Glycoprotein biosynthesis in porcine aortic endothelial cells and changes in the apoptotic cell population
Bibliographic record
Abstract
Porcine aortic endothelial cells (PAECs) produce glycoproteins with important biological functions, such as the control of cell adhesion, blood clotting, blood pressure, the immune system, and apoptosis. Cell surface glycoproteins play important roles in these biological activities. To understand the control of cell surface glycosylation, we elucidated biosynthetic pathways leading to N- and O-glycans in PAECs. Based on the enzyme activities, PAECs should be rich in complex biantennary N-glycans. In addition, the enzymes synthesizing complex O-glycans with core 1 and 2 structures are present in PAECs. The first enzyme of the O-glycosylation pathway, polypeptide GalNAc-transferase, was particularly active. Its specificity toward synthetic peptide substrates was found to be similar to that of purified bovine colostrum enzyme T1. A significant fraction of PAECs treated with tumour necrosis factor alpha or human serum detached from the culture plate, and most of these cells were apoptotic. The apoptotic cell population exhibited decreased core 2 beta 6-GlcNAc-transferase activity. In contrast, the activities of core 1 beta 3-Gal-transferase, which synthesizes O-glycan core 1, and of alpha 3-sialyltransferase (O), which sialylates core 1, were increased in apoptotic PAECs. Thus, apoptotic PAECs are predicted to have fewer complex O-glycans and a higher proportion of short, sialylated core 1 chains.
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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) | 0.001 | 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".