Cardiac Inflammation after Ischemia-Reperfusion of the Kidney: Role of the Sympathetic Nervous System and the Renin-Angiotensin System
Bibliographic record
Abstract
Background/Aims: To investigate the role of the sympathetic nervous system (SNS) and reninangiotensin system (RAS) in renal ischemia/reperfusion-induced (I/R) cardiac inflammatory profile. Methods: Left kidney ischemia was induced in male C57BL/6 mice for 60 min, followed by reperfusion for 12 days, and treatment with or without atenolol, losartan, or enalapril. The expression of vimentin in kidney and atrial natriuretic factor (ANF) in the heart has been investigated by RT-PCR. In cardiac tissue, levels of 1 -adrenoreceptors, adenylyl cyclase, cyclic AMP-dependent protein kinase (PKA), noradrenaline, adrenaline (components of SNS), type 1 angiotensin II receptors (AT 1 R), angiotensinogen/Ang II and renin (components of RAS) have been measured by Western blotting and HPLC analysis. A panel of cytokines -tumour necrosis factor (TNF-a), interleukin IL-6, and interferon gamma (IFN-g) -was selected as cardiac inflammatory markers. Results: Renal vimentin mRNA levels increased by >10 times in I/R mice, indicative of kidney injury. ANF, a marker of cardiac lesion, increased after renal I/R, the values being restored to the level of Sham group after atenolol or enalapril treatment. The cardiac inflammatory profile was confirmed by the marked increase in the levels of mRNAs of TNF-a, IL-6, and IFN-g. Atenolol and losartan reversed the upregulation of TNF-a expression, whereas enalapril restored IL-6 levels to Sham levels; both atenolol and enalapril normalized
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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) | 0.001 | 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) | 0.001 | 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".