Angiopoietin-like proteins 3, 4 and 8: regulating lipid metabolism and providing new hope for metabolic syndrome
Bibliographic record
Abstract
Angiopoietin-like proteins (ANGPTLs) are a group of eight proteins that share structural similarity to the members of the angiopoietin protein family. ANGPTL3 plays a vital role in the regulation of the plasma levels of triglyceride and cholesterol, mainly via reversible inhibition of the lipoprotein lipase activity. ANGPTL4, which functions as a homo-oligomer different from ANGPTL3 and ANGPTL8, not only regulates the plasma levels of triglyceride and prevents the uptake of dietary lipids into adipose tissues but also inhibits intravascular lipolysis. ANGPTL8 (also called betatrophin) has been identified as an important factor in regulating the triglyceride levels and adipose tissue mass as well as in replenishing the adipose tissue triglyceride store. ANGPTL8 acts together with ANGPTL3 to regulate the lipid metabolism, and ANGPTL8 promotes cleavage of ANGPTL3 to augment the activity of ANGPTL3. In addition, ANGPTL8 promotes proliferation of pancreatic β-cells and enhances insulin secretion. The properties of ANGPTLs in regulating the lipid metabolism suggest their application in the target therapy for metabolic syndrome. As ANGPTLs are regulated by several factors and may be involved in certain specific pathways of lipid metabolism, designing drugs that target ANGPTLs or factors regulating ANGPTLs may be an efficient approach to treat metabolic syndrome.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".