Gender‐related differences in advanced glycation endproducts and oxidative stress markers in rats
Bibliographic record
Abstract
A blood pressure-associated increase in MG-induced AGEs including CEL and CML in the kidney of SHR has been shown. In the present study, gender-related changes in AGEs and NOS were investigated in SD rats and SHRsp. The systolic blood pressure of SHRsp was significantly higher than that of SD rats. Male SD rats had more intense kidney staining for CEL than female SD rats. Both male and female SHRsp had more marked CEL and CML staining localized to kidney tubules, as opposed to SD rats. Nuclei containing NF-êB p65 and activated macrophages were seen in the kidney from SHRsp, not so much in SD rats, localized to renal tubules in male and glomerular vessels in female SHRsp. Higher protein level of NF-êB p65 was found in SHRsp than in SD rats. SD rats had more intense kidney nNOS staining than SHRsp. Intensity of iNOS staining was significantly higher in SHRsp than in SD rats with no gender differences in either strain. SHRsp and male rats exhibit higher AGEs and oxidative stress than SD and female rats, respectively. These differences might partly account for development of hypertension in SHRsp and higher vulnerability of male animals to renal pathology. (Supported by CIHR&HSFC)
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 | 0.001 | 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) | 0.002 | 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".