Insulin Sensitivity Is Reflected by Characteristic Metabolic Fingerprints - A Fourier Transform Mass Spectrometric Non-Targeted Metabolomics Approach

BACKGROUND: A decline in body insulin sensitivity in apparently healthy individuals indicates a high risk to develop type 2 diabetes. Investigating the metabolic fingerprints of individuals with different whole body insulin sensitivity according to the formula of Matsuda, et al. (ISI(Matsuda)) by a non-targeted metabolomics approach we aimed a) to figure out an unsuspicious and altered metabolic pattern, b) to estimate a threshold related to these changes based on the ISI, and c) to identify the metabolic pathways responsible for the discrimination of the two patterns. METHODOLOGY AND PRINCIPAL FINDINGS: By applying infusion ion cyclotron resonance Fourier transform mass spectrometry, we analyzed plasma of 46 non-diabetic subjects exhibiting high to low insulin sensitivities. The orthogonal partial least square model revealed a cluster of 28 individuals with alterations in their metabolic fingerprints associated with a decline in insulin sensitivity. This group could be separated from 18 subjects with an unsuspicious metabolite pattern. The orthogonal signal correction score scatter plot suggests a threshold of an ISI(Matsuda) of 15 for the discrimination of these two groups. Of note, a potential subgroup represented by eight individuals (ISI(Matsuda) value between 8.5 and 15) was identified in different models. This subgroup may indicate a metabolic transition state, since it is already located within the cluster of individuals with declined insulin sensitivity but the metabolic fingerprints still show some similarities with unaffected individuals (ISI >15). Moreover, the highest number of metabolite intensity differences between unsuspicious and altered metabolic fingerprints was detected in lipid metabolic pathways (arachidonic acid metabolism, metabolism of essential fatty acids and biosynthesis of unsaturated fatty acids), steroid hormone biosyntheses and bile acid metabolism, based on data evaluation using the metabolic annotation interface MassTRIX. CONCLUSIONS: Our results suggest that altered metabolite patterns that reflect changes in insulin sensitivity respectively the ISI(Matsuda) are dominated by lipid-related pathways. Furthermore, a metabolic transition state reflected by heterogeneous metabolite fingerprints may precede severe alterations of metabolism. Our findings offer future prospects for novel insights in the pathogenesis of the pre-diabetic phase

Investigating the Effect of Galaxy Interactions on the Enhancement of Active Galactic Nuclei at 0.5 < z < 3.0

Galaxy interactions and mergers are thought to play an important role in the evolution of galaxies. Studies in the nearby universe show a higher AGN fraction in interacting and merging galaxies than their isolated counterparts, indicating that such interactions are important contributors to black hole growth. To investigate the evolution of this role at higher redshifts, we have compiled the largest known sample of major spectroscopic galaxy pairs (2381 with $\Delta V <5000$ km s$^{-1}$) at $0.5<z<3.0$ from observations in the COSMOS and CANDELS surveys. We identify X-ray and IR AGN among this kinematic pair sample, a visually identified sample of mergers and interactions, and a mass-, redshift-, and environment-matched control sample for each in order to calculate AGN fractions and the level of AGN enhancement as a function of relative velocity, redshift, and X-ray luminosity. While we see a slight increase in AGN fraction with decreasing projected separation, overall, we find no significant enhancement relative to the control sample at any separation. In the closest projected separation bin ($<25$ kpc, $\Delta V <1000$ km s$^{-1}$), we find enhancements of a factor of 0.94$^{+0.21}_{-0.16}$ and 1.00$^{+0.58}_{-0.31}$ for X-ray and IR-selected AGN, respectively. While we conclude that galaxy interactions do not significantly enhance AGN activity on average over $0.5<z<3.0$ at these separations, given the errors and the small sample size at the closest projected separations, our results would be consistent with the presence of low-level AGN enhancement

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Microenvironmental regulation of metastasis

Metastasis is a multistage process that requires cancer cells to escape from the primary tumour, survive in the circulation, seed at distant sites and grow. Each of these processes involves rate-limiting steps that are influenced by non-malignant cells of the tumour microenvironment. Many of these cells are derived from the bone marrow, particularly the myeloid lineage, and are recruited by cancer cells to enhance their survival, growth, invasion and dissemination. This Review describes experimental data demonstrating the role of the microenvironment in metastasis, identifies areas for future research and suggests possible new therapeutic avenues

Functional microbiomics: evaluation of gut microbiota-bile acid metabolism interactions in health and disease

There is an ever-increasing recognition that bile acids are not purely simple surfactant molecules that aid in lipid digestion, but are a family of molecules contributing to a diverse range of key systemic functions in the host. It is now also understood that the specific composition of the bile acid milieu within the host is related to the expression and activity of bacterially-derived enzymes within the gastrointestinal tract, as such creating a direct link between the physiology of the host and the gut microbiota. Coupled to the knowledge that perturbation of the structure and/or function of the gut microbiota may contribute to the pathogenesis of a range of diseases, there is a high level of interest in the potential for manipulation of the gut microbiota-host bile acid axis as a novel approach to therapeutics. Much of the growing understanding of the biology of this area reflects the recent development and refinement of a range of novel techniques; this study applies a number of those techniques to the analysis of human samples, aiming to illustrate their strengths, drawbacks and biological significance at all stages. Specifically, we used microbial profiling (using 16S rRNA gene sequencing), bile acid profiling (using liquid chromatography–mass spectrometry), bsh and baiCD qPCR, and a BSH enzyme activity assay to demonstrate differences in the gut microbiota and bile metabolism in stool samples from healthy and antibiotic-exposed individuals