Processing of Macromolecular Heparin by Heparanase
Bibliographic record
Abstract
Heparanase is an endo-glucuronidase expressed in a variety of tissues and cells that selectively cleaves extracellular and cell-surface heparan sulfate. Here we propose that this enzyme is involved also in the processing of serglycin heparin proteoglycan in mouse mast cells. In this process, newly synthesized heparin chains (60-100 kDa) are degraded to fragments (10-20 kDa) similar in size to commercially available heparin (Jacobsson, K. G., and Lindahl, U. (1987) Biochem. J. 246, 409-415). A fraction of these fragments contains the specific pentasaccharide sequence required for high affinity binding to antithrombin implicated with anticoagulant activity. Rat skin heparin, which escapes processing in vivo, was used as a substrate in reaction with recombinant human heparanase. An incubation product of commercial heparin size retained the specific pentasaccharide sequence, although oligosaccharides (3-4 kDa) containing this sequence could be degraded by the same enzyme. Commercial heparin was found to be a powerful inhibitor (I50 approximately 20 nM expressed as disaccharide unit, approximately 0.7 nM polysaccharide) of heparanase action toward antithrombin-binding oligosaccharides. Cells derived from a serglycin-processing mouse mastocytoma expressed a protein highly similar to other mammalian heparanases. These findings strongly suggest that the intracellular processing of the heparin proteoglycan polysaccharide chains is catalyzed by heparanase, which primarily cleaves target structures distinct from the antithrombin-binding sequence.
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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 | 0.001 |
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".