Immunochemical Study of Epidermal Growth Factor in Rats with Mercuric Chloride-Induced Acute Renal Failure
Bibliographic record
Abstract
Urine contains high concentrations of epidermal growth factor (EGF), and EGF is a potent growth promoter for proximal tubular cells. In the present study, urinary and whole-kidney EGF levels were investigated in rats with mercuric chloride (HgCl2)-induced acute renal failure (ARF) using a specific radioimmunoassay for rat EGF to clarify changes in EGF after toxic injury. Male Wistar rats were given HgCl2 (2 mg/kg, subcutaneously) or saline. Serum urea nitrogen and creatinine levels were measured for 4 days after toxin administration. Forty-eight hours after toxic injury, urinary immunoreactive EGF levels in HgCl2-treated rats decreased significantly compared with control rats (1.62 +/- 0.15 versus 3.78 +/- 0.21 ng/mg creatinine; p < 0.01). Urinary immunoreactive EGF was at its lowest level 96 h after toxic injury (0.64 +/- 0.06 ng/mg creatinine; p < 0.001). Twenty-four hours after toxic injury, renal immunoreactive EGF levels increased significantly compared with control rats (22.04 +/- 2.12 versus 4.84 +/- 0.70 ng/g wet weight tissue; p < 0.001), and the increase persisted for as long as 48 h (13.36 +/- 1.61 ng/g wet weight tissue; p < 0.05). In summary, urinary immunoreactive EGF levels decreased and renal EGF levels increased in rats with HgCl2-induced ARF. These findings suggest that there is an impairment in the excretion of EGF in rats with HgCl2-induced ARF and that local paracrine production of EGF continues in ARF.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".