Investigation of region-specific effects of pepsin-digested decellularized meniscus on human adipose-derived stromal cells within alginate hydrogels
Bibliographic record
Abstract
Abstract Meniscus tears are one of the most common musculoskeletal injuries, but treatment options remain limited. The meniscus can be divided into distinct inner and outer regions based on differences in the tissue structure and composition. Recognizing that the extracellular matrix (ECM) provides cell-instructive cues that can direct cell differentiation, the current study investigated the effects of incorporating region-specific ECM derived from decellularized meniscus on the viability, growth, and lineage-specific differentiation of human adipose-derived stromal cells (ASCs) encapsulated in alginate beads. The first phase of research focused on validating a novel decellularization protocol for porcine meniscus, which demonstrated the effective removal of cellular content while preserving key ECM constituents including glycosaminoglycans (GAGs) in both the inner and outer meniscus regions. Subsequently, the decellularized inner meniscus (DIM) and decellularized outer meniscus (DOM) were digested with pepsin and combined with a propriety alginate formulation to enable rapid cell encapsulation under mild conditions. Viability staining confirmed that encapsulated human ASCs remained highly viable over 28 days in culture in proliferation or chondrogenic differentiation media. Under both media conditions, the ASC density was significantly higher in the alginate beads incorporating DIM or DOM as compared to alginate alone controls at 28 days. In addition, gene expression analysis and immunofluorescence staining supported that the incorporation of the pepsin-digested ECM within the alginate enhanced fibrochondrogenic marker expression in the samples cultured in chondrogenic differentiation medium. Qualitatively, more intense staining for collagen types I and II were observed within the beads incorporating DOM as compared to DIM, supporting that the formulations had varying effects. Overall, these studies provide new insight supporting that region-specific meniscus ECM can be harnessed to direct cell phenotype and function towards the goal of developing tissue-specific bioinks for tissue-engineering applications.
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 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) | 0.000 | 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".