The polygenetically inherited metabolic syndrome of male WOKW rats is associated with enhanced autophagy in adipose tissue
Bibliographic record
Abstract
BACKGROUND: Recent studies revealed that autophagy is up-regulated in obese individuals, as evidenced by increased expression of autophagy related genes. As argued elsewhere, it is possible that initially insulin resistance functions as an adaptive mechanism to increase autophagy in order to protect cells against death. We have shown that Wistar Ottawa Karlsburg W (RT1(u)) rats (WOKW) develop a metabolic syndrome with insulin resistance in adipose tissue, closely resembling the human disease. Therefore, the aim of this study was to characterize the autophagy phenotype in WOKW rats to clarify the interrelation between insulin resistance and autophagy in adipose tissue. METHODS: Subcutaneous and epidydimal adipose tissue samples of 5-months-old WOKW and healthy LEW.1 W male rats were investigated and protein levels (Western blot and immunhistochemistry) of key autophagy genes, including Atg5, Atg7, LC3-II/LC3-I and apoptosis marker cleaved caspase-3 were analyzed. RESULTS: WOKW rats displayed a significant increase of autophagy related proteins (Atg5, Atg7) in adipose tissue compared with LEW.1 W. This increase was predominantly found in epididymal adipose tissue. Furthermore, the LC3-II/LC3-I ratio as a marker of autophagosomes was significantly up-regulated in subcutaneous adipose tissue of WOKW rats. Cleaved caspase-3 was just slightly detectable in visceral adipose tissue and not detected in subcutaneous fat. CONCLUSION: Insulin resistance in adipose tissue of obese WOKW rats is associated with up-regulation of differing autophagy markers in visceral and subcutaneous fat depots. This fact not only qualifies the WOKW rat for further detailed analysis of genetic determinants of metabolic syndrome but also highlights its suitability for autophagy research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".