eastern wolves facilitated hybridization with coyotes. Ecol Evol. 2012;2: 19–33. View 56. é Continent-wide survey reveals massive decline in African savannah elephants. PeerJ. 2016;4: e2354. View 57. Blanc J. Loxodonta africana. of Threatened Species. In: of [Internet]. 2008 [cited 28 Aug 2019]. 58. -. Illegal killing for ivory drives global decline in African elephants. . 2014;111: 13117–13121. View 59. Wittemyer G, Douglas-Hamilton I, Getz WM. The socioecology of elephants: analysis of the processes creating multitiered social structures. Anim Behav. 2005;69: 1357–1371. View 60. . African elephant play, competence and social complexity.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: Taken together, the findings indicate that maintaining normal weight throughout the adulthood, especially prevention of weight gain in early adulthood, should be encouraged to reduce risk of premature deaths. Finally, further studies are still needed to consider other health related and obesity related outcomes, and clinical trials on the long term health consequences of weight loss are also warranted. What is already known on this topicHigh body mass index in adulthood is associated with higher risk of premature deathScientific evidence on weight change from young to late adulthood or from middle to late adulthood in relation to risk of mortality is not entirely consistentLittle is known about associations between weight change across adulthood, especially from young to middle adulthood, and all cause and cause specific mortalityWhat this study addsWeight gain from young to middle adulthood was associated with increased risk of mortality from all causes and heart diseases in US adultsWeight loss over this period was not significantly related to mortality, and people who remained obese had the highest risk of mortalityAcross adulthood, the association between weight gain and mortality attenuated with increasing age, whereas that with weight loss from middle to late adulthood became stronger and significantThe results highlight the importance of maintaining normal weight across adulthood, especially preventing weight gain in early adulthood, for preventing premature deaths in later lifeFootnotesContributors: CC, XFP, and AP conceived the study design. CC and YY did the statistical analysis. CC and AP wrote the manuscript. All authors provided critical revisions of the draft and approved the submitted draft. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. AP is the guarantor. Funding: This study was supported by grants from the Research and of China to AP (2017YFC0907504) and the (No 176596) and of the Council (No 20180062) to XFP. The funders had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, and approval of the manuscript; or the decision to submit the manuscript for publication. Competing interests: All authors have completed the ICMJE uniform disclosure form at (available on request from the corresponding author) and declare: no support from any organisation for the submitted work other than those described above; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 1017/S1092852915000681 [Opens in a new window] This is an 4. 0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited Copyright © Press 2015 eating disorder (BED) is the most common of eating disordersReference Hudson, Hiripi, Pope and Kessler 1 and is characterized by excessive and rapid food intake without concomitant purging behaviors. BED is commonly associated with obesity but also occurs without obesity. Reference Hudson, Hiripi, Pope and Kessler 1 Reference Kessler, Berglund and Chiu 2 A range of cognitive abnormalities has been reported in BED. The study of cognitive processes allows us to address several issues of relevance to BED. First, cognitive processes have well-defined neural correlates from animal and human studies and represent powerful intermediate endophenotypes that mediate brain function and behavior. Reference Insel, Voon and Nye 3 Thus, cognitive impairments may reflect underlying impairments in corresponding brain substrates. Second, demonstrating similarities across differing pathological disorders provides insights into dimensional mechanistic similarities that might cut across seemingly differing behaviors and assist with further conceptualization of a disorder. Reference Insel, Cuthbert and Garvey 4 How BED might compare with other eating disorders, obesity without BED, and disorders of addiction or impulse control may help with conceptualization of BED. Reference Gearhardt, White and Potenza 5 – and Fletcher 8 This converges with the trend toward dimensional psychiatryReference Insel, Cuthbert and Garvey 4 by conceptualizing binge eating beyond the simple phenomenon of eating behavior (eg, anorexia nervosa or bulimia nervosa), to identifying biological or cognitive endophenotypes that may link this behavior of persistent, out-of-control, rapid consumption of a highly palatable natural reward (food) with other potentially relevant behaviors. Third, differentiating between BED and non-BED obese subjects can further help with defining subtypes of obesity and help particularly with characterizing the heterogeneity of obesity. Thus, understanding cognitive processes underlying BED may help elucidate underlying neural networks, mechanisms leading to aberrant behaviors, and also help with conceptualization of BED and differentiating BED as a subtype of obesity. Aberrant cognitive processes may also represent a marker as a predictor for outcomes, for treatment targets, and to assess therapeutic outcomes.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: pmid:21411454 View 117. van é C. The 2020 elephant die-off in Botswana. PeerJ. 2021;9: e10686. pmid:33510975 View 118. Poaching empties critical wilderness of forest elephants. Curr Biol. 2017;27: R134–R135. pmid:28222286 View 119. . Long-term impacts of poaching on relatedness, stress physiology, and reproductive output of adult female african elephants. Conserv Biol. 2008;22: 1590–1599. pmid:18759771 View 120. . State-space models reveal a continuing elephant poaching problem in most of Africa. Sci Rep. 2020;10: 10166. pmid:32576862 View 121. Mengak MT. Series—Wildlife Translocation. U. S. Department of Agriculture. Animal & 2018. Available: 122. . Giraffe (Giraffa camelopardalis) social networks in areas of contrasting human activity and lion density. McQualter K, editor. Ethology. 2019;125: 702–715. View 123. . Protection from harvesting restores the natural social structure of eastern wolf packs. Biological Conservation. 2010;143: 332–339. View 124. . Shooting pheasants for sport: What does the death of Cecil tell us? Palmer C, editor. People and Nature. 2020;2: 82–95. View 125. . Using multi-scale behavioral investigations to inform wild pig (Sus scrofa) population management. PLoS One. 2020;15: e0228705. pmid:32032396 View 126. . leo Bos taurus Types. Animals (Basel). 2020;10. pmid:32316176 View 127. Shier DM. Effect of family support on the success of translocated black-tailed prairie dogs. Conserv Biol. 2006;20: 1780–1790. pmid:17181813 View 128. Büttner. Social network analysis—centrality parameters and individual network positions of agonistic behavior in pigs over three different age levels. Springerplus. 2015;4: 185. pmid:25932371 View 129. -. One Welfare—a platform for improving human and animal welfare. Vet Rec. 2016;179: 412–413.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: reports BackgroundThere is ample evidence for the U-shaped or J-shaped relationships between body mass index (BMI) and mortality risk [1, 2]. However, most previous studies ignored the dynamic feature of body weight over time. Many adults may experience weight gain due to a sedentary lifestyle and excessive dietary intake [3]. In contrast, a progressive decrease in weight is often observed later in life [4]. Although the association between weight change and mortality has recently attracted much attention, the findings remain inconclusive. A meta-analysis of 26 prospective studies has shown that both weight gain and loss were associated with increased mortality risk among middle-aged and older adults [5]. In contrast, a longitudinal study in Australia indicated that weight loss, but not weight gain, was associated with increased all-cause and cause-specific mortality among older adults [6]. Previous studies predominantly focused on Western populations and were mostly limited to relatively small sample sizes. Meanwhile, these studies differed substantially, involving inconsistent weight indicators (mostly absolute weight) [7, 8] and variability in the categorization of weight change [6, 7]. Moreover, the threshold of weight loss or weight gain at which the risk of mortality begins to increase remains inadequately delineated. Therefore, a study that encompasses a large-scale community-dwelling population and utilizes an appropriate nonlinear methodology is imperative to understand the association between weight change and mortality risk. Age differences have also been observed in the association between weight change and mortality [7, 8]. A longitudinal study conducted in Korea confirmed the interactive associations between absolute weight loss and mortality among middle-aged and older adults [8]. Using prospective data from two longitudinal cohort studies, Yuan et al. found that absolute weight gain was associated with a higher risk of all-cause mortality among participants aged < 60 years, while this association was not observed among those aged ≥ 60 years [7]. Thus, our analyses were stratified by age. In this large-scale prospective cohort study of nearly 0. 75 million Chinese adults, we evaluated the associations of percentage change in BMI and absolute weight change with mortality from all causes, non-communicable disease, CVD, and cancer. MethodsStudy populationThis prospective cohort study used data from the Cohort (SHBDC) in China. Details of the study design and population have been reported in Additional file 1. In brief, the SHBDC has enrolled participants at any time during 2009–2022 in Shenzhen, China.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Risk taking can also be considered a form of impulsivity and can occur in the context of risk (or known probability) or uncertainty (in which the probability is unknown). Response inhibition Response inhibition is the capacity to inhibit prepotent motor responses, which can span the processes of action restraint (eg, tested using the “go/no-go” task, in which actions that are not yet initiated are inhibited) or action cancellation (eg, tested using the “stop signal” task, in which actions that are already initiated are inhibited). Reference Dalley, Everitt and Robbins 10 These are common measures of response control, with meta-analyses showing deficits in attention-hyperactivity disorder, a disorder associated with impulse control impairmentsand Schachar 11 substance use disorders, particularly to stimulants, nicotine, and alcohol, but not to opioids or cannabis; and pathological gambling. Reference Smith, Mattick, Jamadar and Iredale 12 Impairments in the stop signal task have also been shown in unaffected siblings of stimulant-dependent subjects, which suggests an endophenotypic risk factor for the development of addiction. and Bullmore 13 Studies comparing obese BED patients against obese controls or against age- and gender-matched, healthy, non-obese controls suggest that response inhibition tested using the go/no-go task or stop signal task are impaired in BED only if paired with food cues. In one study using a go/no-go task with food and body words, BED subjects made more commission errors to both food and body words compared to non-BED obese subjects. Reference Mobbs, Iglesias, Golay and Van der Linden 14 Similarly, another study showed that BED compared to non-BED obese subjects had prolonged stop signal reaction time in a stop signal task involving food images. The study also showed that BED had greater commission errors to food versus non-food images. Reference Svaldi, Naumann, Trentowska and Schmitz 15 In contrast, 2 studies comparing BED versus their own healthy volunteers did not show an impairment in a neutral stop signal task without food cues.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Elephant poaching in Niassa Reserve, Mozambique: population impact revealed by combined survey trends for live elephants and carcasses Published online by Press: 15 October 2014 Vernon R. Booth andKevin M. author details Vernon R. Booth* Affiliation: 9. Dunham Affiliation: PO Box CH385, Chisipite, Harare, Zimbabwe * (Corresponding author) E-mail vernonrbooth@gmail. com 0. 87 mb) View PDF [Opens in a new window] Save to to Save to & Permissions [Opens in a new window] in the populations of large herbivores in Niassa Reserve, Mozambique, have been monitored through biennial aerial surveys since 1998. The elephant Loxodonta africana population has been subjected to intensive illegal hunting since 2006. We used a simple population model to mimic the observed trends in the numbers of live and dead elephants to demonstrate the impact of poaching. The number of fresh or recent carcasses recorded was used in the model as an index of the annual mortality rate. A maximum likelihood analysis to compare population models revealed that the best fit to the survey estimates of both live elephants and old or very old carcasses was a model that started with 6,635 elephants in 1987. This number increased through births by 4. 6% annually and decreased through deaths from natural and anthropogenic causes. In the best-fit model, the mean mortality rate in any year was 3. 2 times the observed 1 + 2 carcass ratio (ratio for carcasses in age categories 1 and 2), and carcasses remained visible for a mean of 6 years. The model suggested that c. 900 elephants were poached during 2007–2010 and another c. 1,000 during 2011. Population estimates for live elephants and carcasses are now routine outcomes of aerial surveys conducted as part of the CITES programme for Monitoring the of Elephants, and our method can be applied to any population with a time series of estimates for live and dead elephants. surveycarcasselephantMozambiqueNiassapoachingpopulation modelpopulation trend Issue 1 January 2016 10.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: Corresponding with our results, two other studies conducted in Western nations similarly observed that weight loss, but not weight gain, was associated with increased all-cause mortality among middle-aged adults [12, 13]. In contrast, several studies with relatively small sample sizes found no significant association between weight loss and mortality, while weight gain was associated with increased mortality [14,15,16]. Two previous longitudinal studies examined the associations of weight change with CVD and cancer mortality, yielding conflicting results [17, 18]. A study conducted among 1664 adults aged ≥ 65 years revealed that weight loss was associated with higher CVD mortality but not cancer mortality [17]. In contrast, the study indicated that self-reported weight loss was associated with higher CVD mortality and cancer mortality among older adults, which is consistent with our findings [18]. Nevertheless, our study showed that excessive increase in BMI was also significantly associated with increased CVD mortality among older adults, while BMI change was not associated with CVD mortality among middle-aged adults. The possible explanation for the inconsistent findings in previous studies, apart from variations in the ages of the study participants [6, 7] and the relatively small sample sizes [14, 15, 17], may be also attributed to variability in the weight indicators [6, 19], different categorizations of weight change [6, 18], use of self-reported weight [18, 20], long duration of changes [20, 21], and the absence of accounting for potential confounding factors, such as baseline BMI [20, 22]. An alternative explanation may be that the results in many cohort studies could be influenced by potential reverse causation bias. For instance, the majority of these studies did not comprehensively exclude individuals with a history of serious illnesses [21, 23, 24]. In our study, we reduce the reverse causation bias by further excluding participants with CVD, cancer, respiratory disease, kidney disease, or digestive disorders. Additionally, we adjusted for baseline BMI to control the impact of confounding, as obese individuals often exhibit weight loss tendencies in contrast to lean individuals, while having a much higher mortality rate. One of the mechanisms by which a decrease in BMI would lead to a significantly higher risk of mortality is through reducing physical capability, impairing cardiopulmonary performance an increased risk of falls, and disability [25]. However, a lesser decrease in BMI was associated with increased mortality risk among older adults, but not middle-aged adults.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Wu, Giel and Skunde 16 Reference Mole, Irvine and Worbe 17 In these same studies, although the stop signal task was not impaired in BED subjects, subjects with bulimia nervosa had impaired response inhibition compared to healthy volunteersReference Wu, Giel and Skunde 16 and non-BED obese subjects, and those with alcohol use disorders had impaired response inhibition compared to healthy volunteers. Reference Mole, Irvine and Worbe 17 These studies thus suggest that response inhibition in the context of neutral cues may not be impaired in BED; however, in the context of food (and body) cues, both early and late response inhibition are more impaired in BED relative to non-BED obese subjects. Delay discounting Delay discounting tasks in both animal and human studies involve the selection of an immediate smaller reward and a larger delayed reward with variations in either the delay to the reward or the magnitude of the reward to calculate an indifference point in which the 2 options are selected equally. Reference Dalley, Everitt and Robbins 10 This represents the value attached to the delayed reward. Greater delay discounting is observed in and Rubia 18 and across a range of substance use disorders. Reference Bickel, Koffarnus, Moody and Wilson 19 In studies of BED subjects with mild obesity of mixed gender [body mass index (BMI) 33–35]Reference Mole, Irvine and Worbe 17 to moderate obesity in women (BMI 36–38),Reference Davis, Patte, Curtis and Reid 20 both BED and non-BED obese subjects had greater discounting of delayed rewards compared to healthy volunteers. In contrast, in a study in women with higher BMIs (BMI 42), BED subjects had greater discounting to delayed rewards in multiple domains, including food, money, sedentary activity, and massage time compared to non-BED obese subjects. Reference Manwaring, Green, Myerson, Strube and Wilfley 21 Thus, in the domain of delay discounting, an influence of severity of obesity appears to play a role: greater devaluation of the delayed reward appears to be common across BED and non-BED obese subjects, with mild to moderate BMI levels suggesting a core common cognitive deficit.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: 1017/S0030605314000568 [Opens in a new window] © Fauna & 2014 have been notable increases in both the poaching of African elephants Loxodonta africana and the illegal trade in ivory since 2007, mainly because of the rising demand for ivory in the fast-growing economies of Asia, particularly China and Thailand (UNEP et al. , 2013). Elephant populations in Eastern and that were regarded as secure are now threatened, as a wave of poaching seems to be spreading east and southwards across Africa. the of Elephants (MIKE) programme (CITES, 2004) collects data on elephant poaching and law enforcement from >50 sites across Africa (Burn et al. , Reference Burn, Underwood and Blanc2011). However, this programme depends on the law enforcement authority at each site collecting and reporting the carcass data used to judge the effectiveness of their law enforcement. Aerial surveys can provide both an independent check and an assessment of elephant population trends over a large area. The MIKE standards for aerial surveys of elephant populations (Craig, Reference Craig2012) require the collection of data on both live elephants and elephant carcasses. Douglas-Hamilton & Hillman (Reference Douglas-Hamilton and Hillman1981) were among the first to draw attention to the importance of carcass number as an indication of the trend in a population of live elephants. Later, Douglas-Hamilton & Burrill (Reference Douglas-Hamilton, Burrill, Kayanja and Edroma1991) showed that the proportion of dead elephants was correlated with the percentage change in the number of live elephants during the previous 4 years. Wells (Reference Wells1989) modelled a theoretical elephant population under different mortality regimes. He suggested that temporal patterns in the number of dead elephants (as a proportion of live plus dead elephants) permitted natural mortality alone to be distinguished from mortality from both hunting and natural causes, and for selective hunting to be distinguished from unselective hunting. Here we describe a method that uses a simple population model to reveal the trend in an elephant population by combining survey estimates for live elephants with survey estimates for elephant carcasses.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: 48) at both 20 years and entry had a higher mortality rate than women who were underweight/healthy weight at both points. ConclusionsWomen who self-reported overweight and obesity at 20 years had a shorter life expectancy in this cohort of women attending breast cancer screening. Weight gain from 20 years was common in this group. Girls and women should be supported to maintain a healthy weight throughout the lifespan to help increase life expectancy. Trial registration number NCT04359420, retrospectively registered 24/04/2020. reports BackgroundOverweight (body mass index [BMI] 25–29. 9 kg/m2), obesity (BMI ≥ 30 kg/m2) [1] and weight gain increase the risk of multiple diseases in women, including type 2 diabetes, cardiovascular disease (CVD), postmenopausal breast cancer (BC) and 12 other types of cancer [2,3,4]. These diseases all increase risk of mortality [5]. Rates of overweight and obesity for women in England have risen over the past 25 years; currently 60% are overweight including 29% with obesity [6]. BC is the most common cancer in women worldwide [7], and the second highest cause of cancer mortality in UK women [8]. Both the and the for state that weight gain during adulthood, and excess weight throughout adulthood increases risk of postmenopausal BC [7]. Conversely, excess weight between 18 and 30 years is associated with a reduced risk of both pre- and postmenopausal BC [7, 9]. One concern is that the potential benefits of early obesity on BC risk may be interpreted as a positive reinforcement of excess weight amongst younger women. Some studies have shown that higher weight in early adulthood is associated with an increase in all-cause mortality in women [10,11,12]. Using data from the of Screening () study, which recruited women from the in England, we have already shown the association of higher young adulthood weight with increased BC risk. We wished to look at the wider implications of early adulthood weight and weight change within this population of women attending breast screening in the UK. The primary aim of this study was to use data from the cohort to assess all-cause mortality by BMI at 20 years and BMI change between 20 years and entry. We hypothesized that increased BMI at 20 years, and increased weight gain during adulthood would be associated with increased all-cause mortality.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 29 Reference Voon, Irvine and Derbyshire 30 In the task, subjects held down a space bar while performing a serial reaction time task in which they released the space bar to touch the square on the touch screen in which a target appeared. The main outcome was premature responses prior to target onset. In contrast to the BED findings, the same study demonstrated enhanced waiting impulsivity across multiple disorders of substance addiction (abstinent methamphetamine, alcohol-dependent, and cannabis users, and current smokers) and binge drinkers. This study suggests that waiting impulsivity, unlike that observed in disorders of addiction, is not impaired in obese subjects with or without BED. However, in this study, the degree of obesity was mild to moderate, and the task was not tested in the context of food cues or premature responding in BED, both of which may influence outcomes. In a study on reflection impulsivity, which assesses the amount of evidence accumulated prior to a decision, there were no differences between either BED or non-BED obese subjects and healthy volunteers tested using the Task. Reference Mole, Irvine and Worbe 17 The information sampling task involves probabilistic inference, in which subjects are shown 25 squares and must use the accumulated evidence (sequential opening of the square color) to decide whether the squares are predominantly blue or pink. In the Stroop word-color interference task, subjects must report the color in which the word is printed rather than the meaning of the word itself. The task is a complex task that assesses multiple elements, including the capacity to inhibit responding to a conflicting prepotent response, assess conflict, and shift responding. Studies investigating Stroop word-color interference (ie, to non-food related stimuli) report no differences between BED and non-BED obese subjects, suggesting that there is not a fundamental impairment in cognitive control of conflict at least as measured using the Stroop. Reference Duchesne, Mattos and Appolinario 31 Reference Galioto, Spitznagel and Strain 32 In a functional MRI study using the Stroop word-color task, BED subjects had lower activity in regions implicated in self-control, including the ventromedial prefrontal cortex, inferior gyrus, and insula, compared to non-BED obese controls, although no behavioral differences were observed.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: A previous model of an elephant population (Dunham, Reference Dunham2008) is extended, firstly by varying the annual mortality rate in the model to reflect the observed variation in the number of fresh or recent carcasses of elephants, and secondly by mimicking the observed variations in both the number of live elephants and the number of old or very old carcasses. We illustrate the method using long-term aerial survey data for the savannah elephant population in the Reserve in northern Mozambique. population is the largest elephant population in Mozambique and the only one that has been surveyed regularly in recent years. The trend in the estimated number of live elephants in the Reserve has not been clear (Craig, Reference Craig2011), however, with the sample survey estimates suggesting that the number of live elephants increased from c. 12,000 during 2006 to c. 20,000 during 2009, before declining to c. 12,000 during 2011 (Table 1). Real changes of this magnitude over just a few years are unlikely. However, it is not unusual for the trend in population number to be unclear, especially if the population estimates are derived from a relatively small number of sample surveys. We determine the likely trend in the Niassa elephant population by using a model that mimics both the number of live elephants and the number of carcasses. In the process, our analysis reveals the recent impact of illegal hunting on the elephant population. Table 1 Summary of the results of aerial sample surveys of elephants Loxodonta africana and elephant carcasses in Reserve in northern Mozambique (Fig. 1). The carcasses are categorized according to age, as described in the Methods. Study area Reserve (c. 42,000 km2) is in northernmost Mozambique, covering part of Province and nearly one-third of (Fig. 1). It is the country's largest conservation area and the third largest protected area in Africa, and has the highest concentration of wildlife in Mozambique. Tanzania's Reserve (c. 50,000 km2) lies 160 km north of the Rovuma River, which forms the international border as well as the northern border of Reserve. Approximately 9,000 km2 of communal land in southern Tanzania, lying between the Niassa and Selous reserves, is designated the Selous–(Baldus & Hahn, and Hahn2009). Niassa has a tropical climate, with mean monthly temperatures of c.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: 18, 95% CI: 1. 09–1. 27; HRBecoming underweight = 1. 35, 95% CI: 1. 25–1. 46) and cancer death (HROverweight to normal = 1. 20, 95% CI: 1. 04–1. 39; HRBecoming underweight = 1. 44, 95% CI: 1. 24–1. 67), while stable overweight could increase the risk of total death (HRStable overweight = 1. 11, 95% CI: 1. 05–1. 17) and death from stroke (HRStable overweight = 1. 44, 95% CI: 1. 33–1. 56). Interaction effects were observed between age and weight change on cancer mortality, as well as between baseline BMI and weight change on all-cause, heart disease, and stroke mortality (all Pinteraction <0. 01). Conclusions: Weight loss was associated with an increased risk of all-cause, cancer, and heart disease mortality, whereas excessive weight gain and stable overweight were associated with a higher risk of stroke mortality. Efforts of weight management should be taken to improve health status. Trial registration: NCT00342654. weight is one of the markers of nutritional status. [1] Most of the current studies usually use body mass index (BMI), which is defined as the weight (kg) divided by the square of the height (m2), to assess obesity or low body weight. The association between body weight or BMI and the risk of common chronic diseases has been widely reported. [2–5] Multiple disease states, such as cancer and cardiovascular disease, are associated with weight extremes and unexpected weight changes. [6] Most of the current studies confirmed the J-shaped or U-shaped correlation between BMI and the risk of mortality. [7,8] For example, obesity was confirmed to be related to metabolic and cardiovascular risks,[9] while some studies indicated that mortality in the elderly and chronic disease populations was consistently associated with a lower BMI. [10,11] However, body weight changes continuously throughout a lifetime. Many prospective studies only conducted one-time measurements of weight or BMI, and whether the dynamic weight change is an independent risk factor for cancer, stroke, cardiovascular diseases, or other chronic diseases remains controversial.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Impulsivity and compulsivity are believed to be overlapping constructs that might sit at opposite ends of a spectrum: for example, models of addiction posit that impulsivity transitions to compulsivity over the course of addictionReference Dalley, Everitt and Robbins 10 and Volkow 35 they also have overlapping processes and neural substrates, and can co-exist within the same disorder. Compulsivity, similar to impulsivity, also consists of heterogeneous subtypes with discrete but overlapping neural substrates between subtypes and can be either simple or complex. On a simple level, flexibility includes stereotypies, perseveration or impaired switching. On a more complex level, subtypes can include attentional set shifting, reversal, habit, or exploration behaviors as reviewed in the following sections. Set shifting Set shifting assesses a higher order capacity to shift between differing abstract rules or sets. There are several tasks that measure set shifting. In the Sorting Task, subjects must match cards to 1 of 4 cards, which differ by specific dimensions (color, shape, or number) based on specific rules that change over time. In the Test (TMT), Trail B, which tests the capacity to alternate between numbers and letters, subjects draw must draw a line to connect a series of numbers and letters in order. A meta-analysis investigating set shifting across multiple task types in 3 different eating disorder populations (BED, anorexia nervosa, and bulimia nervosa) identified impaired set shifting with a small to moderate effect size across all 3 populations (BED effect size: g=−0. 53). and Friederich 36 A moderate effect size was shown in studies of obesity (g=−0. 61) but not in overweight studies (g=−0. 07). The meta-analysis included only 2 BED studies with a total of 53 BED subjects. Further analysis of the 2 studies and other recently published studies suggests there may be differences between BED and obesity as a function of BMI. In one study with mild obesity (BMI 31–32) assessing the TMT, Trail B, processing time was impaired in BED compared to non-BED obese subjects.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: Data for 2000–2011 were provided by the MODIS burnt area product (no MODIS data are available for 1998). The percentage of area burnt was also recorded during aerial surveys of wildlife during 2002–2009. Blank cells indicate the absence of data. of increased mortality of elephants Increased mortality of African elephants and a subsequent population die-off often follow severe drought, as observed, for example, in Tsavo (Kenya) during 1970–1971 (Corfield, Reference Corfield1973). However, annual rainfall in Niassa was average or above-average after 2006 (Table 2), which suggests that the observed increase in mortality during that period was not drought-related. We considered the possibility that interannual variation in the percentage of the Reserve that was burnt influenced the visibility of elephant carcasses to aerial observers, but the increase in the number of carcasses recorded during 2011 could not be explained by an increase in the proportion of the Reserve that was burnt (Table 3). We believe that there is no natural explanation for the increased mortality observed after the 2006 survey but that it resulted from illegal hunting. Hence, it is likely that the additional 1,901 elephants that the models suggest died during 2007–2011 (including the additional 1,010 that died during 2011) were poached. The 2011 figure is equivalent to a mean of 2. 8 elephants poached daily. Our estimate of 1,010 elephants poached during 2011 is much greater than the number of poached elephants (76) found by field staff and reported to the MIKE programme that year (CITES, 2012). Population model Our study is the first to model simultaneously the numbers of live and dead elephants and to match the modelled trends to survey estimates of elephant and carcass numbers. Application of this approach was facilitated by the consistency between years in survey design, execution and personnel during the Niassa survey programme. The importance of this approach is revealed by the model that mimicked the trend in the number of live elephants only. Although the fit between the modelled and observed elephant numbers (Fig. 4a) was better than the fit produced by the model that mimicked trends in both elephant and carcass numbers (Fig.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: In the Health Center-Study, both weight loss and weight gain of ≥5 kg were associated with an increased risk of all-cause mortality. [25] In the Action to Risk in Diabetes study, researchers observed an asymmetric V-shaped relationship between BMI change and all-cause mortality in patients with type 2 diabetes mellitus. [26] In our study, we reached a similar result when using the 5-year weight change during mid-life as the exposure. However, a decreased risk of cancer mortality was observed among subjects with weight gain ≥5 kg, which was inconsistent with previous studies. Jia et al[27] explored the association of adult weight gain with common health outcomes among 35,989 men and 48,377 women aged 40–59 years. They found that per 5 kg weight gain was associated with a 6% higher risk of cancer mortality in women (HR = 1. 06, 95% CI: 1. 02–1. 10). In the Study, researchers measured the weight status among 3850 adults 3 to 5 times during 14 years, and the results showed that weight gaining ≥0. 45 kg/year over 14 years increased cancer risk by 38% (95% CI: 1. 09–1. 76), compared with maintaining stable weight. [28] A previous review concluded that weight gain or being overweight could increase risk of 13 common cancers, including esophageal adenocarcinoma, cancers of the gastric cardia, colon and rectum, liver, and gallbladder. [29] However, Nicholson et al[30] used cancer registry linked electronic health records from the UK’s to evaluate the association between weight loss and cancer risk, and the results showed that the probability of cancer was initially much higher in patients with unexpected weight loss. Previous research regarding the relationship between body weight status and cancer risk is inconsistent. In the study of Jia et al,[27] obesity-related cancer (such as colorectum cancer and postmenopausal breast cancer) accounted for 53% of all cancer deaths in women and 48% in men, while almost all cancer types included in the Study were obesity-related cancers. [28] However, the distribution of obesity-related cancers in different populations may lead to inconsistent associations between weight change and risk of cancer mortality.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Svaldi, Brand and Tuschen-Caffier 24 In another study comparing moderate obesity (BMI 36) using the Wisconsin card sorting task, perseveration errors and the failure to maintain set were both more impaired in BED compared to non-BED obese controls but not TMT, Trail B. Reference Duchesne, Mattos and Appolinario 31 In contrast, in a recent study with high BMI (BMI 45), no differences were observed between BED and non-BED obese controls in Trail B. Reference Galioto, Spitznagel and Strain 32 A study comparing BED (BMI 35) and anorexia nervosa with healthy controls showed that BED was associated with greater set shifting impairments compared to anorexia nervosa as measured during TMT and failure to maintain set in the Wisconsin card sorting task. Reference Aloi, Rania and Caroleo 23 Thus, although the literature is limited, those with BED appear to be impaired in set shifting with greater impairments relative to non-BED obese controls when BMI is low but possibly with similar impairments when BMI is high. Goal-directed, habitual, and perseverative choices Goal-directed and habitual behaviors have been examined in BED using the Two-step task which assesses whether individuals make choices based on the likely affective outcomes (model-based) or based on previously reinforced choices (model-free). Reference Daw, Gershman, Seymour, Dayan and Dolan 37 In this task, subjects choose between 1 of 2 choices, which then leads with fixed probability to 1 of 2 states; selection of the choice at the second stage then leads to a probabilistic reward. Using this task to examine the balance between goal-directed behavior and habit formation, BED compared to non-BED obese subjects had impairment in model-based, goal-directed behavior with a shift toward model-free habitual behaviors. Reference Voon, Derbyshire and Ruck 38 Higher binge eating scores correlated positively with the shift toward habit formation. These findings were similar to other disorders, including methamphetamine dependence and obsessive compulsive disorder, suggesting similarities linked by compulsive behaviors. In healthy controls, greater model-based behaviors were associated with greater volumes of the medial orbitofrontal cortex and caudate.

Output: pass


Input: Claim: Poaching poses a major threat to endangered species like elephants. [SEP] Text: These factors combine to fuel the illegal ivory trade (van der Westhuizen, Reference van der Westhuizen2011). Poachers focus on big trophy bulls (Kambako Safaris, pers. comm. ), the loss of which affects the viability of the safari industry and thus the management budget for the Reserve. Management authorities in Niassa must deal with a district-driven rural development agenda on one hand and a conservation agenda on the other. The people living within the Reserve see little value in elephants and thus passively encourage poaching, which brings benefits through income, meat and the removal of potential human–elephant conflict. Reversing this attitude requires the conservation authorities to adopt strategies that give greater benefits to local communities from wildlife, and introduce livelihood strategies that stem vegetation clearance for the expansion of agriculture. thank Anabela Rodrigues, former Director of SGDRN, for providing access to the Reserve aerial survey and law enforcement databases. This analysis is based on the findings of surveys conducted by under contract to SGDRN. Those surveys were funded by USAID, the U. S. Fish and Wildlife Service, and Fauna & Flora International. We also thank the safari operators and SGDRN field staff who provided observations on carcass decomposition. commented on drafts of this 4165. 29. 3. . 46. 1. A report to the 62nd meeting of the of CITES. SC62 Inf. 1. . 368. CrossRef2006. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2009. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2011. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2. 0. . 2002. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 2004. Sociedade para a Gestão e Desenvolvimento da Reserva do Niassa, Maputo, Mozambique. 105. of Scientific Unions, Paris, France. 129. Centre for Africa, Addis Ababa, Ethiopia. 48. 108. Http://winfonet. alaska.

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: 7 10 31 32 33Our findings agree with those of a recent meta-analysis, including about 30 million participants, that showed that overweight and obesity are associated with increased risk of all cause mortality, with the nadir of the curve observed at BMI 23-24 among those who had never smoked, 22-23 among healthy people who had never smoked, and 20-22 in studies with a follow-up over 20 years. 34 In our study, the nadir of the curve was observed at BMI 18. 5-22. 4 among people who had never smoked and a follow-up period up to 32 years. Of note, in a recent study conducted among three Danish cohorts, the BMI associated with the lowest all cause mortality increased by 3. 3 units from cohorts enrolled from 1976-78 to 2003-13. 35 The average duration of follow-up for the 2003-13 cohort, however, was only 4. 6 years, and thus the shift to higher BMI associated with the lowest mortality in this cohort is possibly because of reverse causation bias (that is, individuals with pre-existing or preclinical diseases have increased mortality but lower BMI because of weight loss). It should be noted that these studies, unlike ours, did not take into account diet and lifestyle factors. Potential mechanismsBMI is a crude but practical and inexpensive tool to measure adiposity in large population studies. 23 36 It does not, however, measure the ratio of lean to fat or the distribution of fat and, most importantly, the relative contribution of lifestyle and other metabolic factors on the risk of developing a chronic disease and dying prematurely. In this study, we showed that in each of the four categories of BMI (18. 5-22. 4, 22. 5-24. 9, 25-29. 9, ≥30), men and women with healthy lifestyles had significantly lower cardiovascular disease, cancer, and total mortality. Interestingly, even within the obese category, individuals who did not smoke, ate healthier diets, drank a moderate quantity of alcohol, and exercised regularly had a much lower risk of mortality than those who had none of above low risk lifestyle factors. The mechanisms responsible for the protective effects of healthy lifestyles in these individuals are not completely known but probably encompass a series of metabolic and molecular alterations induced by exercise training, healthier diets rich in vitamins and phytochemicals, and avoidance of smoking.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Reference Ziauddeen, Chamberlain and Nathan 45 The same MOR drug also decreased putaminal and pallidal activity and motivational responding (grip force task) specifically to viewing high-calorie foods. Although the drug did not increase subjective liking for passively viewed food images, it increased liking for the high-calorie food images in the grip force task, suggesting a potential relationship between liking and wanting related to motivational processes. Reference Cambridge, Ziauddeen and Nathan 46 Although motivation and liking correlated prior to drug administration and in the placebo group, this relationship was lost following mu-opioid antagonism. The MOR antagonist also showed a selective decrease in attentional bias to food cues as measured using the visual task. Reference Chamberlain, Mogg and Bradley 47 MOR antagonism had a specific effect on later inhibition processes rather than on the earlier facilitation process of the dot probe. There was no effect on a Stroop food-cue task, working memory, or attention. The lack of difference in the Stroop food-cue task but not the dot probe task may reflect the complexity of the Stroop task, as it involves enhanced processing, inhibition, conflict, and shifting. A general mechanism of a decrease in motivational responding to food cues might suggest that both the dot probe and Stroop food-cue tasks might be similarly affected; alternatively, MOR antagonism might have a specific influence by improving inhibitory mechanisms to food cues. Thus, MOR antagonism appears to play a role in (i) decreasing motivational responding to highly salient food cues, and may thus secondarily improve inhibitory processes toward these cues; (ii) a complex relationship with hedonic response by having no effect to passive viewing of highly salient food cues, increasing hedonic ratings to highly salient food cues for which effort or motivation is expended, and decreasing subjective hedonic ratings to consummation of sweetened foods thus the influence of MOR on hedonic responses is dissociable as a function of motivation (passive versus the object of effort) and stage (e. g. during anticipation compared to consummatory stage); and (iii) improving inhibitory mechanisms to food cues. The role of the MOR in anticipatory motivational responding to hedonic food cues is extensively discussed in this series. The following briefly discusses the role of the MOR in impulsivity.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: in ecology and wildlife biology remains crucial for increasing our knowledge and improving species management and conservation in the midst of the current biodiversity crisis. However, obtaining information on population status often involves invasive sampling of a certain number of individual animals. Marking and sampling practices include taking blood and tissue samples, toe-clipping of amphibians and rodents, or using implants and radio-transmitters – techniques that can negatively affect the animal. Wildlife research may then result in a fundamental conflict between individual animal welfare and the welfare of the population or ecosystem, which could be significantly reduced if non-invasive research practices were more broadly implemented. Implementation of non-invasive methods could be guided by the so-called 3Rs principles for animal research (replace, reduce, refine), which were proposed by Russell and Burch 60 years ago and have become a part of many animal protection legislations worldwide. However, the process of incorporating the 3Rs principles into wildlife research has been unfortunately rather slow and their importance overlooked. In order to help alleviate this situation, here I provide an overview of the most common practices in wildlife research, discuss their potential impact on animal welfare, and present available non-invasive alternatives. Ecosystems worldwide are currently experiencing a dramatic species extinction process, which has been largely attributed to human activities (Harrop 2011, Ceballos et al. 2015). Recognizing the critical situation, several international conventions have been implemented with the aim to halt the biodiversity crisis and support conservation measures (e. g. Convention on Biological Diversity, on the Conservation of of Wild Animals, on the Conservation of Convention on in of and Flora). These conservation efforts depend on accurate data on species distribution, population size and impact of global changes, and it is therefore necessary to continuously monitor populations of various plant and animal species. In the noble pursuit of knowledge that is important for preserving wildlife populations, scientists can unfortunately inflict distress on animals, because wildlife biodiversity monitoring has traditionally employed some invasive or even destructive techniques (Vucetich and Nelson 2007, Minteer et al. 2014b, Field et al. 2019). Examples of research activities that might influence animal welfare are chasing, capturing, blood and tissue sampling, marking, attachment of data loggers and lethal sampling (Donnelly et al. 1994, Sutherland et al. 2004, Wilson and McMahon 2006, Walker et al. 2010).

Output: corroborate


Input: Claim: All carbohydrates cause weight gain. [SEP] Text: The 5 additional studies (1 prospective and 4 retrospective, including 1 in women only) examined weight changes in virologically suppressed, treatment-experienced persons who switched to or added an INSTI; 4 of 5 found significantly greater weight gain with INSTIs compared to non-INSTIs [7–11]. Data from randomized clinical trials (RCTs) have been summarized recently [12]. Though not designed to compare weight changes, RCTs that reported comparisons of weight substantiate the cohort study findings. Turning to critical questions: lead to weight gain directly or indirectly? Does the exaggerated weight gain with INSTIs increase the risk of metabolic disturbances or cardiovascular events? Does it magnify the likelihood of neurocognitive impairment (since obesity and metabolic syndrome are risk factors)? In other words, is the weight gain a bothersome side effect or something more sinister? Answers remain unclear. Some studies identified specific risk factors for weight gain with INSTIs, including older age, female sex, and black or Hispanic ethnicity [8, 10]. The current Bourgi et al analysis found no difference between sex or race, but numbers of women were small [5]. Pharmacogenetics may predict weight changes with specific ARVs but are not fully understood. Per 1 retrospective investigation, CYPB26 EFV slow-metabolizers gained more weight than others after they switched to an INSTI; however, this finding varied based on racial characteristics and specific INSTI [13]. Why would EFV slow-metabolizers gain more weight after changing to an INSTI? It was suggested that slower EFV metabolism before switching correlates with feeling better after switching and thus consumption of more calories; however, no study to date has controlled for activity level or caloric intake. In addition, generalized weight gain seems to occur after the switch to an INSTI from a variety of preswitch agents, so this explanation seems far from complete [7, 10]. It has also been proposed that perhaps INSTIs lead to exaggerated weight gain due to faster viral load suppression. Perhaps this induces more rapid reduction of HIV-related inflammation and basal energy expenditure [4]? A compelling part of Bourgi et al’s data addresses this question [5]. Viral load reductions between specific INSTIs were not significantly different over the first 12 months, yet weight change differed. At 18 months, viral loads were the same across ART classes, but weight change varied. Thus, viral kinetics do not explain the weight findings.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Morphine, a MOR agonist, increases premature responding or waiting impulsivity in the 5-task and also increases preference for immediate over delayed rewards, with both measures blocked by naloxone, a MOR antagonist. Reference Pattij, Schetters, Janssen, Wiskerke and Schoffelmeer 48 Naloxone by itself does not affect waiting impulsivity or delay discounting. Morphine, but not naloxone, appears to have a baseline-dependent influence on the stop signal task. MOR antagonism, but not kappa-opioid receptor antagonism, has also been shown to selectively remediate the amphetamine-induced impairments in premature responding, but to have no effect on delay discounting. Reference Wiskerke, Schetters and van Es 49 The MOR modulating effect on inhibition appears to be in the nucleus accumbens shell and may interact with the mesolimbic dopaminergic system. Thus, the observation of the improvement by MOR antagonism in the dot probe task to food cues may be related to improvements in anticipatory responding, or a baseline-dependent effect on response inhibition by improving stopping in individuals with impaired stopping abilities. Reference Pattij, Schetters, Janssen, Wiskerke and Schoffelmeer 48 to obesity without BED, impulsivity in BED does not appear to be as critically impaired across multiple domains as observed across disorders of addiction. Whereas drugs of abuse have been shown to enhance impulsivity, the pattern of food intake, or food itself, may be less likely to cause impulsivity. Behavioral inflexibility or compulsivity and attentional bias toward food cues are more prominently impaired in BED. Behavioral regulation appears to be influenced by the context of motivationally salient food cues and the degree of obesity. Deficits in decisional impulsivity, including delay discounting and risk taking under ambiguity, are impaired in obesity irrespective of BED status. Whether these forms of impulsivity are predictive of or a consequence of obesity is not known. However, these findings are influenced by the severity of obesity: compared to non-BED obese subjects, in BED subjects with milder forms of obesity, greater risk seeking under explicit probabilistic risk is observed to monetary rewards, whereas this shifts to risk aversion and greater discounting of delayed rewards in BED subjects with more severe obesity.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: , Geomalacus maculosus) (Morinha et al. 2014), intertidal snails (Nucella spp. ) (Kawai et al. 2004), polyplacophoran molluscs (Ischnochiton spp. ) (Palmer et al. 2008), freshwater pearl mussels Margaritifera margaritifera (Karlsson et al. 2013) and fish (Manta birostris, Oreochromis niloticus) (Kashiwagi et al. 2015, Taslima et al. 2016). In birds, eggshells (Strausberger and Ashley 2001, Egloff et al. 2009, Kjelland and Kraemer 2012, Maia et al. 2017) or feathers (Rudnick et al. 2007, Kjelland and Kraemer 2012, Olah et al. 2016) can be used as a source of DNA. Feathers can be collected opportunistically or through a feather-trap (Maurer et al. 2010). Saliva is also a great source of DNA that can be collected non-invasively by using e. g. baits and porous material (Vargas et al. 2009, Lobo et al. 2015). Additionally, DNA samples can be obtained from mineral lick (Schoenecker et al. 2015), rests of prey (Harms et al. 2015, Wheat et al. 2016) or damaged crop (Saito et al. 2008). Other potential sources of DNA include scent marks (Malherbe et al. 2009), snow footprints (Dalen et al. 2007), urine (Nagai et al. 2014, Nakamura et al. 2017), insect exuviae (Kranzfelder et al. 2016, Nguyen et al. 2017), spider webs (Xu et al. 2015, Blake et al. 2016), antlers (Hoffmann and Griebeler 2013, Kim et al. 2015) or shed skin (Swanson et al. 2006, Horreo et al. 2015). As organisms move through the environment, they also leave some DNA traces behind. This environmental DNA (eDNA) can be used for detection of targeted organisms, and it is particularly useful for detection of invasive (Collins et al. 2013, Hunter et al. 2015) or rare species (Jerde et al. 2011).

Output: corroborate


Input: Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: To this end, we operationalize two quantitative measures of dietary quality using the recent EAT-Lancet commission on Food, Planet, and Health’s dietary guidelines and food availability data from the database [22] to benchmark the “health and sustainability” of country-level diets today—or the degree to which diets can satisfy human nutritional needs while respecting an environmental “safe operating space” for food systems [23]. Then, using output from an agricultural projection model, and building on the results initially developed by [24], we produce future projections of the dietary quality of country-level food availability to 2050 under different scenarios of global economic and demographic trends to: a) explore whether diets become more (or less) healthy and sustainable over time under uncertain socioeconomic futures, and b) explore the effect of traded agricultural products on dietary health and sustainability. Understanding the evolution of dietary qualityUnhealthy diets are one of the largest risk factors driving the global disease burden [25]. As there is no universally agreed-upon notion of what constitutes a healthy diet, there is also no clear agreement on what constitutes best-practice metrics to measure dietary quality from a holistic and global perspective. A variety of approaches exist to measure dietary quality (for a recent overview, see [26], but many of these are not applicable at the global level. The challenge is compounded when looking at food system sustainability, as the measurements of different aspects of human nutrition at the global scale often do not address the goals of dietary health and environmental sustainability in tandem [27–29]. The transition from a food security focus to a food system emphasis in food policy includes the recognition of a need to develop and track quantitative indicators of multiple facets of global food systems functions. In order to ensure that progress is being made towards ambitious system-level goals, consistent and comparable measures are required to understand whether food systems are functioning in a healthy, equitable, and sustainable manner [30, 31]. Consideration of dietary sustainability in assessments of global diets was a major motivating factor of the EAT-report on eating within planetary boundaries [23], and the report provided global dietary guidelines to that effect. The EAT-Lancet report motivated a variety of complementary studies [32], and critical discussions [33, 34] as well as comparisons with existing dietary patterns and guidelines [35].

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Davis, C, Carter, JC. Compulsive overeating as an addiction disorder: a review of theory and evidence. Appetite. 2009; 53(1): 1–8. 8. Ziauddeen, H, Fletcher, PC. Is food addiction a valid and useful concept? Obes Rev. 2013; 14(1): 19–28. 9. . Psychiatric aspects of impulsivity. Psychiatry. 2001; 158(11): 1783–1793. CrossRef10. . Impulsivity, compulsivity, and top-down cognitive control. Neuron. 2011; 69(4): 680–694. CrossRef11. Lipszyc, J, Schachar, R. Inhibitory control and psychopathology: a meta-analysis of studies using the stop signal task. J Soc. 2010; 16(6): 1064–1076. CrossRef12. . Deficits in behavioural inhibition in substance abuse and addiction: a meta-analysis. Depend. 2014; 145: 1–33. 13. . Abnormal brain structure implicated in stimulant drug addiction. Science. 2012; 335(6068): 601–604. 14. der Linden, M. Cognitive deficits in obese persons with and without binge eating disorder: investigation using a mental flexibility task. Appetite. 2011; 57(1): 263–271. 15. . General and food-specific inhibitory deficits in binge eating disorder. Eat Disord. 2014; 47(5): 534–542. 16. Inhibitory control and decision making under risk in bulimia nervosa and binge-eating disorder. Eat Disord. 2013; 46(7): 721–728. 17. Impulsivity in disorders of food and drug misuse. Psychol Med. 2015; 45(4): 771–782. 18. . Timing deficits in attention-deficit/hyperactivity disorder (ADHD): evidence from neurocognitive and neuroimaging studies. Neuropsychologia. 2013; 51(2): 235–266. CrossRef19. . The behavioral- and neuro-economic process of temporal discounting: a candidate behavioral marker of addiction. Neuropharmacology. 2014; 76(Pt B): 518–527. 20. . Immediate pleasures and future consequences: a neuropsychological study of binge eating and obesity. Appetite.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: Controlling invasive species by empowering environmental stakeholders: ecotourism boat operators as potential guardians of wildlife against the invasive American mink Published online by Press: 19 February 2014 Elaine J. FraserDavid W. MacdonaldandShow author details Elaine J. Fraser Affiliation: School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK. David W. Macdonald Affiliation: Research Unit, Department of Zoology, University of : School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK. Xavier Lambin* Affiliation: School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK. * (Corresponding author) E-mail x. lambin@abdn. ac. uk 0. 36 mb) View PDF [Opens in a new window] Save to to Save to & Permissions [Opens in a new window] who have a stake in their environment are more likely to volunteer to assist conservation but they must be empowered to do so. This study explored the possibility of harnessing volunteers in the control of an invasive predator, the American mink Neovison vison, which decimates seabird colonies in coastal west Scotland. A questionnaire was sent to ecotourism boat operators, a group assumed to have an economic interest in wildlife biodiversity and a stake in their environment, to gauge their opinion on lethal control of American mink. The majority (64%) of respondents were concerned about the presence of mink in their area, agreed with control in principle and were willing to become involved in a volunteer capacity. Respondents who would not volunteer but agreed with control (21%) might reconsider if mink had a visible impact on their local wildlife. The minimum level of support people expected was information on where to get, and how to deploy, monitoring and trapping equipment. This study confirms that people with an intrinsic interest in wildlife consider themselves willing to protect their local biodiversity, with only limited resource input, such as an information pack, from external sources. minkcontrolenvironmental stakeholdersinvasive speciesnative species conservationNeovison visonScotlandvolunteer involvement Issue 4 October 2014 10. 1017/S003060531300046X [Opens in a new window] © Fauna & 2014 species are those introduced by human agency and which subsequently spread and cause damage to the ecosystems in which they have been introduced.

Output: corroborate


Input: Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: For upper-middle income countries especially, and low-income countries to a lesser degree, global agricultural trade may exacerbate a dietary double-burden dynamic under some scenarios (SSP2, SSP3, SSP4 for upper-middle income, SSP2, SSP5 for low-income—Tables 4 and 5). While this dynamic does not persist clearly across other income groups, some geographic heterogeneity is observed (Fig 5). This can be most clearly seen in the region, where a “no-trade” diet is expected to continue to outperform actual diets including traded goods in some scenarios. Implications for food trade policies Looking beyond overall diet to dietary components (Fig 6), we can observe that the composition of traded goods over time are not necessarily aligned with improved dietary quality over the course of business-as-usual scenario conditions (SSP2). For example, some regions () might be expected to expand imports of sugars or meats even while the per capita availability of these products continues to be much higher than that recommended by the EAT-Lancet diet. Other regions () see availability of legumes, nuts, and seeds much lower than what would be needed to satisfy the EAT-Lancet diet, at the same time as the import share of these commodities is expected to fall over time. Levels of legumes, nuts, and seeds in diets across regions into the future are generally consistently lower than the EAT-Lancet dietary guidelines, and this is important to consider in tandem with concerns that the production environments necessary to satisfy these levels may exacerbate water stress [34]. Our category-based measurements of dietary health and sustainability nuances the narratives that trade advances malnutrition reduction in certain regions of the world [61] and draws attention to a more heterogenous role of trade in securing healthy and sustainable diets [62–64]. Countries which are expected to not experience dietary benefit from trade on either the overshoot or undershoot side of the equation may actually see dietary benefits from more limited engagement with global agricultural markets, or reformed trade policies that promote nutritional goals [63, 65–69].

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 2010; 54(1): 208–213. 21. . Discounting of various types of rewards by women with and without binge eating disorder: evidence for general rather than specific differences. Psychol Rec. 2011; 61(4): 561–582. 22. Danner, UN, Ouwehand, C, van Haastert, NL, Hornsveld, H, de Ridder, DT. Decision-making impairments in women with binge eating disorder in comparison with obese and normal weight women. Disord Rev. 2012; 20(1): e56–e62. 23. Decision making, central coherence and set-shifting: a comparison between binge eating disorder, anorexia nervosa and healthy controls. BMC Psychiatry. 2015; 15: 6. 24. Svaldi, J, Brand, M, Tuschen-Caffier, B. Decision-making impairments in women with binge eating disorder. Appetite. 2010; 54(1): 84–92. 25. Risk-taking in disorders of natural and drug rewards: neural correlates and effects of probability, valence, and magnitude. Neuropsychopharmacology. 2015; 40(4): 804–812. 26. Compromised sensitivity to monetary reward in current cocaine users: an ERP study. Psychophysiology. 2008; 45(5): 705–713. 27. -Klein, N, et al. Subjective sensitivity to monetary gradients is associated with frontolimbic activation to reward in cocaine abusers. Depend. 2007; 87(2–3): 233–240. 28. . High impulsivity predicts the switch to compulsive cocaine-taking. Science. 2008; 320(5881): 1352–1355. CrossRef29. Voon, V. Models of impulsivity with a focus on waiting impulsivity: translational potential for neuropsychiatric disorders. Rep. 2014; 1(4): 281–288. 30. Measuring “waiting” impulsivity in substance addictions and binge eating disorder in a novel analogue of rodent serial reaction time task. Biol Psychiatry. 2014; 75(2): 148–155. 31. Assessment of executive functions in obese individuals with binge eating disorder. Psiquiatr. 2010; 32(4): 381–388. 32.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: Biological invasions are a major global threat to biodiversity and ecosystem function (Kolar & Lodge, and Lodge2001). Invasive predatory species can have a devastating impact on native species (Simberloff, Reference Simberloff2001) and biodiversity conservation (Macdonald et al. , Reference Macdonald, King, Strachan, Macdonald and Service2007) and there is an increasing awareness of, and necessity for, management to minimize these impacts (Bryce et al. , and Lambin2011). Control of invasive species on a large scale has been attempted using various methods. For example, successful eradication of the coypu Myocastor coypus in Britain was accomplished using salaried trappers who were given bonuses for early completion (Gosling & Baker, and Baker1989). Eradications of introduced rats and cats on islands, using poison baiting, have proven successful (Howald et al. , and Tershy2010; Ratcliffe et al. , and White2010) but the use of poison for controlling carnivores in populated areas of Europe is unlikely to be acceptable to the public (Genovesi, Reference Genovesi2005). Nevertheless, public support can be gained for control efforts, particularly when humans are viewed as responsible for the invasion (Selge et al. , Reference Selge, Fischer and van der Wal2011). Attempts to control the American mink Neovison vison in Europe have been conducted using dedicated salaried trappers, paying a bounty to hunters, and through the use of volunteers who have an interest in removing mink (Bonesi & Palazon, and Palazon2007; Bryce et al. , and Lambin2011; Heritage, 2012). Involving unpaid volunteers in collating information on the distribution (e. g. Delaney et al. , Reference Delaney, Sperling, Adams and Leung2008; Dickinson et al. , Reference Dickinson, Zuckerberg and Bonter2010; Gallo & Waitt, and Waitt2011) and control of invasive species on a large scale is a feasible alternative to the costly use of professional staff (Tidwell & Brunson, and Brunson2008; Bryce et al. , and Lambin2011; Macdonald & Burnham, and Burnham2011). People willing to participate in invasive species management often have a stake in the environment (Tidwell & Brunson, and Brunson2008; Selge et al.

Output: corroborate


Input: Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: For instance, the significant dietary overshoot in the Sub-region is mostly associated with a large portion of dietary energy coming from roots and tuberous foods—for which the EAT-Lancet dietary guidelines set a relatively low maximum threshold (100 g/cap/day) citing high glycemic load associated with the consumption of tubers and starchy vegetables [23, 74]. Processing of grains into highly refined foods such as white bread makes grain-derived foods comparable to tubers in terms of glycemic load [75], and because our study does not consider food preparation method, it is almost certainly the case that the health benefits from grains versus tubers are skewed here in favor of grains. Future avenues for study into cross-country trends in dietary health using EAT-Lancet should be sensitive to the role of food processing in driving overshoot or undershoot of different category-based dietary thresholds. ConclusionThe world today faces challenges on two distinct fronts of dietary health and sustainability—with countries both undershooting (falling short) and overshooting (exceeding) many dietary health and sustainability goals and limits. The dietary metrics constructed in this paper present a way to track progress towards, or movement away from, “ideal” dietary and sustainability states, and the results make clear that managing the balance between improving dietary undershoot and limiting dietary overshoot will continue to be a major challenge across countries and regions globally in the future. The results further show that trade, though expected to provide benefits for dietary health and sustainability to many countries, is also projected to exacerbate dietary harms in others under business-as-usual trade conditions. We find this to be true to varying degrees when accounting for potential socioeconomic uncertainty under the SSP framework, evidencing that socioeconomic patterns of development will have implications for both the impact of trade on dietary outcomes, and dietary outcomes themselves. In general, we find that scenarios with higher growth conditions imply far greater dietary overshoot potential across a number of regions (Fig 3) while sometimes making only very limited progress towards reducing dietary undershoot. Under such scenarios, new avenues for managing food demand and the dietary environment may need to be explored given the dearth of demand-side policy approaches combining human and planetary health concerns [76].

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Cognitive function in morbidly obese individuals with and without binge eating disorder. Compr Psychiatry. 2012; 53(5): 490–495. 33. Divergent neural substrates of inhibitory control in binge eating disorder relative to other manifestations of obesity. Obesity. 2013; 21(2): 367–377. 34. . Inhibitory control in bulimic-type eating disorders: a systematic review and meta-analysis. PLoS One. 2013; 8(12): e83412. 35. . Neurocircuitry of addiction. Neuropsychopharmacology. 2010; 35(1): 217–238. CrossRef36. . Set-shifting ability across the spectrum of eating disorders and in overweight and obesity: a systematic review and meta-analysis. Psychol Med. 2014; 44(16): 3365–3385. 37. . Model-based influences on humans’ choices and striatal prediction errors. Neuron. 2011; 69(6): 1204–1215. 38. Disorders of compulsivity: a common bias towards learning habits. Mol Psychiatry. 2015; 20(3): 345–352. CrossRef39. -Terpstra, J, Moreno, F. Prefrontal and striatal dopaminergic genes predict individual differences in exploration and exploitation. Nat Neurosci. 2009; 12(8): 1062–1068. CrossRef40. . Biases in the explore-exploit tradeoff in addictions: the role of avoidance of uncertainty. Neuropsychopharmacology. In press. DOI: 10. 1038/n208. 41. Svaldi, J, Tuschen-. Information processing of food pictures in binge eating disorder. Appetite. 2010; 55(3): 685–694. CrossRef42. Impulsivity in binge eating disorder: food cues elicit increased reward responses and disinhibition. PLoS One. 2013; 8(10): e76542. 43. -. Cognitive interference and a food-related memory bias in binge eating disorder. Appetite. 2014; 72: 28–36. 44. Svaldi, J, Bender, C, Tuschen-Caffier, B. Explicit memory bias for positively valenced body-related cues in women with binge eating disorder. J Exp Psychiatry. 2010; 41(3): 251–257. CrossRef45.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: , Reference Selge, Fischer and van der Wal2011), making it possible to connect with the motivations of such stakeholders to promote voluntary participation in the management of invasive species. Success with volunteer-based invasive species control was demonstrated by Bryce et al. (and Lambin2011) for their mink control project. This project aimed to eradicate breeding mink from an area of north-east Scotland, to allow recovery of native species such as the water vole Arvicola amphibius. It involved a wide range of volunteers who had convergent economic and general interests in protecting vulnerable native species. The project has now expanded from its original coverage (Area 1, Fig. 1) and aims to replicate this success across a larger area of mainland Scotland (Area 2, Fig. 1). Fig. 1 Scotland, showing geographical locations mentioned in the text. Areas A–E show regional boundaries used to describe locations of west coast tour operators (A, North Highland; B, Skye and Lochalsh; C, and Lochaber; D, Oban and Mull; E, and Kintyre). The gradation of shading from south to north (areas E to A) represents the pattern of colonization by mink on the west coast. Other mink project areas are represented by numbers (1, original mink project area; 2, current mink project area; 3, project area). The locations of all businesses contacted for the questionnaire are indicated by black dots, where the size represents number of businesses at each location (small = 1, medium = 2, large = 3). Bar graphs show the number of tour boat operators who were contacted (Cont. ) and responded (Resp. ) and of those respondents, the number who were willing to volunteer (black section of bar), in each area (letters correspond as above). The invasive American mink was introduced to many locations outside its native range, including the UK, for fur farming (Cuthbert, Reference Cuthbert1973). Feral populations have established from escaped and released mink. Mink are opportunistic predators that feed on a range of native species including small mammals, fish, frogs, crustaceans, and birds and their eggs (Dunstone, Reference Dunstone1993; Macdonald & Harrington, and Harrington2003).

Output: corroborate


Input: Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Nutrition and health outcomes are influenced by multiple factors, which makes it difficult to tease out and identify relevant entry points to bring a positive change or solution [25]. At the individual level, for example, the nutritional status is influenced by the consumption of single food components or other biological, socioeconomic, and psychological determinants [25]. From the environmental aspect, when developing FSIs to improve nu-trition and health outcomes, it is crucial to consider solutions that will not cause environmental degradation [24]. Moreover, for the food system as a whole, a multidisciplinary team and different actors from the private, public, and non-governmental sector must work toward a coherent objective and align priorities to design an FSI [25]. This can be challenging as all stakeholders have different personal and institutional interests. Nowadays, innovation must adopt a holistic approach that will allow the solution of linear cause–effect interactions as well as more-complex and systemic interactions that consider the environment and socioeconomic context. Second, food systems are dynamic, and nutritional and public health issues are changing at a rapid pace. Under these conditions, the rapid advancement of technology may not be sufficient to address these challenges, as providing robust evidence-based solutions from the development stage to validation and scale-up is time consuming [8, 26]. For example, in the past decade, plant-based products have been proposed as a sustainable and healthy innovation compared to livestock [27, 28]. Although the concept is not new and was already introduced in the 1960s [29], there are still evidence gaps around their environmental, nutritional, health impact, and safety characteristics. Another example relates to lab-grown meat that brings a potential solution to decrease livestock production. Cell-culture-related challenges around large-scale production, food safety standards, and expensive production inputs are still under discussion [30]. Lastly, complexity and dynamism within the food system can generate feedback loops and synergies, which can also influence the outcome of an FSI. Trade-offs among different components of the food system should, therefore, be considered. Indeed, trade-offs between food safety, affordability, and sustainable innovations toward food security and positive nutrition outcomes must be prior-itized, taking into account the local context, especially in LMICs [10]. In addition, the environmental and nutritional impact of food remains a controversial topic within food systems [31].

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Effects of the mu-opioid receptor antagonist GSK1521498 on hedonic and consummatory eating behaviour: a proof of mechanism study in binge-eating obese subjects. Mol Psychiatry. 2013; 18(12): 1287–1293. 46. Neural and behavioral effects of a novel mu opioid receptor antagonist in binge-eating obese people. Biol Psychiatry. 2013; 73(9): 887–894. 47. Effects of mu opioid receptor antagonism on cognition in obese binge-eating individuals. Psychopharmacology (Berl). 2012; 224(4): 501–509. 48. . Acute effects of morphine on distinct forms of impulsive behavior in rats. Psychopharmacology (Berl). 2009; 205(3): 489–502. 49. Wiskerke, J, Schetters, D, van Es, IE, et al. mu-Opioid receptors in the nucleus accumbens shell region mediate the effects of amphetamine on inhibitory control but not impulsive choice. J Neurosci. 2011; 31(1): 262–272.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: They are highly dispersive and inhabit coastal and inland freshwater habitats, the former of which is assumed to be more productive and hence to accommodate denser mink populations (Dunstone, Reference Dunstone1993; Clode et al. , Reference Clode, Haliwell and Macdonald1995; Bodey et al. , Reference Bodey, Bearhop, Roy, Newton and McDonald2010). The detrimental impact of mink on native birds in the invaded range worldwide is well documented (e. g. Craik, Reference Craik1997; Nordström et al. , Reference Nordström, Högmander, Laine, Nummelin, Laanetu and Korpimäki2003; Peris et al. , Reference Peris, Sanguinetti and Pescador2009) and can involve direct killing, desertion of colonies, or breeding failures as a result of disturbance during incubation (Burness & Morris, and Morris1993; Clode & Macdonald, and Macdonald2002). Coastal areas are worst affected, exemplified by studies showing poor breeding success and loss or relocation of many seabird colonies (Clode & Macdonald, and Macdonald2002; Nordström & Korpimäki, Reference Nordström and Korpimäki2004; Ratcliffe et al. , Reference Ratcliffe, Craik, Helyar, Roy and Scott2008). However, mink control has proven successful in reversing this damage, resulting in increases in diversity and breeding densities of seabirds (Nordström et al. , Reference Nordström, Högmander, Laine, Nummelin, Laanetu and Korpimäki2003; Ratcliffe et al. , Reference Ratcliffe, Craik, Helyar, Roy and Scott2008) and re-establishment of colonies previously decimated by mink predation (Ratcliffe et al. , Reference Ratcliffe, Craik, Helyar, Roy and Scott2008). mink are present in all but far northern areas (2012; NBN Gateway, 2012). The north-west coast has been the most recently invaded, leading to growing concern about the impact of mink on wildlife, as well as the potential for further detriment if the far north of the country is colonized.

Output: corroborate


Input: Claim: A vegan diet is automatically healthier than other diets. [SEP] Text: Pattern analysis of vegan eating reveals healthy and unhealthy patterns within the vegan diet Published online by Press: 11 May 2021 GallagherandLane [Opens in a new window] Show author details Gallagher Affiliation: for Sport and Exercise Sciences, I. M. 17 6: for Sport and Exercise Sciences, I. M. 17 6* Affiliation: for Sport and Exercise Sciences, I. M. 17 6BD, UK * *Corresponding author: Email k. e. lane@ljmu. ac. uk 0. 47 mb) View PDF [Opens in a new window] Save to to Save to & Permissions [Opens in a new window] Abstract Objective:This study aimed to identify the types of foods that constitute a vegan diet and establish patterns within the diet. Dietary pattern analysis, a key instrument for exploring the correlation between health and disease, was used to identify patterns within the vegan diet. Design:A modified version of the EPIC-Norfolk FFQ was created and validated to include vegan foods and launched on social media. Setting:UK participants, recruited online. Participants:A convenience sample of 129 vegans voluntarily completed the FFQ. Collected data were converted to reflect weekly consumption to enable factor and cluster analyses. Results:Factor analysis identified four distinct dietary patterns including: (1) convenience (22 %); (2) health conscious (12 %); (3) unhealthy (9 %) and (4) traditional vegan (7 %). Whilst two healthy patterns were defined, the convenience pattern was the most identifiable pattern with a prominence of vegan convenience meals and snacks, vegan sweets and desserts, sauces, condiments and fats. Cluster analysis identified three clusters, cluster 1 ‘convenience’ (26·8 %), cluster 2 ‘traditional’ (22 %) and cluster 3 ‘health conscious’ (51·2 %). Clusters 1 and 2 consisted of an array of ultraprocessed vegan food items. Together, both clusters represent almost half of the participants and yielding similar results to the predominant dietary pattern, strengthens the factor analysis. Conclusions:These novel results highlight the need for further dietary pattern studies with full nutrition and blood metabolite analysis in larger samples of vegans to enhance and ratify these results. pattern analysisVegan dietConvenienceTraditionalHealthyUltraprocessed foods Issue 5 May 2022 10.

Output: contrast


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: New York: HarperOne; 2012. 20. Chapman GB. Time discounting of health outcomes. In: eds. Time and Decision: Economic and on Intertemporal Choice. New York: Foundation; 2003. p 395–418. 21. Croskerry P. The importance of cognitive errors in diagnosis and strategies to minimize them. Acad Med. 2003;78(8):775–80. CrossrefPubMedWeb of Science22. Reporting guidelines for survey research: an analysis of published guidance and reporting practices. PLoS Med. 2011;8(8):e1001069. CrossrefWeb of Science23. . of Reporting (CORE) index identifies important deficiencies in observational study conference abstracts. J Clin Epidemiol. 2008;61(12):1241–9. Crossref24. Meyrick J. What is good qualitative research? A first step towards a comprehensive approach to judging rigour/quality. J Health Psychol. 2006;11(5):799–808. CrossrefPubMedWeb of Science25. . The influence of positive affect on clinical problem solving. Making. 1991;11(3):221–7. CrossrefPubMedWeb of Science26. Myers RE. Decision counseling in cancer prevention and control. Health Psychol. 2005;24(suppl 4):S71–7. CrossrefPubMedWeb of Science27. Sharman SJ. Current negative mood encourages changes in end-of-life treatment decisions and is associated with false memories. Cogn Emot. 2011;25(1):132–9. CrossrefPubMedWeb of Science28. . Affect, framing, and persuasion. J Market Res. 2003;40(1):54–64. CrossrefWeb of Science29. Action tendency emotions evoked by memorable breast cancer messages and their association with prevention and detection behaviors. Health Commun. 2010;25(8):737–46. CrossrefPubMedWeb of Science30. Fox CR, Tversky A. Ambiguity aversion and comparative ignorance. In: Kahneman D, Tversky A, eds. Choices, Values, and Frames. New York: 2000. p 528–42. Crossref31. . Attitudes of obstetricians and gynecologists toward hormone replacement therapy. Making. 1998;18(4):406–11. CrossrefPubMedWeb of Science32.

Output: pass


Input: Claim: Invasive species can disrupt local ecosystems and wildlife. [SEP] Text: Most businesses were > 6 years old, with five operating for > 20 years. All but one respondent reported either seeing mink or being aware of the presence of mink in their area. These are all areas where mink have been recorded (Fig. 1). All but two respondents stated that they agreed with the principle of mink control. Fig. 2 Number of ecotourism boat operators contacted (white bars) and number who responded (black bars), according to primary business type (cetacean watching, mixed wildlife watching, scenic tours, sea eagle watching, seal watching and other activities). The most common opinion expressed by respondents in relation to mink affecting business and local wildlife was the loss of ground-nesting birds from offshore islands and/or their failure to breed. spp. were mentioned specifically. Example comments were ‘terns no longer present’, ‘all ground-nesting birds on a local nest site produced zero chicks this year’, ‘adult birds remain but no chicks’, and ‘the declining number of species over the last few years has reduced customer enjoyment, and has been commented upon by them’. This concern was in line with their reports of the most common animals they expect to see on their trips (all 14 tour operators expect to see seals and seabirds). In response to the informative text provided throughout the questionnaire about mink and their control, respondents changed few of their original answers. Assuming that all respondents read the informative text, this suggests they were already well informed. After reading the informative text two respondents raised their level of concern about the presence of mink in their area and two other respondents increased the level of impact they thought mink could have on their business. One person decreased the impact level. When asked who should be responsible for mink control, the general consensus was that it should be shared amongst the suggested groups. These were government organizations, national conservation NGOs, local conservation NGOs and local individuals with a personal interest, with an additional option for other suggestions. Opinions did not change after reading about the various organizations and projects that already operate. Nine respondents would consider becoming involved in mink control. They were all concerned about the presence of mink, thought that mink had a visible or highly visible impact on their local wildlife and reported an impact, or potential impact, on their business. Six of these respondents had trapped mink before (Fig. 3). Fig.

Output: corroborate