Metformin attenuates lead‐induced inflammatory and apoptotic lung injury through modulation of P53 and TNF‐α pathways in rats
Bibliographic record
Abstract
Exposure to heavy metals, such as Lead (Pb) is a matter of growing concern and potential risk factor for developing inflammatory lung diseases. The aim of this study was to a) investigate the protective effect of metformin against Pb‐induced lung injury in rat and b) investigate the underlying mechanisms specifically the role of oxidative stress, inflammation and apoptosis. For this purpose, twenty‐four adult male Wistar albino rats weighing about 230 gm were randomly distributed into six study groups of four rats each. The first group received normal saline (0.5 ml/kg/day) for 6 consecutive days and served as a a Control. The second group received metformin (500 mg/kg) for 6 consecutive days. The third and fourth groups received a single dose of normal saline (0.5 ml/kg/day) for 3 consecutive days followed by lead nitrate (Pb) (25 and 50 mg/kg, i.p.) for 3 consecutive days, respectively. The fifth and sixth groups received metformin (500 mg/kg) for 3 consecutive days followed by Pb 25 and 50 mg/kg, i.p. plus metformin 500 mg/kg for additional 3 consecutive days, respectively. One day after the last dose, animals were a and blood samples were collected via cardiac puncture for determination the levels of Pb. Rats lung tissues were excised and processed for histopathological examination, determination the levels of mRNA and protein expression of target genes, Analysis of apoptosis and TNF‐α production were determined by flow cytometer. Our results showed that exposure to Pb caused induction of inflammatory cells infiltration, cell apoptosis, modulation of genes involving in inflammation and oxidation, induction of p53 and TNF‐α were demonstrated in Pb‐induced lung injury. Administration of metformin 500 mg/kg for 6 days resulted in a protective effect on the Pb‐induced inflammatory lung injury through induction of the expression levels of NQO1, SOD, HO‐1, and p53 genes. In addition, metformin treatment significantly reduced the production of TNF‐α and expression of IL‐6 while induced the expression of IL‐10 in Pb‐treated groups. In conclusion, these observations suggest that metformin processes anti‐inflammatory, antiapoptotic and the induction of antioxidants properties against Pb‐induced lung injuries.
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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 | 0.000 |
| 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".