Obesity-induced alterations in the gut microbiome in female mice fed a high-fat diet are antagonized by dietary supplementation with a novel, wax ester–rich, marine oil

Dietary supplementation with calanus oil, a novel wax ester–rich marine oil, has been shown to reduce adiposity in high-fat diet (HFD)–induced obese mice. Current evidence suggests that obesity and its comorbidities are intrinsically linked with unfavorable changes in the intestinal microbiome. Thus, in line with its antiobesity effect, we hypothesized that dietary supplementation with calanus oil should counteract the obesity-related deleterious changes in the gut microbiota. Seven-week-old female C57bl/6J mice received an HFD for 12 weeks to induce obesity followed by 8-week supplementation with 2% calanus oil. For comparative reasons, another group of mice was treated with exenatide, an antiobesogenic glucagon-like peptide-1 receptor agonist. Mice fed normal chow diet or nonsupplemented HFD for 20 weeks served as lean and obese controls, respectively. 16S rRNA gene sequencing was performed on fecal samples from the colon. HFD increased the abundance of the Lactococcus and Leuconostoc genera relative to normal chow diet, whereas abundances of Allobaculum and Oscillospira were decreased. Supplementation with calanus oil led to an apparent overrepresentation of Lactobacillus and Streptococcus and underrepresentation of Bilophila. Exenatide prevented the HFD-induced increase in Lactococcus and caused a decrease in the abundance of Streptococcus compared to the HFD group. Thus, HFD altered the gut microbiota composition in an unhealthy direction by increasing the abundance of proinflammatory genera while reducing those considered health-promoting. These obesity-induced changes were antagonized by both calanus oil and exenatide

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Modulation of Cardiometabolic Health by Dietary Supplementation with Calanus oil

Obesity leads to alterations in myocardial metabolism, expressed as an increased utilization of fat for energy purposes at the expense of carbohydrate. This shift in energy metabolism is associated with impairment of ventricular function which can lead to heart failure. This thesis raises the question of whether dietary supplementation with Calanus oil, a novel marine oil derived from the marine copepod, Calanus finmarchicus (Norwegian, raudåte), can attenuate obesity-related changes in metabolism and associated co-morbidities. The major finding in this thesis project was that dietary Calanus oil was able to prevent obesity-related shifts in myocardial metabolism and restore the capacity of the heart to utilize carbohydrate as energy source. In addition, we demonstrated that Calanus oil had a cardioprotective action, in the sense that recovery ventricular function following an ischemic insult of hearts from mice receiving high-fat diet with Calanus oil was superior to that of control hearts. To examine the mechanism involved, we exposed H9c2 cardiomyoblast to lipotoxic stress (palmitic acid) with and without micromolar concentrations of hydrolysed wax ester from Calanus oil (WEH). Live cell imaging revealed major cell death in response to palmitiate-exposure, while co-incubation with WEH almost completely rescued the cells. Further analyses suggested that WEH protects H9c2 cardiomyocytes from lipotoxicity by attenuating the associated ER stress, as well as alleviating palmitate-induced impairment of autophagic flux. This thesis also showed that Calanus oil, at least to some extent, were able to antagonize obesity-induced changes in the gut microbiota composition. In conclusion, the present results show that dietary supplementation with Calanus oil has the potential to attenuate obesity-induced alterations in myocardial metabolism and, in addition, protect the heart towards ischemic stress, and may therefore be an alternative to anti-obesity/anti-diabetic drugs

Ecological Discomforts and How to Study Them

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A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task

Background: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively trained with dermoscopic images in a clinical image classification task in direct competition with a large number of dermatologists has not been measured to date. This study compares the performance of a convolutional neuronal network trained with dermoscopic images exclusively for identifying melanoma in clinical photographs with the manual grading of the same images by dermatologists. Methods: We compared automatic digital melanoma classification with the performance of 145 dermatologists of 12 German university hospitals. We used methods from enhanced deep learning to train a CNN with 12,378 open-source dermoscopic images. We used 100 clinical images to compare the performance of the CNN to that of the dermatologists. Dermatologists were compared with the deep neural network in terms of sensitivity, specificity and receiver operating characteristics. Findings: The mean sensitivity and specificity achieved by the dermatologists with clinical images was 89.4% (range: 55.0%-100%) and 64.4% (range: 22.5%-92.5%). At the same sensitivity, the CNN exhibited a mean specificity of 68.2% (range 47.5%-86.25%). Among the dermatologists, the attendings showed the highest mean sensitivity of 92.8% at a mean specificity of 57.7%. With the same high sensitivity of 92.8%, the CNN had a mean specificity of 61.1%. Interpretation: For the first time, dermatologist-level image classification was achieved on a clinical image classification task without training on clinical images. The CNN had a smaller variance of results indicating a higher robustness of computer vision compared with human assessment for dermatologic image classification tasks. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)