Role of ecto‐NTPDases on UDP‐sensitive P2Y<sub>6</sub>receptor activation during osteogenic differentiation of primary bone marrow stromal cells from postmenopausal women
Bibliographic record
Abstract
This study aimed at investigating the expression and function of uracil nucleotide-sensitive receptors (P2Y(2), P2Y(4), and P2Y(6)) on osteogenic differentiation of human bone marrow stromal cells (BMSCs) in culture. Bone marrow specimens were obtained from postmenopausal female patients (68 ± 5 years old, n = 18) undergoing total hip arthroplasty. UTP and UDP (100 µM) facilitated osteogenic differentiation of the cells measured as increases in alkaline phosphatase (ALP) activity, without affecting cell proliferation. Uracil nucleotides concentration-dependently increased [Ca(2+)](i) in BMSCs; their effects became less evident with time (7 > 21 days) of the cells in culture. Selective activation of P2Y(6) receptors with the stable UDP analog, PSB 0474, mimicked the effects of both UTP and UDP, whereas UTPγS was devoid of effect. Selective blockade of P2Y(6) receptors with MRS 2578 prevented [Ca(2+)](i) rises and osteogenic differentiation caused by UDP at all culture time points. BMSCs are immunoreactive against P2Y(2), P2Y(4), and P2Y(6) receptors. While the expression of P2Y(6) receptors remained fairly constant (7∼21 days), P2Y(2) and P2Y(4) became evident only in less proliferative and more differentiated cultures (7 < 21 days). The rate of extracellular UTP and UDP inactivation was higher in less proliferative and more differentiated cell populations. Immunoreactivity against NTPDase1, -2, and -3 rises as cells differentiate (7 < 21 days). Data show that uracil nucleotides are important regulators of osteogenic cells differentiation predominantly through the activation of UDP-sensitive P2Y(6) receptors coupled to increases in [Ca(2+)](i) . Endogenous actions of uracil nucleotides may be balanced through specific NTPDases determining whether osteoblast progenitors are driven into proliferation or differentiation.
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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) | 0.000 | 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) | 0.001 | 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 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".