LIF Inhibits Osteoblast Differentiation at Least in Part by Regulation of HAS2 and Its Product Hyaluronan
Bibliographic record
Abstract
UNLABELLED: LIF arrests osteogenesis in fetal rat calvaria cells in a differentiation stage-specific manner. Differential display identified HAS2 as a LIF-induced gene and its product, HA, modulated osteoblast differentiation similarly to LIF. Our data suggest that LIF arrests osteoblast differentiation by altering HA content of the extracellular matrix. INTRODUCTION: Leukemia inhibitory factor (LIF) elicits both anabolic and catabolic effects on bone. We previously showed in the fetal rat calvaria (RC) cell system that LIF inhibits osteoblast differentiation at the late osteoprogenitor/early osteoblast stage. MATERIALS AND METHODS: To uncover potential molecular mediators of this inhibitory activity, we used a positive-negative genome-wide differential display screen to identify LIF-induced changes in the developing osteoblast transcriptome. RESULTS: Although LIF signaling is active throughout the RC cell proliferation-differentiation sequence, only a relatively small number of genes, in several different functional clusters, are modulated by LIF specifically during the LIF-sensitive inhibitory time window. Based on their known and predicted functions, most of the LIF-regulated genes identified are plausible candidates to be involved in the LIF-induced arrest of osteoprogenitor differentiation. To test this hypothesis, we further analyzed the function of one of the genes identified, hyaluronan synthase 2 (HAS2), in the LIF-induced inhibition. Synthesis of hyaluronan (HA), the product of HAS enzymatic activity, was stimulated by LIF and mimicked the HAS2 expression profile, with highest expression in early/proliferative and late/maturing cultures and lowest levels in intermediate/late osteoprogenitor-early osteoblast cultures. Exogenously added high molecular weight HA, the product of HAS2, dose-dependently inhibited osteoblast differentiation, with pulse-treatment effective in the same differentiation stage-specific inhibitory window as seen with LIF. In addition, however, pulse treatment with HA in early cultures slightly increased bone nodule formation. Treatment with hyaluronidase, on the other hand, stimulated bone nodule formation in early cultures but caused a small dose-dependent inhibition of osteoblast differentiation in the LIF- and HA-sensitive late time window. CONCLUSIONS: Together the data suggest that osteoblast differentiation is acutely sensitive to HA levels and that LIF inhibits osteoblast development at least in part by stimulating high molecular weight HA synthesis through HAS2.
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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 | 0.001 | 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) | 0.000 | 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".