Nobiletin

Slow transit constipation (STC) is a functional gastrointestinal disorder with complex etiology and limited therapeutic options. Nobiletin (NOB), a natural polymethoxyflavone derived from citrus, exhibits multiple pharmacological activities. However, its effects on STC remain unknown. Using a loperamide-induced STC mouse model, this study demonstrates that NOB administration significantly alleviates constipation symptoms, improves intestinal propulsion, and restores plasma neurotransmitter balance. NOB also enhanced intestinal barrier function by upregulating colonic MUC2 and tight junction proteins (Claudin-1, Occludin). Importantly, it is reported for the first time that NOB differentially modulates bile acid signaling along the gut axis: it normalized ileal bile acid reabsorption via the FXR/TGR5-ASBT pathway, while enhancing colonic motility through the FXR/TGR5/5-HT3R axis, which is a dual-regulatory mechanism that has not been previously described in the context of STC. In addition, NOB modulated gut microbiota composition by reducing the Firmicutes to Bacteroidota ratio (F/B ratio) and enriching beneficial bacteria such as Alloprevotella and Bacteroides. These results underscore NOB's multitarget and gut axis-coordinated role in alleviating STC, highlighting its promise as a novel therapeutic agent and providing new mechanistic insights into bile acid signaling in constipation.

This study employed UHPLC-QTOF-MS-based untargeted metabolomics, integrated with chemometrics and machine learning, to discriminate between varieties of Citri Reticulatae Pericarpium (CRP). To identify specific markers between each pair of varieties more precisely, a progressive screening strategy was adopted. Initially, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) screened 46 universal differential metabolites across the four varieties. Subsequently, pairwise orthogonal partial least squares discriminant analysis (OPLS-DA) applied to these universal metabolites facilitated the detection of specific differential metabolites. LC-MS analysis identified a total of 268 metabolites. PCA revealed significant metabolic differences among the four CRP varieties, while PLS-DA screened 46 universal differential metabolites (VIP > 1). 9 machine learning discrimination models constructed from these 46 metabolites exhibited excellent performance (with accuracy, etc. > 0.9461) and successfully discriminated externally validated CRP samples from different varieties with a 100% recognition rate. Further, pairwise OPLS-DA based on the universal differential metabolites screened out 10 universal specific differential metabolites (VIP > 1), including 5-O-demethylnobiletin. Notably, nobiletin distinguished pharmacopoeia from non-pharmacopoeia CRP varieties. Finally, integrative analyses linked these findings to their biological significance, attributing differential flavonoid accumulation among CRP varieties to molecular evolutionary mechanisms driven by genetic background-dependent methylation and glycosylation processes. This study demonstrates the considerable potential of UHPLCQTOF-MS-based untargeted metabolomics for distinguishing CRP varieties, providing a useful reference for market quality control and clinical practice.