Milk proteins and their derived peptides on bone health: Biological functions, mechanisms, and prospects
Bibliographic record
Abstract
Bone is a dynamic organ under constant metabolism (or remodeling), where a delicate balance between bone resorption and bone formation is maintained. Disruption of this coordinated bone remodeling results in bone diseases, such as osteoporosis, the most common bone disorder characterized by decreased bone mineral density and microarchitectural deterioration. Epidemiological and clinical evidence support that consumption of dairy products is beneficial for bone health; this benefit is often attributed to the presence of calcium, the physiological contributions of milk proteins on bone metabolism, however, are underestimated. Emerging evidence highlighted that not only milk proteins (including individual milk proteins) but also their derived peptides positively regulate bone remodeling and attenuate bone loss, via the regulation of cellular markers and signaling of osteoblasts and osteoclasts. This article aims to review current knowledge about the roles of milk proteins, with an emphasis on individual milk proteins, bioactive peptides derived from milk proteins, and effect of milk processing in particular fermentation, on bone metabolism, to highlight the potential uses of milk proteins in the prevention and treatment of osteoporosis, and, to discuss the knowledge gap and to recommend future research directions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".