Temporal Dystrophic Remodeling within the Intrinsic Cardiac Nervous System of the Streptozotocin Diabetic Rat Model
Bibliographic record
Abstract
There is significant evixdence to support the existence of “diabetic cardiomyopathy,” described as heart failure (HF) in diabetic individuals in the absence of obstructive coronary disease and hypertension. The underlying pathogenesis is only partially understood, but alterations in the autonomic nervous system’s (ANS) control of cardiac function have been implicated. An important component of the cardiac ANS is the intrinsic cardiac nervous system (ICNS). The ICNS behaves as a neuronal modulator of cardiac function, and has been called the “little brain on the heart”. While there have been several investigations into the effects of diabetes on extracardiac neurons, little is known about the alterations that occur in the ICNS. It is proposed that high glucose concentrations induce toxicity via oxidative stress, resulting in neuronal dystrophy and dysfunction. Our first aim was therefore to confirm that a process of dystrophic remodeling occurs within the ICNS of diabetic hearts. Our second aim was to examine the role of oxidative stress in the pathogenesis of neuronal dystrophy. Our preliminary data indicated that neuronal dystrophy occurs in the ICNS neurons of streptozotocin (STZ)-diabetic rats, and accumulates temporally within the disease process. It was also determined that an increase in reactive oxygen species (ROS) occurs in the neuronal processes of diabetic rats, indicating an association between oxidative stress and the development of a dystrophy. While our preliminary work provides novel insight for diabetes and cardiac research, more investigations are needed to further examine neuronal dysfunction and cell death, and to prove a causative role for oxidative stress in the development of dystrophy.
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) | 0.000 | 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".