
IntroductionThis study investigated the effects of a compound preparation combining Lycium barbarum and probiotics (LB-Pro) on chemotherapy-induced cancer-related fatigue (CRF) in a murine model. The aim was to explore potential mechanisms related to the gut microbiota-metabolic axis.Materials and methodsA CRF model was established in C57BL/6NCr mice using 5-fluorouracil. Mice were divided into four groups receiving varying concentrations of LB-Pro. Over 14 days, interventions were administered, followed by treadmill exhaustion tests to assess fatigue levels. Body weight, serum biomarkers (TNF-α, GSH-Px, NAD-MDH, SOD), and gut microbiota composition were analyzed to evaluate physiological and metabolic changes.ResultsAdministration of medium- and high-concentration LB-Pro significantly improved fatigue-related outcomes, including prolonged exhaustion times and enhanced antioxidant enzyme activities, compared to the control group. Low-concentration LB-Pro showed limited efficacy. Gut microbiota analysis revealed alterations in microbial composition, including enrichment of short-chain fatty acid-producing taxa, and metabolic pathways associated with energy metabolism and antioxidant defense were upregulated in probiotic-treated groups.ConclusionLB-Pro alleviated chemotherapy-induced CRF in mice, likely through modulation of gut microbiota and enhancement of mitochondrial energy metabolism and antioxidant systems. These findings highlight the potential of integrative approaches combining traditional Chinese medicine and probiotics for managing CRF, emphasizing the gut microbiota-metabolic axis as a key therapeutic target.
Lycium barbarum, probiotics, gut microbiota, Nutrition. Foods and food supply, TX341-641, cancer-related fatigue, chemotherapy, Nutrition
Lycium barbarum, probiotics, gut microbiota, Nutrition. Foods and food supply, TX341-641, cancer-related fatigue, chemotherapy, Nutrition
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
