Development of a Model Bladder Extracellular Matrix Combining Disulfide Cross‐Linked Hyaluronan with Decellularized Bladder Tissue
Bibliographic record
Abstract
[Image: see text] In this work we investigate the feasibility of modifying porcine-derived BAM to include HA with a view to developing a model, artificial extracellular matrix for the study of bladder cell-matrix interactions. HA-DPTH was incorporated into BAM disks and then cross-linked oxidatively to a disulfide containing hydrogel. Disks were seeded with bladder smooth muscle cells (BSMC) and UEC under three culture configurations and incubated for 3, 7, and 14 d. At each time point, matrix contraction was measured, and media supernatants assayed for cell-secreted gelatinase activity. To evaluate cell adherence and organization, triple immunofluorescent labeling of cell nuclei, actin cytoskeleton, and focal contacts was performed. HA-modified BAM exhibited a significant increase in matrix contraction and induced a higher level of cell-secreted gelatinase activity compared to unmodified BAM. Immunofluorescent labeling demonstrated that BSMCs remained adherent to both scaffold types over time. The distribution and organization of the cytoskeleton and focal contacts did not appear to be altered by the presence of HA. Interestingly, cellular infiltration into modified BAM was evident by 7 d and continued beyond 14 d, while BSMCs seeded onto unmodified BAM remained localized to the surface out to 14 d, with minimal infiltration evident only at day 28. These differences in cell infiltration support the gelatinase activity results. Increases in cell migration and matrix proteolysis in the presence of HA may be contributing factors toward BAM remodeling leading to increased matrix contraction with time. The model ECM developed in this work will be utilized for future studies aimed at elucidating the mechanisms controlling key remodeling events associated with bladder repair. Matrix contraction of cell-seeded BAM scaffolds.
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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 | 0.001 | 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".