Genes on Rat Chromosomes 3, 5, 10, and 16 Are Linked With Facets of Metabolic Syndrome
Bibliographic record
Abstract
WOKW (Wistar Ottawa Karlsburg W) rats develop metabolic syndrome closely resembling human disorder. In crossing studies between disease-prone WOKW and disease-resistant DA (Dark Agouti) rats, several quantitative trait loci (QTLs) were mapped. To prove the in vivo relevance of QTLs, congenic DA.WOKW rats, briefly termed DA.3aW, DA.3bW, DA.5W, DA.10W, and DA.16W, were generated by transferring chromosomal regions of WOKW chromosomes 3, 5, 10, and 16 onto DA genetic background. Male (n=12) and female (n=12) rats of each congenic strain and their parental strain DA were characterized for adiposity index (AI), serum leptin, and serum insulin as well as serum cholesterol and serum triglycerides as single facets of metabolic syndrome at the age of 30 weeks. The data showed a significant higher AI for male and female DA.3aW and female DA.16W compared with DA. Serum leptin was significantly elevated in male and female DA.3aW, DA.10W, and DA.16W rats in comparison with DA. Rats of both sexes of DA.10W and female DA.16W showed significantly elevated serum insulin in comparison to DA. Female rats of all congenics had significantly higher serum cholesterol compared with DA, while males did not differ. Finally, triglycerides were only elevated in male DA.16W. The results demonstrate an involvement of WOKW chromosomes 3, 5, 10, and 16 in developing facets of the metabolic syndrome.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".