Bibliographic record
Abstract
The human skeleton serves several functions for the body: support, locomotion, protection of vital organs, and housing of bone marrow. Bone remodeling is the result of the interactions of multiple elements, including osteoblasts, osteoclasts, hormones, growth factors, and cytokines, the end result being the maintenance of the bone architecture and to maintain systemic calcium homeostasis. In early life, a careful balance exists between bone formation by osteoblasts and bone resorption by osteoclasts. With aging, the process of coupled bone formation is affected by the reduction of osteoblast differentiation, activity, and life span which is further potentiated in the perimenopausal years with hormone deprivation and increased osteoclast activity. Age-related bone loss is thus not only a consequence of hormone deprivation, but also the result of changes in bone formation and cell-cell interactions with a unique pathophysiology. In this review, we describe the cellular and metabolic changes associated with aging bone and present recent evidence regarding cell differentiation within the bone marrow. We also consider the mechanism of programmed cell death, apoptosis, as being an important determinant of aging in bone as well as describe possible future interventions to prolong the life span of osteoblasts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".