Resorufin Butyrate as a Soluble and Monomeric High-Throughput Substrate for a Triglyceride Lipase
Bibliographic record
Abstract
Triglyceride lipases such as lipoprotein lipase, endothelial lipase, and hepatic lipase play key roles in controlling the levels of plasma lipoprotein. Accordingly, small-molecule modulation of these species could alter patient lipid profiles with corresponding health effects. Screening of these enzymes for small-molecule therapeutics has historically involved the use of lipid-based particles to mimic native substrates. However, particle-based artifacts can complicate the discovery of therapeutic molecules. As a simplifying solution, the authors sought to develop an approach involving a soluble and monomeric lipase substrate. Using purified bovine lipoprotein lipase as a model system, they show that the hydrolysis of resorufin butyrate can be fluorescently monitored to give a robust assay (Z' > 0.8). Critically, using parallel approaches, they show that resorufin butyrate is soluble and monomeric under assay conditions. The presented assay should be useful as a simple and inexpensive primary or secondary screen for the discovery of therapeutic lipase modulators.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".