Aqueous extract of Sedum sarmentosum (SS-Ex) promotes bone formation and linear bone growth in a calcium/vitamin D-deficient mouse model
Bibliographic record
Abstract
Proper bone development during the growth phase is essential for achieving normal skeletal length, mineral density, and strength, which is regulated by growth hormones, vitamin D, and calcium. Deficiencies in these elements can impair skeletal formation, increasing the risk of disorders such as rickets and osteoporosis. Therefore, natural compounds with bone-supportive effects are of growing interest. Sedum sarmentosum (S. sarmentosum), a plant traditionally used in Korea to treat liver disorders, contains abundant vitamin C and calcium, however, its effects on bone development remain unclear. We found that oral administration of an aqueous extract of S. sarmentosum (SS-Ex) improved trabecular bone structure and bone mineral density in mice fed a calcium- and vitamin D-deficient diet. SS-Ex treated mice showed increased growth plate thickness and elevated serum levels of osteocalcin (Ocn), type I collagen alpha 1 (Col1a1), calcium, and calcitonin. In vitro, SS-Ex enhanced alkaline phosphatase (Alp) activity and promoted mineral deposition in MC3T3-E1 pre-osteoblasts. Additionally, SS-Ex upregulated osteogenic genes including runt-related transcription factor 2, osterix, Ocn, osteopontin, Alp, and Col1a1. Whereas mechanistically, SS-Ex downregulated the expression of dickkopf-related protein 1, a negative regulator of the wingless-type MMTV integration site (Wnt)/β-Catenin pathway, thereby activating Wnt3a/β-Catenin signaling. Moreover, SS-Ex upregulated the expression of bone morphogenetic protein 2 (Bmp2), further enhancing osteogenic signaling. These findings suggest that SS-Ex promotes osteoblast differentiation, supports linear bone growth via growth plate stimulation, and helps maintain calcium balance, indicating its potential as a natural agent for enhancing bone development during growth.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".