ReviewCellular and molecular gastroenterology and hepatology2026
Proteases and Abdominal Pain-Old Dog, New (Microbial) Tricks.
Review in Cellular and molecular gastroenterology and hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed.
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Authors and funding
3 authors.
Funding
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Abstract
Chronic abdominal pain is a debilitating symptom associated with various gastrointestinal (GI) conditions, such as inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). Unfortunately, the pathophysiology of chronic abdominal pain is poorly understood, leading to inadequate clinical treatments. Proteases have emerged as critical modulators of nociception through the activation or inactivation of Protease-Activated Receptors (PARs) on pain sensing neurons (nociceptors). Traditionally viewed as exclusively host-derived, recent work highlights the gut microbiota as a significant source of proteases and demonstrates that a delicate equilibrium exists between pro-nociceptive and anti-nociceptive signalling in IBS and IBD. Consequently, dysbiosis of the gut microbiota may contribute to the pathogenesis of chronic pain in these disorders. This review outlines the mechanisms by which host and microbial proteases contribute to the pathogenesis of chronic abdominal pain, emphasizing recent advancements in microbial involvement.
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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.