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  • Neuroinformatics
  • 2. Zero hunger

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Park, Bo-yong; Hong, Jisu; Park, Hyunjin;

    AbstractObesity is a serious medical condition highly associated with health problems such as diabetes, hypertension, and stroke. Obesity is highly associated with negative emotional states, but the relationship between obesity and emotional states in terms of neuroimaging has not been fully explored. We obtained 196 emotion task functional magnetic resonance imaging (t-fMRI) from the Human Connectome Project database using a sampling scheme similar to a bootstrapping approach. Brain regions were specified by automated anatomical labeling atlas and the brain activity (z-statistics) of each brain region was correlated with body mass index (BMI) values. Regions with significant correlation were identified and the brain activity of the identified regions was correlated with emotion-related clinical scores. Hippocampus, amygdala, and inferior temporal gyrus consistently showed significant correlation between brain activity and BMI and only the brain activity in amygdala consistently showed significant negative correlation with fear-affect score. The brain activity in amygdala derived from t-fMRI might be good neuroimaging biomarker for explaining the relationship between obesity and a negative emotional state.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Europe PubMed Central
    Article . 2017
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Scientific Reports
    Article . 2017 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Scientific Reports
    Article . 2017
    Data sources: DOAJ-Articles
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Europe PubMed Central
      Article . 2017
      Data sources: PubMed Central
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Scientific Reports
      Article . 2017 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Scientific Reports
      Article . 2017
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anna Ratsika; Martin C. Codagnone; Siobhain M. O'Mahony; Catherine Stanton; +1 Authors

    Microbes colonize the human body during the first moments of life and coexist with the host throughout the lifespan. Intestinal microbiota and their metabolites aid in the programming of important bodily systems such as the immune and the central nervous system during critical temporal windows of development, with possible structural and functional implications throughout the lifespan. These critical developmental windows perinatally (during the first 1000 days) are susceptible timepoints for insults that can endure long lasting effects on the microbiota-gut-brain axis. Environmental and parental factors like host genetics, mental health, nutrition, delivery and feeding mode, exposure to antibiotics, immune activation and microbiota composition antenatally, are all factors that are able to modulate the microbiota composition of mother and infant and may thus regulate important bodily functions. Among all these factors, early life nutrition plays a pivotal role in perinatal programming and in the modulation of offspring microbiota from birth throughout lifespan. This review aims to present current data on the impact of early life nutrition and microbiota priming of important bodily systems and all the factors influencing the microbial coexistence with the host during early life development.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Nutrientsarrow_drop_down
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    Nutrients
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Sygma; Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Europe PubMed Central
    Article . 2021
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nutrients
    Article . 2021
    Data sources: DOAJ-Articles
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nutrients
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Nutrientsarrow_drop_down
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      Nutrients
      Article . 2021 . Peer-reviewed
      License: CC BY
      Data sources: Sygma; Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Europe PubMed Central
      Article . 2021
      Data sources: PubMed Central
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nutrients
      Article . 2021
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nutrients
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jacqueline Blissett; Magdalena Chechlacz; Suzanne Higgs; Timothy Barrett; +1 Authors

    Social context, specifically within the family, influences adolescent eating behaviours and thus their health. Little is known about the specific mechanisms underlying the effects of parental feeding practices on eating. We explored relationships between parental feeding practices and adolescent eating habits and brain activity in response to viewing food images. Fifty- seven adolescents (15 with type 2 diabetes mellitus, 21 obese and 21 healthy weight controls) underwent fMRI scanning whilst viewing images of food or matched control images. Participants completed the Kids Child Feeding Questionnaire, the Childrens’ Dutch Eating Behaviour Questionnaire (DEBQ) and took part in an observed meal. Parents completed the Comprehensive Feeding Practices Questionniare and the DEBQ. We were particularly interested in brain activity in response to food cues that was modulated by different feeding and eating styles. Healthy-weight participants increased activation (compared to the other groups) to food in proportion to the level of parental restriction in visual areas of the brain such as right lateral occipital cortex (LOC), right temporal occipital cortex, left occipital fusiform gyrus, left lateral and superior LOC. Adolescents with type 2 diabetes mellitus had higher activation (compared to the other groups) with increased parental restrictive feeding in areas relating to emotional control, attention and decision-making, such as posterior cingulate, precuneus, frontal operculum and right middle frontal gyrus. Participants with type 2 diabetes mellitus also showed higher activation (compared to the other groups) in the left anterior intraparietal sulcus and angular gyrus when they also reported higher self restraint. Parental restriction did not modulate food responses in obese participants, but there was increased activity in visual (visual cortex, left LOC, left occipital fusiform gyrus) and reward related brain areas (thalamus and parietal operculum) in response to parental teaching and modelling of behaviour. Parental restrictive feeding and parental teaching and modelling affected neural responses to food cues in different ways, depending on motivations and diagnoses, illustrating a social influence on neural responses to food cues.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PLoS ONEarrow_drop_down
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    PLoS ONE
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PLoS ONE; OpenAPC Global Initiative
    Article . Conference object . 2016 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ PLoS ONEarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PLoS ONE
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      PLoS ONE; OpenAPC Global Initiative
      Article . Conference object . 2016 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Nancy Pham; Vincent Fazio; Luca Cucullo; Qingshan Teng; +3 Authors

    S100B, established as prevalent protein of the central nervous system, is a peripheral biomarker for blood-brain barrier disruption and often also a marker of brain injury. However, reports of extracranial sources of S100B, especially from adipose tissue, may confound its interpretation in the clinical setting. The objective of this study was to characterize the tissue specificity of S100B and assess how extracranial sources of S100B affect serum levels. The extracranial sources of S100B were determined by analyzing nine different types of human tissues by ELISA and Western blot. In addition, brain and adipose tissue were further analyzed by mass spectrometry. A study of 200 subjects was undertaken to determine the relationship between body mass index (BMI) and S100B serum levels. We also measured the levels of S100B homo- and heterodimers in serum quantitatively after blood-brain barrier disruption. Analysis of human tissues by ELISA and Western blot revealed variable levels of S100B expression. By ELISA, brain tissue expressed the highest S100B levels. Similarly, Western blot measurements revealed that brain tissue expressed high levels of S100B but comparable levels were found in skeletal muscle. Mass spectrometry of brain and adipose tissue confirmed the presence of S100B but also revealed the presence of S100A1. The analysis of 200 subjects revealed no statistically significant relationship between BMI and S100B levels. The main species of S100B released from the brain was the B-B homodimer. Our results show that extracranial sources of S100B do not affect serum levels. Thus, the diagnostic value of S100B and its negative predictive value in neurological diseases in intact subjects (without traumatic brain or bodily injury from accident or surgery) are not compromised in the clinical setting.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Europe PubMed Central
    Article . 2010
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    PLoS ONE
    Article . 2010 . Peer-reviewed
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    Article . 2010
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      Europe PubMed Central
      Article . 2010
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      Article . 2010 . Peer-reviewed
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      Article . 2010
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    Authors: Gurholt, Tiril P; Kaufmann, Tobias; Frei, Oleksandr; Alnæs, Dag; +13 Authors

    AbstractBackgroundUnderstanding complex body-brain processes, and putative interplay between adipose tissue and brain health, is of vital importance for brain and somatic disease prevention in the general population. We studied the link between body composition and brain structure through large-scale investigation in a healthy population without secondary disease effects.MethodsWe processed brain magnetic resonance imaging (MRI) data and extracted measures of brain morphometry from 19,330 healthy UK Biobank participants, of which a subset (n=2,703) had body MRI. We investigated associations between brain structure and (i) anthropometric body composition measures, and (ii) regional/specific body MRI measures of abdominal fat and muscle tissue.FindingsWe identified highly significant body-brain associations (p-values≤0·0002). Anthropometric measures showed negative, nonlinear, associations with cerebellar/cortical gray matter, and brain stem structures, negative associations with white matter, and positive associations with ventricular volumes. Subcortical structures exhibited mixed effect directionality, with strongest positive association for accumbens. Among body MRI measures, liver fat was negatively associated with thinner/lower cortical gray matter thickness/volume, and thigh muscle volume positively associated with accumbens volume.InterpretationWe demonstrate significant body-brain associations, and map individual differences in body composition to brain morphology in healthy individuals. Common measures of body composition correlated negatively with cerebellar and cortical structures and positively with the accumbens, a dopamine rich structure involved in reward processing. These findings of a relationship between brain anatomy and body composition provide new insight into body-brain processes and suggest shared mechanisms of cardiometabolic risk factors and brain disorders. This may form the foundation for a new type of prevention studies, and provides a framework for studies of underlying mechanisms related to unhealthy lifestyle and obesity, with implications for public health and prevention.FundingThe Research Council of Norway, South-Eastern Norway Regional Health Authority, European Union’s Horizon 2020 Research and Innovation Programme & European Research Council.Research in contextEvidence before this studyPrior studies have indicated an association between brain structure and both obesity and fitness levels - of opposing directionality. Despite this, normal body-brain association patterns in healthy individuals have not been established, and the causal mechanisms are unclear. To enhance our understanding and establish the link between the body and the brain, we saw the need for large-scale investigations in healthy populations. For the study, we searched the PubMed database from March 12th, 2019, through February 25th, 2020, for scientific literature related to adipose tissue, body composition, brain morphology, and body and brain MRI. Search terms included: body fat, adipose tissue, subcutaneous/visceral adipose tissue, liver fat, body composition, anthropometric measures, body mass index, waist circumference, waist-to-hip ratio, adiposity, obesity, metabolic syndrome, cardiovascular, cardiometabolic, disease/disorder, muscle volume, fitness, brain structure, brain morphology, brain MRI, and body MRI. We based the scientific foundation on review studies, meta-analyses, and other larger studies, but generally excluded smaller studies, and thereby lowering the risk of evidential bias such as winner’s curse, although this does not eliminate the risk of publication bias.Added value of this studyIn the largest study, to date, including 19,330 healthy participants without secondary disease effects, we provide insight into normal body-brain processes by identifying body-brain associations that map normally varying body composition to brain morphology.Implications of all the available evidenceWe identified body-brain associations that give insight into normal physiological body-brain processes in healthy individuals, providing a reference point for studies of underlying mechanisms related to unhealthy lifestyle, obesity, and disorders of the body and the brain. Whereas the directionality and causal chain is unknown, these findings have potential implications for public health and disease prevention.

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    Authors: Scholtz, S; Miras, AD; Chhina, N; Prechtl, CG; +14 Authors

    Objectives Roux-en-Y gastric bypass (RYGB) has greater efficacy for weight loss in obese patients than gastric banding (BAND) surgery. We hypothesise that this may result from different effects on food hedonics via physiological changes secondary to distinct gut anatomy manipulations. Design We used functional MRI, eating behaviour and hormonal phenotyping to compare body mass index (BMI)-matched unoperated controls and patients after RYGB and BAND surgery for obesity. Results Obese patients after RYGB had lower brain-hedonic responses to food than patients after BAND surgery. RYGB patients had lower activation than BAND patients in brain reward systems, particularly to high-calorie foods, including the orbitofrontal cortex, amygdala, caudate nucleus, nucleus accumbens and hippocampus. This was associated with lower palatability and appeal of high-calorie foods and healthier eating behaviour, including less fat intake, in RYGB compared with BAND patients and/or BMI-matched unoperated controls. These differences were not explicable by differences in hunger or psychological traits between the surgical groups, but anorexigenic plasma gut hormones (GLP-1 and PYY), plasma bile acids and symptoms of dumping syndrome were increased in RYGB patients. Conclusions The identification of these differences in food hedonic responses as a result of altered gut anatomy/physiology provides a novel explanation for the more favourable long-term weight loss seen after RYGB than after BAND surgery, highlighting the importance of the gut–brain axis in the control of reward-based eating behaviour.

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    Europe PubMed Central
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    Authors: Olivia Petit; Adrian David Cheok;

    Taking into account how people value the healthiness and tastiness of food at both the behavioral and brain levels may help to better understand and address overweight and obesity-related issues. Here, we investigate whether brain activity in those areas involved in self-control may increase significantly when individuals with a high body-mass index (BMI) focus their attention on the taste rather than on the health benefits related to healthy food choices. Under such conditions, BMI is positively correlated with both the neural responses to healthy food choices in those brain areas associated with gustation (insula), reward value (orbitofrontal cortex), and self-control (inferior frontal gyrus), and with the percent of healthy food choices. By contrast, when attention is directed towards health benefits, BMI is negatively correlated with neural activity in gustatory and reward-related brain areas (insula, inferior frontal operculum). Taken together, these findings suggest that those individuals with a high BMI do not necessarily have reduced capacities for self-control but that they may be facilitated by external cues that direct their attention toward the tastiness of healthy food. Thus, promoting the taste of healthy food in communication campaigns and/or food packaging may lead to more successful self-control and healthy food behaviors for consumers with a higher BMI, an issue which needs to be further researched.

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    PLoS ONE; OpenAPC Global Initiative
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    Authors: Claudia Metzler-Baddeley; Roland J. Baddeley; Derek K. Jones; John Patrick Aggleton; +1 Authors

    The prevalence of obesity and associated health conditions is increasing in the developed world. Obesity is related to atrophy and dysfunction of the hippocampus and hippocampal lesions may lead to increased appetite and weight gain. The hippocampus is connected via the fornix tract to the hypothalamus, orbitofrontal cortex, and the nucleus accumbens, all key structures for homeostatic and reward related control of food intake. The present study employed diffusion MRI tractography to investigate the relationship between microstructural properties of the fornix and variation in Body Mass Index (BMI), within normal and overweight ranges, in a group of community-dwelling older adults (53-93 years old). Larger BMI was associated with larger axial and mean diffusivity in the fornix (r = 0.64 and r = 0.55 respectively), relationships that were most pronounced in overweight individuals. Moreover, controlling for age, education, cognitive performance, blood pressure and global brain volume increased these correlations. Similar associations were not found in the parahippocampal cingulum, a comparison temporal association pathway. Thus, microstructural changes in fornix white matter were observed in older adults with increasing BMI levels from within normal to overweight ranges, so are not exclusively related to obesity. We propose that hippocampal-hypothalamic-prefrontal interactions, mediated by the fornix, contribute to the healthy functioning of networks involved in food intake control. The fornix, in turn, may display alterations in microstructure that reflect weight gain.

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    Authors: Uku Vainik; Travis E. Baker; Mahsa Dadar; Yashar Zeighami; +6 Authors

    AbstractRecent molecular genetic studies have shown that the majority of genes associated with obesity are expressed in the central nervous system. Obesity has also been associated with neurobehavioural factors such as brain morphology, cognitive performance, and personality. Here, we tested whether these neurobehavioural factors were associated with the heritable variance in obesity measured by body mass index (BMI) in the Human Connectome Project (N=895 siblings). Phenotypically, cortical thickness findings supported the “right brain hypothesis” for obesity. Namely, increased BMI associated with decreased cortical thickness in right frontal lobe and increased thickness in the left frontal lobe, notably in lateral prefrontal cortex. In addition, lower thickness and volume in entorhinal-parahippocampal structures, and increased thickness in parietal-occipital structures in participants with higher BMI supported the role of visuospatial function in obesity. Brain morphometry results were supported by cognitive tests, which outlined a negative association between BMI and visuospatial function, verbal episodic memory, impulsivity, and cognitive flexibility. Personality-BMI correlations were inconsistent. We then aggregated the effects for each neurobehavioural factor for a behavioural genetics analysis and estimated each factor’s genetic overlap with BMI. Cognitive test scores and brain morphometry had 0.25 - 0.45 genetic correlations with BMI, and the phenotypic correlations with BMI were 77-89% explained by genetic factors. Neurobehavioural factors also had some genetic overlap with each other. In summary, obesity as measured by BMI has considerable genetic overlap with brain and cognitive measures. This supports the theory that obesity is inherited via brain function, and may inform intervention strategies.Significance StatementObesity is a widespread heritable health condition. Evidence from psychology, cognitive neuroscience, and genetics has proposed links between obesity and the brain. The current study tested whether the heritable variance in body mass index (BMI) is explained by brain and behavioural factors in a large brain imaging cohort that included multiple related individuals. We found that the heritable variance in BMI had genetic correlations 0.25 - 0.45 with cognitive tests, cortical thickness, and regional brain volume. In particular, BMI was associated with frontal lobe asymmetry and differences in temporal-parietal perceptual systems. Further, we found genetic overlap between certain brain and behavioural factors. In summary, the genetic vulnerability to BMI is expressed in the brain. This may inform intervention strategies.

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    bioRxiv
    Preprint . 2017
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    Proceedings of the National Academy of Sciences
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      bioRxiv
      Preprint . 2017
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      Proceedings of the National Academy of Sciences
      Article . 2018 . Peer-reviewed
      License: CC BY NC ND
      Data sources: Crossref
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      Proceedings of the National Academy of Sciences
      Article . Preprint
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    Authors: Heni, Martin; Kullmann, Stephanie; Gallwitz, Baptist; Häring, Hans-Ulrich; +2 Authors

    Objective Glucagon-like peptide-1 (GLP-1) is released into the bloodstream after food intake. In addition to stimulating insulin release, it causes satiety and contributes to the termination of food intake. In this study, we investigated whether endogenous GLP-1 affects food-related brain activity and hunger. Methods Twenty-four volunteers (12 lean; 12 obese) underwent a 75 g oral glucose tolerance test that promotes GLP-1 secretion. Food cue-induced brain activity was assessed by functional magnetic resonance imaging and GLP-1 concentrations were measured before, 30, and 120 min after glucose intake. Results The significant increase in GLP-1 levels negatively correlated with a change in the food cue-induced brain activity in the orbitofrontal cortex, a major reward area. This association was independent of simultaneous alterations in insulin and glucose concentrations. The association was present in lean and overweight participants. By contrast, postprandial insulin changes were associated with orbitofrontal activations in lean individuals only. Conclusions The postprandial release of GLP-1 might alter reward processes in the orbitofrontal cortex and might thereby support the termination of food intake and reduce hunger. While obese persons showed brain insulin resistance, no GLP-1 resistance was observed. Our study provides novel insight into the central regulation of food intake by the incretin hormone GLP-1. Highlights • GLP-1 levels associate with food cue-induced brain activity in the orbitofrontal cortex, a major reward area. • While obese persons are brain insulin-resistant in the orbitofrontal cortex, they still respond to GLP-1. • Postprandial GLP-1 release may alter reward processes in the orbitofrontal cortex to support the termination of food intake.

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    Europe PubMed Central
    Article . 2015
    Data sources: PubMed Central
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    Molecular Metabolism
    Article . 2015 . Peer-reviewed
    License: CC BY NC ND
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    Molecular Metabolism
    Article . 2015
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      Europe PubMed Central
      Article . 2015
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      Molecular Metabolism
      Article . 2015 . Peer-reviewed
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      Article . 2015
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Park, Bo-yong; Hong, Jisu; Park, Hyunjin;

    AbstractObesity is a serious medical condition highly associated with health problems such as diabetes, hypertension, and stroke. Obesity is highly associated with negative emotional states, but the relationship between obesity and emotional states in terms of neuroimaging has not been fully explored. We obtained 196 emotion task functional magnetic resonance imaging (t-fMRI) from the Human Connectome Project database using a sampling scheme similar to a bootstrapping approach. Brain regions were specified by automated anatomical labeling atlas and the brain activity (z-statistics) of each brain region was correlated with body mass index (BMI) values. Regions with significant correlation were identified and the brain activity of the identified regions was correlated with emotion-related clinical scores. Hippocampus, amygdala, and inferior temporal gyrus consistently showed significant correlation between brain activity and BMI and only the brain activity in amygdala consistently showed significant negative correlation with fear-affect score. The brain activity in amygdala derived from t-fMRI might be good neuroimaging biomarker for explaining the relationship between obesity and a negative emotional state.

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    Europe PubMed Central
    Article . 2017
    Data sources: PubMed Central
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    Scientific Reports
    Article . 2017 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Scientific Reports
    Article . 2017
    Data sources: DOAJ-Articles
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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      Europe PubMed Central
      Article . 2017
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      Scientific Reports
      Article . 2017 . Peer-reviewed
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      Scientific Reports
      Article . 2017
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anna Ratsika; Martin C. Codagnone; Siobhain M. O'Mahony; Catherine Stanton; +1 Authors

    Microbes colonize the human body during the first moments of life and coexist with the host throughout the lifespan. Intestinal microbiota and their metabolites aid in the programming of important bodily systems such as the immune and the central nervous system during critical temporal windows of development, with possible structural and functional implications throughout the lifespan. These critical developmental windows perinatally (during the first 1000 days) are susceptible timepoints for insults that can endure long lasting effects on the microbiota-gut-brain axis. Environmental and parental factors like host genetics, mental health, nutrition, delivery and feeding mode, exposure to antibiotics, immune activation and microbiota composition antenatally, are all factors that are able to modulate the microbiota composition of mother and infant and may thus regulate important bodily functions. Among all these factors, early life nutrition plays a pivotal role in perinatal programming and in the modulation of offspring microbiota from birth throughout lifespan. This review aims to present current data on the impact of early life nutrition and microbiota priming of important bodily systems and all the factors influencing the microbial coexistence with the host during early life development.

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    Nutrients
    Article . 2021 . Peer-reviewed
    License: CC BY
    Data sources: Sygma; Crossref
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    Europe PubMed Central
    Article . 2021
    Data sources: PubMed Central
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    Nutrients
    Article . 2021
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    Nutrients
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