Novel Functions of the Matricellular Proteins Osteopontin and Osteonectin/SPARC
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Osteopontin (OPN) and osteonectin/SPARC (ON/SPARC) are prominent matricellular components of the extracellular matrix of mineralized tissues of bones and teeth in which they can regulate the formation and growth of hydroxyapatite crystals and influence a variety of cell activities. OPN regulates cell responses through several integrin receptors and is also a ligand for the CD44 receptor, through which it acts as a chemoattractant. Although a cell-surface receptor for SPARC has not been identified it can block cell-cell and cell-matrix interactions and inhibit cell migration and chemotaxis. OPN and SPARC also appear to function inside cells. Thus, OPN appears to exist in association with the CD44 receptor inside migratory cells, while intracellular SPARC is associated with axonemal tubulin in ciliated epithelial cells. Analyses of fibroblasts and peritoneal macrophages from OPN-null and CD44-null cells show impaired functionality involving migration and cell fusion required for osteoclast formation, while disruption of SPARC expression leads to developmental defects in Xenopus. To gain further insights into the intracellular functions of OPN and SPARC, we have used the yeast two-hybrid system to identify potential interacting molecules. Using full-length SPARC as bait the carboxy-terminal domain, which contains two EF-hand, high-affinity binding sites, was found to have transcriptional activity, while several novel proteins that interact with the amino-terminal domains of SPARC and full-length OPN have been identified. The identification of OPN and SPARC inside specialized cells introduces a novel concept in cellular regulation by matricellular proteins.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it