Phosphorylation decreases trypsin activation and apolipoprotein AI binding to glycosylphosphatidylinositol-specific phospholipase D
Bibliographic record
Abstract
Glycosylphosphatidylinositol-specific phospholipase D (GPI-PLD) is present in plasma as an apolipoprotein and as a cell-associated lipase. GPI-PLD mRNA levels are regulated, but it is unclear if posttranslational mechanisms also regulate GPI-PLD function. We examined the effect of protein kinase A phosphorylation on human serum GPI-PLD activity, trypsin activation, and apolipoprotein AI binding. Protein kinase A phosphorylation did not activate GPI-PLD activity in vitro, nor did phosphorylated GPI-PLD cleave a GPI-anchored protein from intact porcine erythrocytes. Trypsin cleaves the C-terminal beta propeller of purified human serum GPI-PLD to generate three immunodetectable fragments (75, 28, and 18 kDa) in association with a 12-fold increase in enzyme activity. After phosphorylation, the amounts of 28- and 18-kDa fragments were markedly decreased with trypsin treatment, and activity was only increased five-fold. Phosphorylation also inhibits binding of GPI-PLD to apolipoprotein AI. These data are the first demonstrating that phosphorylation may regulate GPI-PLD interaction with other proteins.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".