Tissue-Specific Modulation of Spexin Expression in Diet-Induced Obese Male Rats: Comparative Effects of Aerobic Exercise and Metformin
Bibliographic record
Abstract
Obesity, a major global health concern, is associated with systemic metabolic dysregulation. Spexin, a peptide implicated in appetite control and energy balance, may represent a biomarker and therapeutic target in obesity management. This study aimed to investigate tissue-specific modulation of spexin expression in obese male rats subjected to aerobic exercise and/or metformin treatment. Thirty-six Sprague–Dawley rats were randomly assigned to six groups (n = 6 per group): (i) control, (ii) obese control, (iii) exercise, (iv) metformin, (v) metformin + exercise, and (vi) a decapitation baseline group. Obesity was induced via a 12-week high-calorie diet. Subsequently, interventions were applied over 4 weeks: treadmill running (30 min/day, 5 days/week) and/or metformin (150 mg/kg/day). Post-intervention, body weight significantly decreased in intervention groups (p < 0.001) exercise (−13.7%), metformin (−14.6%), and metformin + exercise (−21.1%) compared to the obese control group. ELISA revealed tissue-specific effects on spexin expression. In skeletal muscle, spexin levels were highest in controls (628 ± 160.5 pg/mL), with a significant reduction in the metformin + exercise group (349 ± 84.7 pg/mL; p = 0.003, Cohen’s d = 2.17). In the liver, the control group showed the highest expression (443 ± 240.8 pg/mL), while metformin + exercise yielded the lowest (254 ± 20.4 pg/mL). In contrast, heart tissue maintained elevated spexin levels across all intervention groups, with the metformin + exercise group nearly matching control levels (617 ± 25.2 vs. 618 ± 53.2 pg/mL). Immunohistochemistry confirmed these patterns, with the highest cardiac histoscore in the metformin + exercise group (2.34 ± 0.09). Hierarchical clustering underscored distinct tissue-specific expression patterns, separating muscle from liver and heart. Collectively, these findings suggest that spexin is differentially regulated by exercise and metformin, with joint effects and complex, tissue-specific modulation. This highlights spexin’s potential as a biomarker and therapeutic target in precision obesity interventions.
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) | 0.001 | 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) | 0.002 | 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".