Adipocyte Angptl8 deletion improves glucose and energy metabolism and obesity associated inflammation in mice
Bibliographic record
Abstract
Angiopoietin-like protein 8 (Angptl8), expressed in the liver and adipocytes, forms a complex with Angptl3 or Angptl4, which regulates lipoprotein lipase and triglyceride metabolism. However, the precise functions of adipocyte Angptl8 remain elusive. Here we report that adipocyte-specific inducible Angptl8-knockout (AT-A8-KO) male mice on normal diet showed minor phenotypic changes, but after a high-fat high fructose (HFHF) diet, exhibited decreased body weight gain and glycemia, elevated rectal temperature and early dark phase energy expenditure compared to the Cre controls. AT-A8-KO mice also displayed improved glucose tolerance, a trend for better insulin sensitivity, improved insulin-stimulated glucose uptake in adipose tissues, and reduced visceral adipose tissue crown-like structures, plasma MCP-1 and leptin levels. The results indicate the importance of adipose Angptl8 in the context of nutri-stress and obesity, as its deletion in mice promotes a metabolically healthy obese phenotype by slightly ameliorating obesity, improving glucose and energy homeostasis, and mitigating inflammation.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".