Effect of magnesium sulfate and thyroxine on inflammatory markers in a rat model of hypothyroidism
Bibliographic record
Abstract
Inflammation is a major risk factor for cardiovascular complications. Magnesium sulfate (MgSO4) has anti-inflammatory actions. Therefore we investigated the effects of levothyroxine and MgSO4 on inflammatory markers as C-reactive protein (CRP), interleukin-6, tumor necrosis factor-α (TNF-α), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) in hypothyroid rats. Sixty male rats were divided into 6 groups; normal, normal + MgSO4, hypothyroidism, hypothyroidism + levothyroxine, hypothyroidism + MgSO4, and hypothyroidism + levothyroxine + MgSO4. Thyroxine, triiodothyronine, and thyroid-stimulating hormone (TSH), CRP, interleukin-6, TNF-α, ICAM-1, and VCAM-1 were measured in all rats. Hypothyroidism significantly increased TSH, CRP, interleukin-6, TNF-α, ICAM-1, and VCAM-1 and decreased triiodothronine and thyroxine. Treatment of hypothyroid rats with levothyroxine or MgSO4 significantly decreased CRP, interleukin-6, TNF-α, ICAM-1, and VCAM-1. Combined therapy of hypothyroid rats with levothyroxine and MgSO4 significantly decreased CRP, interleukin-6, TNF-α, ICAM-1, and VCAM-1 compared with hypothyroid rats either untreated or treated with levothyroxine or MgSO4. This study demonstrates that hypothyroid rats have chronic low grade inflammation, which may account for increased risk of cardiovascular diseases. Combined levothyroxine and MgSO4 is better than levothyroxine or MgSO4 alone in alleviating the chronic low grade inflammatory status and therefore reducing the risk of cardiovascular diseases in hypothyroid animals.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".