Scavenger receptor class B, type I (<i>Scarb1</i>) deficiency promotes osteoblastogenesis but stunts terminal osteocyte differentiation
Bibliographic record
Abstract
Scavenger receptor class B type I (SR-BI), the Scarb1 gene product, is a high-density lipoprotein (HDL) receptor which was shown to influence bone metabolism. Its absence in mice is associated with alterations of the glucocorticoid/adrenocorticotropic hormone axis, and translated in high bone mass and enhanced bone formation. Since the cellular alterations underlying the enhanced bone formation remain unknown, we investigated Scarb1-deficient marrow stromal cells (MSC) behavior in vitro. No difference in HDL3, cholesteryl ester (CE) or estradiol (E) association/binding was measured between Scarb1-null and wild-type (WT) cells. Scarb1 genic expression was down-regulated twofold following osteogenic treatment. Neither WT nor null cell proliferation was influenced by HDL3 exposure whereas this condition decreased genic expression of osteoblastic marker osterix (Sp7), and osteocyte markers sclerostin (Sost) and dentin matrix protein 1 (Dmp1) independently of genotype. Sost and Dmp1 basal expression in null cells was 40% and 50% that of WT cells; accordingly, osteocyte density was 20% lower in vertebrae from Scarb1-null mice. Genic expression of co-receptors for Wnt signaling, namely LDL-related protein (Lrp) 5 and Lrp8, was increased, respectively, by two- and threefold, and of transcription target-genes axis inhibition protein 2 (Axin2) and lymphoid enhancer-binding factor 1 (Lef1) over threefold. Gene expression of Wnt signaling agonist Wnt5a and of the antagonist dickkopfs-related protein 1 (Dkk1) were found to be increased 10- to 20-fold in null MSC. These data suggest alterations of Wnt pathways in Scarb1-deficient MSC potentially explaining their enhanced function, hence contributing to the high bone mass observed in these mice.
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 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 | 0.000 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".