Hepatic functions of GLP-1 and its based drugs: current disputes and perspectives
Bibliographic record
Abstract
GLP-1 and its based drugs possess extrapancreatic metabolic functions, including that in the liver. These direct hepatic metabolic functions explain their therapeutic efficiency for subjects with insulin resistance. The direct hepatic functions could be mediated by previously assumed "degradation" products of GLP-1 without involving canonic GLP-1R. Although GLP-1 analogs were created as therapeutic incretins, extrapancreatic functions of these drugs, as well as native GLP-1, have been broadly recognized. Among them, the hepatic functions are particularly important. Postprandial GLP-1 release contributes to insulin secretion, which represses hepatic glucose production. This indirect effect of GLP-1 is known as the gut-pancreas-liver axis. Great efforts have been made to determine whether GLP-1 and its analogs possess direct metabolic effects on the liver, as the determination of the existence of direct hepatic effects may advance the therapeutic theory and clinical practice on subjects with insulin resistance. Furthermore, recent investigations on the metabolic beneficial effects of previously assumed "degradation" products of GLP-1 in the liver and elsewhere, including GLP-128-36 and GLP-132-36, have drawn intensive attention. Such investigations may further improve the development and the usage of GLP-1-based drugs. Here, we have reviewed the current advancement and the existing controversies on the exploration of direct hepatic functions of GLP-1 and presented our perspectives that the direct hepatic metabolic effects of GLP-1 could be a GLP-1 receptor-independent event involving Wnt signaling pathway activation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".