Degradation of apolipoprotein B-100 by lysosomal cysteine cathepsins
Bibliographic record
Abstract
Although the degradation of cellular or endocytosed proteins comprises the normal function of lysosomal proteinases, these enzymes were also detected extracellularly during diseases such as atherosclerosis. Since lysosomal cysteine cathepsins were demonstrated to transform native LDL particles into a proatherogenic type, the following study was undertaken to characterize the modification of LDL particles and the degradation of apolipoprotein B-100 in more detail. LDL was incubated with cathepsins B, F, K, L, S, and V at pH 5.5 and under physiological conditions (pH 7.4) for 2 h to mimic conditions of limited proteolysis. Gel electrophoretic analysis of the degradation products revealed that cathepsin-mediated proteolysis of apolipoprotein B-100 is a fast process carried out by all enzymes at pH 5.5, and by cathepsin S also at pH 7.4. Electron microscopic analysis showed that cathepsin-mediated degradation of apolipoprotein B-100 rendered LDL particles fusion-competent compared to controls. N-Terminal sequencing of cathepsin cleavage fragments from apolipoprotein B-100 revealed an abundance of enzyme-specific cleavage sites located in almost all structurally and functionally essential regions. Since the cleavage sites superimpose well with results from substrate specificity studies, they might be useful for the development of cathepsin-specific inhibitors and substrates.
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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) | 0.000 | 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".