The cardiac neural stem cell phenotype is compromised in streptozotocin‐induced diabetic cardiomyopathy
Bibliographic record
Abstract
Neural stem cells were identified in the rat heart and during scar formation and healing participated in sympathetic fiber sprouting and angiogenesis. In the setting of diabetes, impaired wound healing represents a typical pathological feature. These findings provided the impetus to test the hypothesis that experimental diabetes adversely influenced the phenotype of cardiac neural stem cells. Streptozotocin (STZ)-induced diabetic rats were associated with elevated plasma glucose levels, significant loss of body weight and left ventricular contractile dysfunction. In the heart of STZ-diabetic rats, the density of nestin immunoreactive processes emanating from cardiac neural stem cells were reduced. The latter finding was reaffirmed as nestin protein expression was significantly decreased in the heart of STZ-diabetic rats and associated with a concomitant reduction of nestin mRNA. Employing the TUNEL assay, the loss of nestin expression in STZ-diabetic rats was not attributed to widespread cardiac neural stem cell apoptosis. Insulin administration to STZ-diabetic rats with established hyperglycaemia led to a modest recovery of nestin protein expression in cardiac neural stem cells. By contrast, the administration of insulin immediately after STZ injection improved plasma glucose levels and significantly attenuated the loss of nestin protein expression. These data highlight the novel observation that nestin protein expression in cardiac neural stem cells was significantly reduced in STZ-induced type I diabetic rats. The aberrant cardiac neural stem cell phenotype may compromise their biological role and predispose the diabetic heart to maladaptive healing following ischemic injury.
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 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 | 0.000 | 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) | 0.000 | 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".