Two Heparanase Splicing Variants with Distinct Properties Are Necessary in Early Xenopus Development
Bibliographic record
Abstract
Heparanase is an endoglycosidase that cleaves heparan sulfate (HS) side chains from heparan sulfate proteoglycans (HSPGs) present in extracellular matrix and cell membranes. Although HSPGs have many functions during development, little is known of the role of the enzyme that degrades HS, heparanase. We cloned and characterized the expression of two heparanase splicing variants from Xenopus laevis and studied their function in early embryonic development. The heparanase gene (termed xHpa) spans over 15 kb and consists of at least 12 exons. The long heparanase (XHpaL) cDNA encodes a 531-amino acid protein, whereas the short splicing variant (XHpaS) results in a protein with the same open reading frame but missing 58 amino acids as a consequence of a skipped exon 4. Comparative studies of both isoforms using heterologous expression systems showed: 1) XHpaL is enzymatically active, whereas XHpaS is not; 2) XHpaL and XHpaS interact with heparin and HS; 3) both proteins traffic through the endoplasmic reticulum and Golgi apparatus, but XHpaL is secreted into the medium, whereas XHpaS remains associated with the membrane as a consequence of the loss of three glycosylation sites; 4) overexpression of XHpaS but not XHpaL increases cell adhesion of glioma cells to HS-coated surfaces; 5) XHpaL and XHpaS mRNA and protein levels vary as development progresses; 6) specific antisense knock-down of both XHpaL and XHpaS, but not XHpaL alone, results in failure of embryogenesis to proceed. Interestingly, rescue experiments suggest that the two heparanases regulate the same developmental processes, but via different mechanisms.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".