LYPLAL1 enzyme activity is linked to hepatic glucose metabolism
Bibliographic record
Abstract
The serine hydrolase LYPLAL1 is a poorly characterised enzyme with emerging roles in hepatic metabolism. A multitude of association studies have shown links between variants of this gene locus and metabolic conditions such as obesity and insulin resistance. However, the enzyme's function is still largely unknown. Recent biochemical studies have revealed that it may play a role in hepatic glucose metabolism and that its activity is allosterically regulated. Herein, we use a selective activity-based probe to delineate LYPLAL1's involvement in hepatic metabolism. We show that the enzyme's activity is modulated during metabolic stress, specifically pointing to a putative role in negatively regulating gluconeogenesis and upregulating glycolysis. We also determine that knock-out of the enzyme does not affect liver lipid profiles and bring forth evidence for insulin-mediated control of LYPLAL1 in HepG2 cells. Furthermore, LYPLAL1 activity appears to be largely post-translationally regulated as gene expression levels remain largely constant under insulin and glucagon treatments. Taken together these data point to an enzymatic role in regulating glucose metabolism that may be part of a feedback mechanism of signal transduction. • LYPLAL1's enzyme activity is modulated during metabolic stress. • Changes in enzyme activity imply an important role in regulating gluconeogenesis and glycolysis. • Knockout not affect liver lipid profiles suggesting signaling role. • LYPLAL1 activity appears to be largely post-translationally regulated. • LYPLAL1 appears to be part of a feedback mechanism of signal transduction.
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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) | 0.000 | 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) | 0.002 | 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".