The effect of the GLP-1 analogue Exenatide on functional connectivity within an NTS-based network in women with and without obesity.

ObjectiveThe differential effect of GLP-1 agonist Exenatide on functional connectivity of the nucleus tractus solitaries (NTS), a key region associated with homeostasis, and on appetite-related behaviours was investigated in women with normal weight compared with women with obesity.MethodsFollowing an 8-h fast, 19 female subjects (11 lean, 8 obese) participated in a 2-d double blind crossover study. Subjects underwent functional magnetic resonance imaging at fast and 30-min post subcutaneous injection of 5 μg of Exenatide or placebo. Functional connectivity was examined with the NTS. Drug-induced functional connectivity changes within and between groups and correlations with appetite measures were examined in a region of interest approach focusing on the thalamus and hypothalamus.ResultsWomen with obesity reported less hunger after drug injection. Exenatide administration increased functional connectivity of the left NTS with the left thalamus and hypothalamus in the obese group only and increased the correlation between NTS functional connectivity and hunger scores in all subjects, but more so in the obese.ConclusionsObesity can impact the effects of Exenatide on brain connectivity, specifically in the NTS and is linked to changes in appetite control. This has implications for the use of GLP-1 analogues in therapeutic interventions

Altered functional connectivity within the central reward network in overweight and obese women.

Background/objectivesNeuroimaging studies in obese subjects have identified abnormal activation of key regions of central reward circuits, including the nucleus accumbens (NAcc), in response to food-related stimuli. We aimed to examine whether women with elevated body mass index (BMI) show structural and resting state (RS) functional connectivity alterations within regions of the reward network.Subjects/methodsFifty healthy, premenopausal women, 19 overweight and obese (high BMI=26-38 kg m(-2)) and 31 lean (BMI=19-25 kg m(-2)) were selected from the University of California Los Angeles' Oppenheimer Center for Neurobiology of Stress database. Structural and RS functional scans were collected. Group differences in grey matter volume (GMV) of the NAcc, oscillation dynamics of intrinsic brain activity and functional connectivity of the NAcc to regions within the reward network were examined.ResultsGMV of the left NAcc was significantly greater in the high BMI group than in the lean group (P=0.031). Altered frequency distributions were observed in women with high BMI compared with lean group in the left NAcc (P=0.009) in a medium-frequency (MF) band, and in bilateral anterior cingulate cortex (ACC) (P=0.014, <0.001) and ventro-medial prefrontal cortex (vmPFC) (P=0.034, <0.001) in a high-frequency band. Subjects with high BMI had greater connectivity of the left NAcc with bilateral ACC (P=0.024) and right vmPFC (P=0.032) in a MF band and with the left ACC (P=0.03) in a high frequency band.ConclusionsOverweight and obese women in the absence of food-related stimuli show significant structural and functional alterations within regions of reward-related brain networks, which may have a role in altered ingestive behaviors

History of early life adversity is associated with increased food addiction and sex-specific alterations in reward network connectivity in obesity.

Background:Neuroimaging studies have identified obesity-related differences in the brain's resting state activity. An imbalance between homeostatic and reward aspects of ingestive behaviour may contribute to obesity and food addiction. The interactions between early life adversity (ELA), the reward network and food addiction were investigated to identify obesity and sex-related differences, which may drive obesity and food addiction. Methods:Functional resting state magnetic resonance imaging was acquired in 186 participants (high body mass index [BMI]: ≥25: 53 women and 54 men; normal BMI: 18.50-24.99: 49 women and 30 men). Participants completed questionnaires to assess ELA (Early Traumatic Inventory) and food addiction (Yale Food Addiction Scale). A tripartite network analysis based on graph theory was used to investigate the interaction between ELA, brain connectivity and food addiction. Interactions were determined by computing Spearman rank correlations, thresholded at q < 0.05 corrected for multiple comparisons. Results:Participants with high BMI demonstrate an association between ELA and food addiction, with reward regions playing a role in this interaction. Among women with high BMI, increased ELA was associated with increased centrality of reward and emotion regulation regions. Men with high BMI showed associations between ELA and food addiction with somatosensory regions playing a role in this interaction. Conclusions:The findings suggest that ELA may alter brain networks, leading to increased vulnerability for food addiction and obesity later in life. These alterations are sex specific and involve brain regions influenced by dopaminergic or serotonergic signalling

Sex differences in the influence of body mass index on anatomical architecture of brain networks.

Background/objectivesThe brain has a central role in regulating ingestive behavior in obesity. Analogous to addiction behaviors, an imbalance in the processing of rewarding and salient stimuli results in maladaptive eating behaviors that override homeostatic needs. We performed network analysis based on graph theory to examine the association between body mass index (BMI) and network measures of integrity, information flow and global communication (centrality) in reward, salience and sensorimotor regions and to identify sex-related differences in these parameters.Subjects/methodsStructural and diffusion tensor imaging were obtained in a sample of 124 individuals (61 males and 63 females). Graph theory was applied to calculate anatomical network properties (centrality) for regions of the reward, salience and sensorimotor networks. General linear models with linear contrasts were performed to test for BMI and sex-related differences in measures of centrality, while controlling for age.ResultsIn both males and females, individuals with high BMI (obese and overweight) had greater anatomical centrality (greater connectivity) of reward (putamen) and salience (anterior insula) network regions. Sex differences were observed both in individuals with normal and elevated BMI. In individuals with high BMI, females compared to males showed greater centrality in reward (amygdala, hippocampus and nucleus accumbens) and salience (anterior mid-cingulate cortex) regions, while males compared to females had greater centrality in reward (putamen) and sensorimotor (posterior insula) regions.ConclusionsIn individuals with increased BMI, reward, salience and sensorimotor network regions are susceptible to topological restructuring in a sex-related manner. These findings highlight the influence of these regions on integrative processing of food-related stimuli and increased ingestive behavior in obesity, or in the influence of hedonic ingestion on brain topological restructuring. The observed sex differences emphasize the importance of considering sex differences in obesity pathophysiology

Synaptic Remodeling Depends on Signaling between Serotonin Receptors and the Extracellular Matrix

Rewiring of synaptic circuitry pertinent to memory formation has been associated with morphological changes in dendritic spines and with extracellular matrix (ECM) remodeling. Here, we mechanistically link these processes by uncovering a signaling pathway involving the serotonin 5-HT7 receptor (5-HT7R), matrix metalloproteinase 9 (MMP-9), the hyaluronan receptor CD44, and the small GTPase Cdc42. We highlight a physical interaction between 5-HT7R and CD44 (identified as an MMP-9 substrate in neurons) and find that 5-HT7R stimulation increases local MMP-9 activity, triggering dendritic spine remodeling, synaptic pruning, and impairment of long-term potentiation (LTP). The underlying molecular machinery involves 5-HT7R-mediated activation of MMP-9, which leads to CD44 cleavage followed by Cdc42 activation. One important physiological consequence of this interaction includes an increase in neuronal outgrowth and elongation of dendritic spines, which might have a positive effect on complex neuronal processes (e.g., reversal learning and neuronal regeneration)

Increased pain intensity is associated with greater verbal communication difficulty and increased production of speech and co-speech gestures

Effective pain communication is essential if adequate treatment and support are to be provided. Pain communication is often multimodal, with sufferers utilising speech, nonverbal behaviours (such as facial expressions), and co-speech gestures (bodily movements, primarily of the hands and arms that accompany speech and can convey semantic information) to communicate their experience. Research suggests that the production of nonverbal pain behaviours is positively associated with pain intensity, but it is not known whether this is also the case for speech and co-speech gestures. The present study explored whether increased pain intensity is associated with greater speech and gesture production during face-to-face communication about acute, experimental pain. Participants (N = 26) were exposed to experimentally elicited pressure pain to the fingernail bed at high and low intensities and took part in video-recorded semi-structured interviews. Despite rating more intense pain as more difficult to communicate (t(25) = 2.21, p = .037), participants produced significantly longer verbal pain descriptions and more co-speech gestures in the high intensity pain condition (Words: t(25) = 3.57, p = .001; Gestures: t(25) = 3.66, p = .001). This suggests that spoken and gestural communication about pain is enhanced when pain is more intense. Thus, in addition to conveying detailed semantic information about pain, speech and co-speech gestures may provide a cue to pain intensity, with implications for the treatment and support received by pain sufferers. Future work should consider whether these findings are applicable within the context of clinical interactions about pain

Protocol for a randomized controlled study of Iyengar yoga for youth with irritable bowel syndrome

<p>Abstract</p> <p>Introduction</p> <p>Irritable bowel syndrome affects as many as 14% of high school-aged students. Symptoms include discomfort in the abdomen, along with diarrhea and/or constipation and other gastroenterological symptoms that can significantly impact quality of life and daily functioning. Emotional stress appears to exacerbate irritable bowel syndrome symptoms suggesting that mind-body interventions reducing arousal may prove beneficial. For many sufferers, symptoms can be traced to childhood and adolescence, making the early manifestation of irritable bowel syndrome important to understand. The current study will focus on young people aged 14-26 years with irritable bowel syndrome. The study will test the potential benefits of Iyengar yoga on clinical symptoms, psychospiritual functioning and visceral sensitivity. Yoga is thought to bring physical, psychological and spiritual benefits to practitioners and has been associated with reduced stress and pain. Through its focus on restoration and use of props, Iyengar yoga is especially designed to decrease arousal and promote psychospiritual resources in physically compromised individuals. An extensive and standardized teacher-training program support Iyengar yoga's reliability and safety. It is hypothesized that yoga will be feasible with less than 20% attrition; and the yoga group will demonstrate significantly improved outcomes compared to controls, with physiological and psychospiritual mechanisms contributing to improvements.</p> <p>Methods/Design</p> <p>Sixty irritable bowel syndrome patients aged 14-26 will be randomly assigned to a standardized 6-week twice weekly Iyengar yoga group-based program or a wait-list usual care control group. The groups will be compared on the primary clinical outcomes of irritable bowel syndrome symptoms, quality of life and global improvement at post-treatment and 2-month follow-up. Secondary outcomes will include visceral pain sensitivity assessed with a standardized laboratory task (water load task), functional disability and psychospiritual variables including catastrophizing, self-efficacy, mood, acceptance and mindfulness. Mechanisms of action involved in the proposed beneficial effects of yoga upon clinical outcomes will be explored, and include the mediating effects of visceral sensitivity, increased psychospiritual resources, regulated autonomic nervous system responses and regulated hormonal stress response assessed via salivary cortisol.</p> <p>Trial registration</p> <p>ClinicalTrials.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01107977">NCT01107977</a>.</p

Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery

Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phenotyping efforts. The objective of this study was to select principal features extracted from UAV imagery and critical growth stages that contributed the most in explaining winter wheat grain yield. Five dates of multispectral images and seven dates of RGB images were collected by a UAV system during the spring growing season in 2018. Two classes of features (variables), totaling to 172 variables, were extracted for each plot from the vegetation index and plant height maps, including pixel statistics and dynamic growth rates. A parametric algorithm, LASSO regression (the least angle and shrinkage selection operator), and a non-parametric algorithm, random forest, were applied for variable selection. The regression coefficients estimated by LASSO and the permutation importance scores provided by random forest were used to determine the ten most important variables influencing grain yield from each algorithm. Results: Both selection algorithms assigned the highest importance score to the variables related with plant height around the grain filling stage. Some vegetation indices related variables were also selected by the algorithms mainly at earlier to mid growth stages and during the senescence. Compared with the yield prediction using all 172 variables derived from measured phenotypes, using the selected variables performed comparable or even better. We also noticed that the prediction accuracy on the adapted NE lines (r = 0.58–0.81) was higher than the other lines (r = 0.21–0.59) included in this study with different genetic backgrounds. Conclusions: With the ultra-high resolution plot imagery obtained by the UAS-based phenotyping we are now able to derive more features, such as the variation of plant height or vegetation indices within a plot other than just an averaged number, that are potentially very useful for the breeding purpose. However, too many features or variables can be derived in this way. The promising results from this study suggests that the selected set from those variables can have comparable prediction accuracies on the grain yield prediction than the full set of them but possibly resulting in a better allocation of efforts and resources on phenotypic data collection and processing