Lnc‐NTF3‐5 promotes osteogenic differentiation of maxillary sinus membrane stem cells via sponging miR‐93‐3p
Bibliographic record
Abstract
BACKGROUND: The function and the mechanism of long non-coding RNAs (lncRNAs) on the osteogenic differentiation of maxillary sinus membrane stem cells (MSMSCs) remain largely unknown. MATERIALS AND METHODS: The expression of lnc-NTF3-5 and Runt-related transcription factor 2 (RUNX2), Osterix (OSX), and Alkaline Phosphatase (ALP) was examined by quantitative real-time PCR (qRT-PCR) in MSMSCs during the process osteogenic differentiation. Then the function of lnc-NTF3-5 was evaluated by loss- and gain-of-function techniques, as well as qRT-PCR, western blot, and Alizarin Red staining. In addition, the microRNAs (miRNAs) sponge potential of lnc-NTF3-5 was assessed through RNA immunoprecipitation, dual luciferase reporter assay, and in vivo ectopic bone formation. RESULTS: Lnc-NTF3-5, RUNX2, OSX, and ALP increased alone with the differentiation. Inhibition of lnc-NTF3-5 decreased the expression of RUNX2, OSX, and ALP both at mRNA and protein levels. Alizarin red staining showed similar trend. In contrast, overexpression of lnc-NTF3-5 presented totally opposite effects. Besides, overexpression of lnc-NTF3-5 could decrease the expression of microRNA-93-3p (miR-93-3p). Enhance miR-93-3p could also inhibit the expression level of lnc-NTF3-5. RNA immunoprecipitation demonstrated that lnc-NTF3-5 is directly bound to miR-93-3p and dual luciferase reporter assay proved that miR-93-3p targets 3' UTR of RUNX2 to regulate its expression. Ultimately, in vivo bone formation study showed that lnc-NTF3-5 and miR-93-3p inhibitor co-transfection group displayed the strongest bone formation. CONCLUSIONS: The novel pathway lnc-NTF3-5/miR-93-3p/RUNX2 could regulate osteogenic differentiation of MSMSCs and might serve as a therapeutic target for bone regeneration in the posterior maxilla.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".