High-Intensity Interval Training Ameliorates Molecular Changes in the Hippocampus of Male Rats with the Diabetic Brain: the Role of Adiponectin
Bibliographic record
Abstract
Abstract Objectives: Alzheimer’s disease (AD) is closely related to type 2 diabetes (T2D). This study investigated the impact of High-intensity interval training (HIIT) on diabetes-induced disturbances in AD-related factors (including AMP-activated protein kinase (AMPK), Glycogen synthase kinase-3β (GSK3β), and Tau protein) in the hippocampus, with the main focus on adiponectin signaling. Methods: 40 male Wistar rats at the age of 8 weekd were randomly assigned to four groups: control (Con), type 2 diabetes (T2D), HIIT (Ex), and type 2 diabetes + HIIT (T2D+Ex). T2D was induced by high-fat diet plus a single dose of Streptozotocin (STZ). Rats in Ex and T2D+Ex groups performed eight weeks of HIIT (running at 80-95% of Vmax, 4-10 intervals). Insulin and adiponectin levels in serum and hippocampus were measured along with hippocampal expression of insulin and adiponectin receptors, AMPK, GSK3β, and Tau. Homeostasis model assessment for Insulin Resistance (HOMA-IR), Homeostasis model assessment for Insulin Resistance Beta (HOMA-β), and quantitative insulin sensitivity check index (QUICKI) were calculated to assess insulin resistance and sensitivity. Results: T2D decreased insulin and adiponectin levels in serum and hippocampus as well as the hippocampal levels of insulin and adiponectin receptors and AMKP but increased GSK3β and Tau in the hippocampus. HIIT reversed diabetes-induced impairments and consequently decreased Tau accumulation in the hippocampus of diabetic rats. HOMA-IR, HOMA-β, and QUICKI were improved in Ex and T2D+Ex groups. Conclusion: Overall, our results confirmed that T2D has undesirable effects on the levels of some Alzheimer's-related factors in the hippocampus and HIIT could ameliorate these impairments in the hippocampus.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".