Porcine bladder acellular matrix porosity: Impact of hyaluronic acid and lyophilization
Bibliographic record
Abstract
Bladder acellular matrix (ACM) is being investigated as a urinary bladder replacement scaffold. We have demonstrated that ACM is porous and theorized that this contributes to ACM fibrosis and contracture over time in vivo and may preclude uptake and retention of molecules, which may aid cellular repopulation. We sought to determine if hyaluronic acid (HA) would decrease ACM porosity. Porcine ACM was lyophilized and rehydrated in HA (SIGMA) to form the hybrid HA-ACM construct. Three groups (n = 15/group: HA-ACM, ACM, and lyophilized/rehydrated ACM) were tested for porosity to a 10 cm column of distilled water, measuring the effluent hourly for 3 h. A porosity index was determined as the total effluent divided by time and area (cc/cm2 hr). Alcian blue staining and fluorophore-assisted carbohydrate electrophoresis qualitatively and quantitatively confirmed the uptake of HA. HA-ACM and lyophilized/rehydrated ACM were significantly less porous to water than untreated ACM [mean (+/-SE): 0.09 (+/-0.02), 0.74 (+/-0.4), and 9.8 (+/-1.6) cc/cm2 hr, respectively; Mann Whitney p < 0.0001 (HA) and p < 0.0001 (lyo)]. The difference between HA-ACM and lyophilized ACM was also statistically significant (p = 0.014). ACM hybridization with HA decreases ACM porosity, in part because of ACM lyophilization during the hybridization process. In future applications, HA may function as a carrier for smaller molecules such as growth factors, and as a bioactive molecule to improve wound healing and decrease fibrosis in tissue-engineered bladder constructs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 teacher head, 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".