Exosome-targeted delivery of METTL14 regulates NFATc1 m6A methylation levels to correct osteoclast-induced bone resorption
Bibliographic record
Abstract
Osteoporosis has a profound influence on public health. First-line bisphosphonates often cause osteonecrosis of the jaw meanwhile inhibiting osteoclasts. Therefore, it is important to develop effective treatments. The results of this study showed that the increased level of NFATc1 m6A methylation caused by zoledronic acid (ZOL), with 4249A as the functional site, is highly correlated with the decreased bone resorption of osteoclasts. Upstream, METTL14 regulates osteoclast bone absorption through the methylation functional site of NFATc1. Downstream, YTHDF1 and YTHDF2 show antagonistic effects on the post-transcriptional regulation of NFATc1 after the m6A methylation level is elevated by METTL14. In this study, meRIP-Seq, luciferase reporter assays, meRIP and other methods were used to elucidate the NFATc1 regulatory mechanism of osteoclasts from the perspective of RNA methylation. In addition, EphA2 overexpression on exosomes is an effective biological method for targeted delivery of METTL14 into osteoclasts. Importantly, this study shows that METTL14 released by exosomes can increase the m6A methylation level of NFATc1 to inhibit osteoclasts, help postmenopausal osteoporosis patients preserve bone mass, and avoid triggering osteonecrosis of the jaw, thus becoming a new bioactive molecule for the treatment of osteoporosis.
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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".