Noggin suppression decreases BMP‐2‐induced osteogenesis of human bone marrow‐derived mesenchymal stem cells <i>In Vitro</i>
Bibliographic record
Abstract
Numerous studies with rodent cells and animal models indicate that noggin inhibits osteogenesis by antagonizing bone morphogenetic proteins (BMPs); however, the effect of noggin on osteogenesis of human cells remains ambiguous. This study aims to examine the effects of noggin suppression on viability and BMP-2-induced osteogenic differentiation of human bone marrow-derived mesenchymal stem cells (MSCs) in vitro. Noggin expression in human MSCs was suppressed by noggin-specific small interfering RNA (siRNA), and viability of human MSCs was determined by measuring the mitochondrial dehydrogenase activity, cellular DNA content and protein amount. The BMP-2-induced osteogenic differentiation of human MSCs was assessed by analyzing the expression levels of several osteoblastic genes, enzymatic alkaline phosphatase (ALP) activity and calcification. Our study showed that noggin suppression significantly decreased human MSC metabolism and DNA content on Days 3 and 6, and decreased total protein amount on Day 14. Noggin suppression also reduced the expression levels of osteoblastic genes, ALP, integrin-binding sialoprotein (IBSP), muscle segment homeobox gene (MSX2), osteocalcin (OC), osteopontin (OPN), and runt-related transcription factor-2 (RUNX2). Significantly decreased enzymatic ALP activity in noggin-suppressed group was evident. Moreover, noggin suppression decreased calcium deposits by BMP-2-induced osteoblasts. Collectively, this study showed that noggin suppression decreased viability and BMP-2-induced osteogenic differentiation of human MSCs, which suggests that noggin is stimulatory to osteogenesis of human MSCs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".