888 research outputs found

    Ethnic differences in adiposity and diabetes risk – insights from genetic studies

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    Type 2 diabetes is more common in non-Europeans and starts at a younger age and at lower BMI cut-offs. This review discusses the insights from genetic studies about pathophysiological mechanisms which determine risk of disease with a focus on the role of adiposity and body fat distribution in ethnic disparity in risk of type 2 diabetes. During the past decade, genome-wide association studies (GWAS) have identified more than 400 genetic variants associated with the risk of type 2 diabetes. The Eurocentric nature of these genetic studies have made them less effective in identifying mechanisms that make non-Europeans more susceptible to higher risk of disease. One possible mechanism suggested by epidemiological studies is the role of ethnic difference in body fat distribution. Using genetic variants associated with an ability to store extra fat in a safe place, which is subcutaneous adipose tissue, we discuss how different ethnic groups could be genetically less susceptible to type 2 diabetes by developing a more favourable fat distribution

    Body Fat: our own Janus

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    A Framework for Automatic Morphological Feature Extraction and Analysis of Abdominal Organs in MRI Volumes

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    The accurate 3D reconstruction of organs from radiological scans is an essential tool in computer-aided diagnosis (CADx) and plays a critical role in clinical, biomedical and forensic science research. The structure and shape of the organ, combined with morphological measurements such as volume and curvature, can provide significant guidance towards establishing progression or severity of a condition, and thus support improved diagnosis and therapy planning. Furthermore, the classification and stratification of organ abnormalities aim to explore and investigate organ deformations following injury, trauma and illness. This paper presents a framework for automatic morphological feature extraction in computer-aided 3D organ reconstructions following organ segmentation in 3D radiological scans. Two different magnetic resonance imaging (MRI) datasets are evaluated. Using the MRI scans of 85 adult volunteers, the overall mean volume for the pancreas organ is 69.30 ± 32.50cm3, and the 3D global curvature is (35.23 ± 6.83) × 10−3. Another experiment evaluates the MRI scans of 30 volunteers, and achieves mean liver volume of 1547.48 ± 204.19cm3 and 3D global curvature (19.87 ± 3.62) × 10− 3. Both experiments highlight a negative correlation between 3D curvature and volume with a statistical difference (p < 0.0001). Such a tool can support the investigation into organ related conditions such as obesity, type 2 diabetes mellitus and liver disease

    A Framework for Morphological Feature Extraction of Organs from MR Images for Detection and Classification of Abnormalities

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    In clinical practice, a misdiagnosis can lead to incorrect or delayed treatment, and in some cases, no treatment at all; consequently, the condition of a patient may worsen to varying degrees, in some cases proving fatal. The accurate 3D reconstruction of organs, which is a pioneering tool of medical image computing (MIC) technology, plays a key role in computer aided diagnosis (CADx), thereby enabling medical professionals to perform enhanced analysis on a region of interest. From here, the shape and structure of the organ coupled with measurements of its volume and curvature can provide significant guidance towards establishing the severity of a disorder or abnormality, consequently supporting improved diagnosis and treatment planning. Moreover, the classification and stratification of organ abnormalities is widely utilised within biomedical, forensic and MIC research for exploring and investigating organ deformations following injury, illness or trauma. This paper presents a tool that calculates, classifies and analyses pancreatic volume and curvature following their 3D reconstruction. Magnetic resonance imaging (MRI) volumes of 115 adult patients are evaluated in order to examine a correlation between these two variables. Such a tool can be utilised in the scope of much greater research and investigation. It can also be incorporated into the development of effective medical image analysis software application in the stratification of subjects and targeting of therapies

    Cell-Cell Death Communication by Signals Passing Through Non-Aqueous Environments: A Reply

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    The effects of the emission of low intensity light from cells and organelles, known as biophotons, or ultraweak photon emission, are not well understood and subject to debate. Potapovich & Kostyuk recently proposed that the induction of oxidative stress generates non-chemical death signals which can induce cell death in neighbouring, chemically isolated cells (termed detector cells). Given the significance of these results, here we attempt to replicate their findings. We found treatment of “inductor cells” with duroquinone dissolved in ethanol does indeed induce significant cell death in neighbouring “detector” cells relative to distant control cells (64.53% ± 14.42 vs 99.72% ± 6.09 cell viability), closely reproducing their original results. However, this was no longer true if the induction drug was dissolved in a less volatile solvent, suggesting that their original findings may have been a result of volatile solvent-based transmission as opposed to light-based non-chemical signalling

    Psoas major cross-sectional area: A potential marker of cardiorespiratory fitness

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    Background and Aim: Cardiorespiratory fitness is an important marker for overall health that significantly correlates with obesity-associated morbidities and mortality. Maximal oxygen uptake (VO2max) recorded during an incremental exercise test is the gold standard assessment for aerobic fitness. However, its cost, chronic illness, and frailty often preclude its application. The cross-sectional area (CSA) of the abdominal psoas major muscle is a predictor of sarcopenia and surgery outcomes and represents a promising biomarker for cardiorespiratory health. Therefore, in the present study, we have planned to assess the relationship between psoas major CSA, anthropometry, and body composition in a UK-based cohort of 210 men and women. Methods: Body mass (kg), height (cm), waist circumference (cm), VO2max, and blood pressure were measured in each participant. The CSA of psoas major, rectus abdominus, and another abdominal muscle of the core muscle group were assessed. Results: Following adjustment for height, psoas major CSA was found to be a significant predictor of percentage body fat (P = 0.02) in men, and body mass index (BMI) in both men (P = 0.015) and women (P = 0.004). We found psoas major CSA correlated more strongly with VO2max (r = 0.74, P < 0.01) than any other study outcome, including age and BMI. Conclusion: Psoas major muscle CSA represents an accurate, reproducible, and time-efficient surrogate for cardiorespiratory fitness and body composition

    Non-chemical Signalling Between Mitochondria

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    A wide variety of studies have reported some form of non-chemical or non-aqueous communication between physically isolated organisms, eliciting changes in cellular proliferation, morphology, and/or metabolism. The sources and mechanisms of such signalling pathways are still unknown, but have been postulated to involve vibration, volatile transmission, or light through the phenomenon of ultraweak photon emission. Here, we report non-chemical communication between isolated mitochondria from MCF7 (cancer) and MCF10A (non-cancer) cell lines. We found that mitochondria in one cuvette stressed by an electron transport chain inhibitor, antimycin, alters the respiration of mitochondria in an adjacent, but chemically and physically separate cuvette, significantly decreasing the rate of oxygen consumption compared to a control (p = <0.0001 in MCF7 and MCF10A mitochondria). Moreover, the changes in O2-consumption were dependent on the origin of mitochondria (cancer vs non-cancer) as well as the presence of "ambient" light. Our results support the existence of non-chemical signalling between isolated mitochondria. The experimental design suggests that the non-chemical communication is light-based, although further work is needed to fully elucidate its nature

    A randomized controlled trial: the effect of inulin on weight management and ectopic fat in subjects with prediabetes.

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    BACKGROUND: Fat infiltration of the liver, muscle and pancreas is associated with insulin resistance and risk of diabetes. Weight loss reduces ectopic fat deposition and risk of diabetes, but is difficult to sustain to due to compensatory increases in appetite. Fermentable carbohydrates have been shown to decrease appetite and food intake, and promote weight loss in overweight subjects. In animal studies, fermentable carbohydrate reduces ectopic fat independent of weight loss. We aimed to investigate the effect of the fermentable carbohydrate inulin on weight maintenance, appetite and ectopic fat in subjects with prediabetes. METHODS: Forty-four subjects with prediabetes were randomized to 18 weeks' inulin or cellulose supplementation. During weeks 1-9 (weight loss phase) all subjects had four visits with a dietitian to guide them towards a 5 % weight loss. During weeks 10-18 (weight maintenance phase) subjects continued taking their assigned supplementation and were asked to maintain the weight they had lost but were offered no further support. All subjects attended study sessions at baseline, 9 and 18 weeks for measurement of weight; assessment of adipose tissue and ectopic fat content by magnetic resonance imaging and magnetic resonance spectroscopy; glucose, insulin and GLP-1 levels following a meal tolerance test; and appetite by ad libitum meal test and visual analogue scales. RESULTS: Both groups lost approximately 5 % of their body weight by week nine (-5.3 ± 0.1 % vs -4.3 ± 0.4 %, p = 0.13, but the inulin group lost significantly more weight between 9 and 18 weeks (-2.3 ± 0.5 % vs -0.6 ± 0.4 %, p = 0.012). Subjects taking inulin had lower hepatic (p = 0.02) and soleus muscle (p < 0.05) fat content at 18 weeks compared to control even after controlling for weight loss and consumed less at the ad libitum meal test (p = 0.027). Fasting glucose significantly decreased at week nine only (p = 0.005), insulin concentrations did not change, and there was a significant increase in GLP-1 in the cellulose group at 9 and 18 weeks (p < 0.03, p < 0.00001). CONCLUSION: Inulin may have a two-pronged effect on the risk of diabetes by 1) promoting weight loss 2) reducing intrahepatocellular and intramyocellular lipid in people with prediabetes independent of weight loss

    3D Deep Learning for Anatomical Structure Segmentation in Multiple Imaging Modalities

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    Accurate, automated quantitative segmentation of anatomical structures in radiological scans, such as Magnetic Resonance Imaging (MRI) and Computer Tomography (CT), can produce significant biomarkers and can be integrated into computer-aided diagnosis (CADx) systems to support the in- terpretation of medical images from multi-protocol scanners. However, there are serious challenges towards developing robust automated segmentation techniques, including high variations in anatomical structure and size, varying image spatial resolutions resulting from different scanner protocols, and the presence of blurring artefacts. This paper presents a novel computing ap- proach for automated organ and muscle segmentation in medical images from multiple modalities by harnessing the advantages of deep learning techniques in a two-part process. (1) a 3D encoder-decoder, Rb-UNet, builds a localisation model and a 3D Tiramisu network generates a boundary-preserving segmentation model for each target structure; (2) the fully trained Rb-UNet predicts a 3D bounding box encapsulating the target structure of interest, after which the fully trained Tiramisu model performs segmentation to reveal organ or muscle boundaries for every protrusion and indentation. The proposed approach is evaluated on six different datasets, including MRI, Dynamic Contrast Enhanced (DCE) MRI and CT scans targeting the pancreas, liver, kidneys and iliopsoas muscles. We achieve quantitative measures of mean Dice similarity coefficient (DSC) that surpasses or are comparable with the state-of-the-art and demonstrate statistical stability. A qualitative evaluation performed by two independent experts in radiology and radiography verified the preservation of detailed organ and muscle boundaries
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