Abstract 2: Mesenchymal Stem Cell Therapy Prevented Doxorubicin Induced Cardiac Dysfunction in Diabetics Rats
Bibliographic record
Abstract
Background: It is now established that having diabetes not only increases the chances of cancer also it complicates cancer treatment therapy. Doxorubicin (DOX) is a well known anticancer drug, however the clinical use of DOX was limited due to its cardiotoxic effects. One of the major concerns with DOX therapy has been its toxicity in patients who are less robust and more prone to toxic side effects, particularly patients with comorbid diseases such as diabetes mellitus. Several studies have demonstrated that mesenchymal stem cell (MSC) therapy has the potential to restore cardiac function following DOX induced cardiac injury. However, there is no study available on the effects of MSC therapy on DOX induced cardiac dysfunction in diabetics. Methods and Results: Diabetes was induced in male Wistar rats by streptozotcin injection (STZ, 65mg/kg body weight, i.p.). After 4 weeks of STZ injection, blood glucose levels in STZ group (301.58±23.97mg/dl) were significantly greater than control group (83.51±7.91mg/dl). These diabetic rats were treated with adriamycin (2.5mg/kg body weight, i.p) 3 times/week for two weeks (AD group); or with adriamycin+bone marrow MSCs (BM-MSC; 2x106 cells, via tail vein) or with adriamycin+adipose tissue derived MSCs (AD-MSC; 2x106 cells, via tail vein). Echocardiographic measurements showed a significant decline in cardiac function (%EF) following adriamycin treatment. Both BM-MSC and AT-MSC treatment improved %EF at 4 weeks. After 4 weeks of MSC injection, hearts from all the groups were excised and subjected to retrograde Langendorff perfusion and baseline levels of left ventricular developed pressure (LVDP), maximum rate of pressure rise dp/dt max and rate pressure product (RPP) were recorded. AD treatment caused a significant decrease in LVDP, dp/dt max and RPP levels. Both BM-MSCs and AD-MSCs injection significantly improved all these parameters. Conclusion: Both BM-MSC and AT-MSC were equally effective in preventing deterioration of cardiac function following doxorubicin therapy in diabetic rats. Furthermore, these findings should act as a stimulus for further research on the benefits of MSC therapy for diabetic subjects suffering from cancer.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".