Development of a unique crosslinked glycosaminoglycan for soft tissue repair: Treatment of interstitial cystitis/bladder pain syndrome
Bibliographic record
Abstract
Chemical modification of naturally derived glycosaminoglycans (GAGs) expands their potential utility for applications in soft tissue repair and regenerative medicine. Here we report the preparation of a novel crosslinked chondroitin sulfate (~200 to 2000 kilodaltons) that is both soluble in aqueous solution and microfilterable. We refer to these materials as "SuperGAGs." One can further conjugate these materials with diverse capture agents to further modify polymer properties and add new capabilities. A representative material (GLX-100) demonstrated durable restoration of bladder impermeability in a gold standard animal model of Interstitial Cystitis/Bladder Pain Syndrome (IC/BPS). Histologic examination of the animal bladders treated with a GLX-100 SuperGAG conjugated to biotin as a reporter demonstrated that the residence time of GLX-100 is superior to chondroitin sulfate (a product that is currently used for clinical treatment of patients with IC/BPS). As expected, this novel crosslinked GAG biopolymer was restricted to the luminal surface of the bladder wall. In this communication we describe a simple and versatile synthesis of a crosslinked glycosaminoglycan (GAG) biopolymer for soft tissue repair. Chondroitin sulfate (~12 kD) was crosslinked to form a water soluble and microfilterable polymer with approximately 200 to 2000 kD molecular weight. The synthesis presented here allows for control of molecular weight while avoiding formation of an extended block gel. Moreover, the procedure enables further chemical modification of the SuperGAG through the selection of a capture agent. A set of agents have been used, demonstrating the preparation of a family of SuperGAGs with diverse capabilities. We can optimize polymer properties, adjust adherence to various tissues, add reporters, and engage the biochemistry of surrounding tissues with peptides and other bioactives.
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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".