Extracellular glutamate alters mature osteoclast and osteoblast functions
Bibliographic record
Abstract
Glutamatergic intercellular communication is involved in many aspects of metabolic homeostasis in normal bone. In bone metastasis, the balance between bone formation and degradation is disrupted. Although the responsible mechanisms are not clear, we have previously identified that cancer cell lines used in bone tumour models secrete glutamate, suggesting that tumour-derived glutamate may disrupt sensitive signalling systems in bone. This study examines the role of glutamate in mature osteoclastic bone resorption, osteoblast differentiation, and bone nodule formation. Glutamate was found to have no effect on the survival or activity of mature osteoclasts, although glutamate transporter inhibition and receptor blockade increased the number of bone resorption pits. Furthermore, transporter inhibition increased the area of resorbed bone while significantly decreasing the number of osteoclasts. Alkaline phosphatase activity and extracellular matrix mineralization were used as measurements of osteoblast differentiation. Glutamate significantly increased osteoblast differentiation and mineralization, but transport inhibitors had no effect. These studies support earlier findings suggesting that glutamate may be more important for osteoclastogenesis than for osteoclast proliferation or functions. Since glutamate is capable of changing the differentiation and activities of both osteoclast and osteoblast cell types in bone, it is reasonable to postulate that tumour-derived glutamate may impact bone homeostasis in bone metastasis.
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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) | 0.002 | 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".