ReviewMetabolites2022
Targeting the Gut in Obesity: Signals from the Inner Surface.
Review in Metabolites, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Selective modulation of murine intestinal MAmerican journal of physiology. Cell physiology · 2026Article
- Effects of an Innovative High-Fat Diet on Intestinal Structure, Barrier Integrity, and Inflammation in a Zebrafish Model of Visceral Obesity.International journal of molecular sciences · 2024Article
- The Possible Involvement of Glucagon-like Peptide-2 in the Regulation of Food Intake through the Gut-Brain Axis.Nutrients · 2024Review
- Novel Insights into the Physiology of Nutrient Sensing and Gut-Brain Communication in Surgical and Experimental Obesity Therapy.Obesity surgery · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Obesity is caused by prolonged energy surplus. Current anti-obesity medications are mostly centralized around the energy input part of the energy balance equation by increasing satiety and reducing appetite. Our gastrointestinal tract is a key organ for regulation of food intake and supplies a tremendous number of circulating signals that modulate the activity of appetite-regulating areas of the brain by either direct interaction or through the vagus nerve. Intestinally derived messengers are manifold and include absorbed nutrients, microbial metabolites, gut hormones and other enterokines, collectively comprising a fine-tuned signalling system to the brain. After a meal, nutrients directly interact with appetite-inhibiting areas of the brain and induce satiety. However, overall feeding behaviour also depends on secretion of gut hormones produced by highly specialized and sensitive enteroendocrine cells. Moreover, circulating microbial metabolites and their interactions with enteroendocrine cells further contribute to the regulation of feeding patterns. Current therapies exploiting the appetite-regulating properties of the gut are based on chemically modified versions of the gut hormone, glucagon-like peptide-1 (GLP-1) or on inhibitors of the primary GLP-1 inactivating enzyme, dipeptidyl peptidase-4 (DPP-4). The effectiveness of these approaches shows that that the gut is a promising target for therapeutic interventions to achieve significant weigh loss. We believe that increasing understanding of the functionality of the intestinal epithelium and new delivery systems will help develop selective and safe gut-based therapeutic strategies for improved obesity treatment in the future. Here, we provide an overview of the major homeostatic appetite-regulating signals generated by the intestinal epithelial cells and how these signals may be harnessed to treat obesity by pharmacological means.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.