Regeneration of Insulin-Producing β Cells, Reduction in Inflammation and Oxidation Stress, and Improvement in Lipid Profile in a Type 1 Diabetes Rat Model by Intraperitoneal Injection of the Growth Factors-Rich Catfish Skin-Derived Fraction-B: An Introductory Report
Bibliographic record
Abstract
Type 1 diabetes (T1D) results from the autoimmune destruction of insulin-producing β-cells. The regeneration of durable insulin-producing β-cells remains a critical challenge. This study investigated the regenerative potential of Fraction-B (FB), a catfish skin-derived preparation rich in growth factors, in a T1D rat model to regenerate active β-cells. Sprague Dawley rats with T1D caused by streptozotocin injection received daily intraperitoneal injections of FB for 8 weeks. FB treatment significantly reduced blood glucose to a level close to that of normal control animals, increased serum insulin and C-peptide, and restored pancreatic insulin content. Histopathological and immunohistochemical analyses confirmed the regeneration of insulin-producing β-cells in pancreatic islets. FB treatment also improved diabetes-related health issues through a reduction in inflammation and oxidative stress, and an improvement in lipid profiles without toxicity or side effects. The regenerated β-cells remained functional for 48 weeks without the use of immunosuppressants, until the animals were sacrificed. These findings suggest FB treatment to be a promising procedure for translational research into T1D treatment.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".