50 resultados para Gut
Resumo:
UNLABELLED A high proportion of gut and bronchial neuroendocrine tumors (NETs) overexpresses somatostatin receptors, especially the sst2 subtype. It has also recently been observed that incretin receptors, namely glucagonlike peptide 1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) receptors, can be overexpressed in gut and bronchial NETs. However, because not all tumors can express these receptors in sufficient amounts, in vivo imaging with a single radioligand may not always be successful. We therefore evaluated with in vitro methods whether a cocktail of radioligands targeting these 3 receptors would improve tumor labeling. METHODS In vitro receptor autoradiography was performed on 55 NETs, comparing in each successive section of tumor the binding with a single radioligand, either (125)I-Tyr(3)-octreotide, (125)I-GLP-1(7-36)amide, or (125)I-GIP(1-30), with the binding using a cocktail of all 3 radioligands, given concomitantly under identical experimental conditions. RESULTS Using the cocktail of radioligands, all tumors without exception showed moderate to very high binding, with a receptor density corresponding to 1,000-10,000 dpm/mg of tissue; conversely, single-ligand binding, although identifying most tumors as receptor-positive, failed to detect receptors or measured only a low density of receptors below 1,000 dpm/mg in a significant number of tumors. In addition, the cocktail of radioligands always provided a homogeneous labeling of the whole tumor, whereas single radioligands occasionally showed heterogeneous labeling. CONCLUSION The study suggests that the use of a cocktail of 3 radioligands binding to somatostatin receptors, GLP-1 receptors, and GIP receptors would allow detecting virtually all NETs and labeling them homogeneously in vivo, representing a significant improvement for imaging and therapy in NETs.
Resumo:
BACKGROUND/AIMS Important characteristics of neuroendocrine neoplasms (NEN) for prognosis and therapeutic decisions are the MIB-1 proliferative index (tumor grade) and tumor stage. Moreover, these tumors express peptide hormone receptors like somatostatin and gastric inhibitory peptide (GIP) receptors which represent important established and potential future targets, respectively, for molecular imaging and radiotherapy. However, the interrelation between tumor proliferation, stage, and peptide receptor amounts has never been assessed. METHODS In 114 gastrointestinal and bronchopulmonary NEN, the proliferative rate assessed with MIB-1 immunohistochemistry and tumor stage were compared with the somatostatin type 2 receptor (sst2) and GIP receptor expression measured quantitatively with in vitro receptor autoradiography. RESULTS NEN generally showed high sst2 and GIP receptor expression. GIP receptor but not sst2 expression correlated with the MIB-1 index. GIP receptor levels gradually increased in a subset of insulinomas and nonfunctioning pancreatic NEN, and decreased in ileal and bronchopulmonary NEN with increasing MIB-1 rate. MIB-1 levels were identified, above which GIP receptor levels were consistently high or low. These MIB-1 levels were clearly different from those defining tumor grade. In grade 3 NEN, GIP receptor levels were always low, while sst2 levels were variable and sometimes extremely high. Conversely, sst2 expression correlated more frequently with tumor stage than GIP receptor expression, with metastasized NEN showing higher sst2 levels than localized tumors. CONCLUSIONS sst2, a clinically crucial molecular target, shows variable and unpredictable expression in NEN irrespective of tumor grade. Therefore, each NEN should be tested for sst2 if clinical applications with somatostatin analogs are considered. Conversely, the potential future role of GIP receptors as molecular targets in NEN may be dependent on the MIB-1 level.
Resumo:
In this chapter the basic aspects helping to understand the microbiome in terms of quantity, diversity, complexity, function, and interaction with the host are discussed. First the nomenclature, definitions of taxa, and measures of diversity as well as methods to unravel this kingdom are outlined. A brief summary on its physiological relevance for general health and the functions exerted specifically by the microbiome is presented. Differences in the composition of the microbiome along the gastrointestinal tract and across the gut wall and its interindividual variations, enterotypes, and stability are highlighted. The reader will be familiarized with all different modulators impacting on the microbiome, namely, intrinsic and extrinsic factors. Intrinsic factors include gastrointestinal secretions (gastric acid, bile, pancreatic juice, mucus), antimicrobial peptides, motility, enteric nervous system, and host genotype. Extrinsic factors are mainly dietary choices, hygiene, stress, alcohol consumption, exercise, and medications. The second part of the chapter focuses on quantitative and qualitative changes in microbiome in liver cirrhosis. The mechanisms contributing to dysbiosis, small intestinal bacterial overgrowth, and bacterial translocation are delineated underscoring their role for the liver-gut axis.
Resumo:
Microbial functions in the host physiology are a result of the microbiota-host co-evolution. We show that cold exposure leads to marked shift of the microbiota composition, referred to as cold microbiota. Transplantation of the cold microbiota to germ-free mice is sufficient to increase insulin sensitivity of the host and enable tolerance to cold partly by promoting the white fat browning, leading to increased energy expenditure and fat loss. During prolonged cold, however, the body weight loss is attenuated, caused by adaptive mechanisms maximizing caloric uptake and increasing intestinal, villi, and microvilli lengths. This increased absorptive surface is transferable with the cold microbiota, leading to altered intestinal gene expression promoting tissue remodeling and suppression of apoptosis-the effect diminished by co-transplanting the most cold-downregulated strain Akkermansia muciniphila during the cold microbiota transfer. Our results demonstrate the microbiota as a key factor orchestrating the overall energy homeostasis during increased demand.