Recapitulating bone development events in a customised bioreactor through interplay of oxygen tension, medium pH, and systematic differentiation approaches
Bibliographic record
Abstract
Bone development and homeostasis are intricate processes that require co-existence and dynamic interactions among multiple cell types. However, controlled dynamic niches that derive and support stable propagation of these cells from single stem cell source is not sustainable in conventional culturing vessels. In bioreactor cultures that support dynamic niches, the limited source and stability of growth factors are often a major limiting factor for long-term in vitro cultures. Hence, alternative growth factor-free differentiation approaches are designed and their efficacy to achieve different osteochondral cell types is investigated. Briefly, a dynamic niche is achieved by varying medium pH, oxygen tension (pO2) distribution in bioreactor, initiating chondrogenic differentiation with chondroitin sulphate A (CSA), and implementing systematic differentiation regimes. In this study, we demonstrated that CSA is a potent chondrogenic inducer, specifically in combination with acidic medium and low pO2. Further, endochondral ossification is recapitulated through a systematic chondrogenic–osteogenic (ch-os) differentiation regime, and multiple osteochondral cell types are derived. Chondrogenic hypertrophy was also enhanced specifically in high pO2 regions. Consequently, mineralised constructs with higher structural integrity, volume, and tailored dimensions are achieved. In contrast, a continuous osteogenic differentiation regime (os-os) has derived compact and dense constructs, whereas a continuous chondrogenic differentiation regime (ch-ch) has attenuated construct mineralisation and impaired development. In conclusion, a growth factor-free differentiation approach is achieved through interplay of pO2, medium pH, and systematic differentiation regimes. The controlled dynamic niches have recapitulated endochondral ossification and can potentially be exploited to derive larger bone constructs with near physiological properties.
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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) | 0.001 | 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 | 0.001 |
| 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 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".