Preservation of Heart Function in Diabetic Rats by the Combined Effects of Muscle Cell Implantation and Insulin Therapy
Bibliographic record
Abstract
BACKGROUND: Diabetic cardiomyopathy is a common cause of heart failure in diabetic patients, but current treatments do not directly improve ventricular function. Cell transplantation can prevent cardiac dilatation after injury, and may also prevent congestive heart failure in diabetic cardiomyopathy. AIM: This study evaluated the functional effects of smooth muscle cells (SMCs) implanted into the myocardium of insulin- and non insulin-treated diabetic rats. METHODS: Four weeks after streptozotocin infusion, adult Wistar rats were implanted with BrdU-labelled SMCs or culture media (N=12/group). Six rats in each group were also treated with insulin. Echocardiograms were performed at 0, 4 and 8 weeks after streptozotocin injection, and histology and heart function were evaluated at 4 weeks after implantation. RESULTS: Blood glucose levels decreased after insulin treatment. Among cell-injected rats, histology indicated that those that did not receive insulin retained fewer surviving BrdU+ SMCs, and a smaller volume of myocardial tissue positive for alpha-smooth muscle actin. Cardiac function was preserved in the insulin-treated groups relative to those that did not receive insulin. Among insulin-treated rats, the cell-injected group functioned better than the media-injected group. CONCLUSIONS: Diabetic cardiomyopathy is partially treatable with insulin; however, a combination of SMC transplantation and insulin treatment produced the best functional result. Cell transplantation may prevent the progression of diabetic cardiomyopathy in patients whose glucose levels are controlled with insulin.
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) | 0.001 | 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 | 0.001 |
| 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".