A by-product of glutathione production in cancer cells may cause disruption in bone metabolic processesThis review is one of a selection of papers published in a Special Issue on Oxidative Stress in Health and Disease.
Bibliographic record
Abstract
Bone is a frequent site for metastasis of breast and prostate cancers, often resulting in pathologic changes in bone metabolism and severe pain. The mechanisms involved are not well understood, but tumour cells may release factors that interfere with bone homeostasis. Several observations have led us to hypothesize that the functional disruptions in bone metastasis are the result of a biological process common to many cell types. The high metabolic activity characteristic of cancer cells often upregulates oxidative stress protection mechanisms such as the antioxidant molecule glutathione. In maintaining redox balance, this normal metabolic response may result in unintended pathologic effects in certain sensitive organ sites. Malignant glioma cells kill surrounding neurons in the brain specifically by secreting the amino acid glutamate, an obligatory waste product of glutathione synthesis. We suggest that glutamate release is a plausible mechanism that may account for the pathologic changes in bone metastasis, since bone, like brain, is also highly sensitive to glutamatergic disruption. This report reviews the available evidence to draw a mechanistic connection between tumour cell oxidative stress and the pathology seen in patients with 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".