ArticleScientific reports2026
Uncovering the mechanisms of Jingui Shenqi pill alleviates type 2 diabetic osteoporosis using a combined network pharmacology and metabolomics approach.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Molecular mechanisms and preclinical evidence of natural products in diabetic osteoporosis: a review.Frontiers in endocrinology · 2026Review
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
Abstract
Diabetic osteoporosis (DOP) is a long-term musculoskeletal complication of type 2 diabetes mellitus (T2DM) in the population. One well-known traditional Chinese medicine(TCM) medication that works effectively for DOP is Jingui Shenqi Pill (JGSQP). However, more research is needed to understand the underlying mechanisms. In this study, both the potential active targets and therapeutic mechanisms of JGSQP on DOP are explored by integrated analysis of metabolomics and network pharmacology. The metabolic pathways closely linked to the function of JGSQP, and differential metabolites were validated using plasma metabolomics. Subsequently, network pharmacology was utilized to reveal additional essential targets against DOP caused by JGSQP. JGSQP can significantly reduce bone loss, injury to trabecular bone tissue, and aberrant glucose metabolism in DOP mice. Furthermore, JGSQP also successfully restored the MC3T3-E1 cells' impoverished proliferation brought on by excessive hyperglycemia. Using network pharmacology analysis in conjunction with liquid chromatography coupled with liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-Q-TOF/MS), 143 JGSQP components-or 277 targets-were found. 3168 targets were connected to DOP. Among them, 152 targets overlapped with known DOP treatment-related targets as potential targets for JGSQP treatment of DOP. TP53, TNF, IL-1β, and NFKBIA2 were identified by protein-protein interaction (PPI) analysis as possible targets. Moreover, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the AGE-RAGE signaling pathway and NF-κB signaling pathway in diabetic complications were the key pathways through which JGSQP exerts its therapeutic effects on DOP. The compound reaction-enzyme-gene network diagram was created by enriching the major metabolic pathways of tryptophan metabolism and amino sugar metabolism. Finally, further experimental data verified that JGSQP treatment could significantly reduce the expression levels of inflammatory factors IL-1β and IL-6, and AGE, NFKB in MC3T3-E1 cells. JGSQP can reduce DOP by regulating the pathway to reduce inflammation and improve metabolism. The study offers a theoretical foundation for the investigation of TCM in the treatment of DOP from various perspectives and uncovers the intricate mechanism of JGSQP in the treatment of DOP.
Indexed as
Identifiers
What Socratic 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 Socratic graph.