Assessing Arrhythmia Risk in Diabetic and Ischemic-preconditioned Rat Hearts
Bibliographic record
Abstract
The purpose of this study is to understand the extent of protection against arrhythmia that Streptozotocin (STZ) induced diabetes and ischemic-preconditioning (IPC) on Sprague-Dawley rat hearts subjected to ischemia-reperfusion injury. Hearts were extracted and perfused using the langendorff method with aerated Krebs Henseleit solution. ECG recordings were recoded as the hearts were subjected to 35 minute baseline, 30 minute of no flow (ischemia) followed by 1 hour of reperfusion. The four groups investigated were vehicle control, Streptozotocin (STZ) induced diabetic rats (65mg/kg STZ), ischemic preconditioned hearts (IPC) that were subjected to two 3 minute ischemic intervals followed by 5 and 10 minute reperfusion intervals respectively), and finally diabetic hearts that underwent ischemic preconditioning (STZ+IPC). The time elapsed during ischemia until all ventricular activation stops for control hearts is 7.1±0.8 minutes, while STZ, IPC, and IPC + STZ are 15.5± 3.7, 8.6± 0.9 and 9.9± 1.6 minutes respectively. The STZ group was significantly different from the control group. When the time spent by each heart in the normal sinus rhythm state was analyzed during the 60-minute reperfusion period, control animals maintained normal rhythm for 20.9±9 minutes while STZ, IPC, and IPC + STZ maintained 29.6± 12.4, 31.7± 10.2, and 40.94+ 9.6 minutes respectively. Furthermore, the time spent in ventricular fibrillation (VF) was analyzed, and the IPC+STZ group spent 0.24± 0.2 minutes while control hearts spent 11.28± 9.2 minutes in VF. The data suggests a trend of improved arrhythmia protection when treated with STZ, IPC, or both. The IPC+STZ group is potentially displaying an additive cardioprotective effect.
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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) | 0.000 | 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 | 0.001 |
| 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".