At the Crossroads of the Adipocyte and Osteoclast Differentiation Programs: Future Therapeutic Perspectives
Bibliographic record
Abstract
The coordinated development and function of bone-forming (osteoblasts) and bone-resorbing (osteoclasts) cells is critical for the maintenance of skeletal integrity and calcium homeostasis. An enhanced adipogenic versus osteogenic potential of bone marrow mesenchymal stem cells (MSCs) has been linked to bone loss associated with diseases such as diabetes mellitus, as well as aging and postmenopause. In addition to an inherent decrease in bone formation due to reduced osteoblast numbers, recent experimental evidence indicates that an increase in bone marrow adipocytes contributes to a disproportionate increase in osteoclast formation. Therefore, a potential strategy for therapeutic intervention in chronic bone loss disorders such as osteoporosis is to interfere with the pro-osteoclastogenic influence of marrow adipocytes. However, application of this approach is limited by the extremely complex regulatory processes in the osteoclastogenic program. For example, key regulators of osteoclastogenesis such as the receptor activator of nuclear factor-kappaB ligand (RANKL) and the soluble decoy receptor osteoprotegerin (OPG) are not only secreted by both osteoblasts and adipocytes, but are also regulated through several cytokines produced by these cell types. In this context, biologically active signaling molecules secreted from bone marrow adipocytes, such as chemerin, adiponectin, leptin, visfatin and resistin, can have a profound influence on the osteoclast differentiation program of hematopoietic stem cells (HSCs), and thus, hold therapeutic potential under disease conditions. In addition to these paracrine signals, adipogenic transcription factors including CCAAT/enhancer binding protein alpha (C/EBPα), C/EBP beta (C/EBPβ) and peroxisome proliferator-associated receptor gamma (PPARγ) are also expressed by osteoclastogenic cells. However, in contrast to MSCs, activation of these adipogenic transcription factors in HSCs promotes the differentiation of osteoclast precursors into mature osteoclasts. Herein, we discuss the molecular mechanisms that link adipogenic signaling molecules and transcription factors to the osteoclast differentiation program and highlight therapeutic strategies targeting these mechanisms for promoting bone homeostasis.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".