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The gut hormone oxyntomodulin (OXM) causes weight loss by reducing appetite and increasing energy expenditure. Several analogues are being developed to treat obesity. Exactly how oxyntomodulin works, however, remains controversial. OXM can activate both glucagon and GLP-1 receptors but no specific receptor has been identified. It is thought that the anorectic effect occurs predominantly through GLP-1 receptor activation but, to date, it has not been formally confirmed which receptor is responsible for the increased energy expenditure. We developed OX-SR, a sustained-release OXM analogue. It produces a significant and sustained increase in energy expenditure in rats as measured by indirect calorimetry. We now show that this increase in energy expenditure occurs via activation of the glucagon receptor. Blockade of the GLP-1 receptor with Exendin 9-39 does not block the increase in oxygen consumption caused by OX-SR. However, when activity at the glucagon receptor is lost, there is no increase in energy expenditure. Glucagon receptor activity therefore appears to be essential for OX-SR's effects on energy expenditure. The development of future 'dual agonist' analogues will require careful balancing of GLP-1 and glucagon receptor activities to obtain optimal effects.
Pubmed ID: 29680267
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 2nd, 2023. Sequence composition based classifier for metagenomic sequences. It works by capturing signatures of each sequence based on the sequence composition. Each sequence is modeled as a walk in a de Bruijn graph with underlying Markov chain properties. ClaMS captures stationary parameters of the underlying Markov chain as well as structural parameters of the underlying de Bruijn graph to form this signature. In practice, for each sequence to binned, such a signature is computed and matched to similar signatures computed for the training sets. The best match that also qualifies the normalized distance cut-off wins. In the case that the best match does not qualify this cut-off, the sequence remains un-binned.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentionsCell line CHO-K1 is a Spontaneously immortalized cell line with a species of origin Cricetulus griseus (Chinese hamster)
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