Transcriptome-based identification of pro- and antioxidative gene expression in kidney cortex of nitric oxide-depleted rats
Bibliographic record
Abstract
Nitric oxide (NO) depletion in rats induces severe endothelial dysfunction within 4 days. Subsequently, hypertension and renal injury develop, which are ameliorated by alpha-tocopherol (VitE) cotreatment. The hypothesis of the present study was that NO synthase (NOS) inhibition induces a renal cortical antioxidative transcriptional response and invokes pro-oxidative and proinflammatory gene expression due to elimination of dampening effects of NO and enhanced oxidative stress. Male Sprague-Dawley rats received NOS inhibitor N(omega)-nitro-l-arginine (l-NNA, 500 mg/l water) for 4 (4d-LNNA), 21 (21d-LNNA), or 21 days with VitE in chow (0.7 g/kg body wt/day). Renal cortical RNA was applied to oligonucleotide rat arrays. In 4d-LNNA, 21d-LNNA, and 21d-LNNA+VitE, 120, 320, and 184 genes were differentially expressed, respectively. Genes related to glutathione and bilirubin synthesis were suppressed during 4d and 21d-LNNA and not corrected by VitE. Proteinuria, tubulointerstitial macrophages, and heme-oxygenase-1 (HO-1) expression were strongly correlated. Remarkably, pro-oxidative genes were not induced. Inflammation- and injury-related genes, including kidney injury molecule-1 and osteopontin, were unchanged at day 4, induced at 21d, and partly corrected by VitE. Superimposing HO-1 inhibition on NOS inhibition had no impact on the development of hypertension. To summarize, renal expression of genes involved in synthesis of the antioxidants glutathione and bilirubin seemed directly NO dependent, but there were no direct effects of NO depletion on pro-oxidant systems. This indicates that renal transcriptional regulation of two defense systems, glutathione and bilirubin syntheses, seems to depend upon adequate NO synthesis. Interaction between NO synthesis and heme degradation pathways for blood pressure regulation was not found.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".