Phosphoproteomic analysis of chondrocytes after short-term exposure to inorganic polyphosphate
Bibliographic record
Abstract
Abstract Osteoarthritis is a debilitating disease of the joint that affects over 230 million people worldwide. Currently there are no treatments that slow the progression of this disease. For these reasons, new biological treatment options are currently being explored. Inorganic polyphosphates are naturally occurring biological molecules that have an anabolic effect on chondrocytes grown in vitro in the presence of Ca 2+ . We hypothesized that when examining significant changes in protein phosphorylation, key candidates would emerge that could help to elucidate the anabolic effects of polyphosphate on chondrocytes. Therefore, we conducted a large-scale quantitative proteomic and phosphoproteomic study of bovine primary articular chondrocytes after 30-minute treatment with inorganic polyphosphate and Ca 2+ . Mass spectrometry identified more than 6000 phosphorylation sites on ∼1600 chondrocyte phosphoproteins while proteomic analysis detected approximately 4100 proteins. Analysis of the data revealed a swift and dynamic response to polyphosphate after 30 minutes. What emerged from the list of proteins most affected by the treatment were proteins with key roles in chondrogenesis including TNC, IGFBP-5, and CTGF, indicating that polyphosphate plays an important role in chondrocyte metabolism. This phosphoproteome serves as a meaningful resource to help elucidate the molecular events that contribute to extracellular matrix production in cartilage.
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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".