Preventive roles of swimming exercise and pioglitazone treatment on hepatic dysfunction in a rat model of metabolic syndrome
Bibliographic record
Abstract
Pioglitazone (Pio) and swimming exercise (SE) are insulin sensitisers. This investigation was suggested because of the significant side effects associated with Pio treatment in metabolic syndrome (MetS). This study was, therefore, designed to investigate the preventive role of Pio treatment and SE in terms of efficiency and pathological changes in MetS in a rat model. Sixty male Sprague-Dawley rats were distributed equally among 6 groups: (i) control group (C), (ii) exercised control group (C+E), (iii) Pio-treated control group (C+Pio), (iv) group with MetS, (v) group with MetS treated with Pio (MetS+Pio), and (vi) exercised MetS group (MetS+E). Systolic blood pressure and heart rate were measured at the end of the experiments (16 weeks). Retro-orbital blood samples were used to determine the serum levels of glucose, insulin, lipids, gamma glutamyl transferase, alanine transaminase, aspartate transaminase, alkaline phosphatase, fetuin-A, and adiponectin. Semiquantitative reverse transcriptase - PCR insulin gene expression assays and hepatic histopathological examination were conducted. Swimming exercise significantly improved all of the aforementioned parameters, more so than the Pio treatment. In particular, the serum hepatic enzyme levels and hepatic histopathological changes were improved compared with the MetS group. These results suggested that swimming exercise might be an alternative physiological preventive tool against hepatic dysfunction to avoid the side effects associated with Pio treatment, and this could be demonstrated in a rat model of metabolic syndrome.
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 | 0.001 | 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) | 0.001 | 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".