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Record W4413955063 · doi:10.1096/fj.202501859r

The Pathophysiological Functions of Heparanases: From Evolution, Structural and Tissue‐Specific Perspectives

2025· review· en· W4413955063 on OpenAlexafffund
Elham Vahdatahar, Clément Daviaud, Rachel Havret, Claire Debarnot, Laure Favot, Jean‐François Jégou, Ingrid Fruitier‐Arnaudin, Antoine Dufour, Romain R. Vivès, Franck Morel, Yves Bourne, Kévin Baranger

Bibliographic record

VenueThe FASEB Journal · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProteoglycans and glycosaminoglycans research
Canadian institutionsAlberta Bone and Joint Health Institute
FundersNatural Sciences and Engineering Research Council of CanadaUniversité de PoitiersFrench Infrastructure for Integrated Structural BiologyLa Rochelle UniversitéCampus FranceConseil Régional AquitaineLigue Contre le CancerAgence Nationale de la RechercheCentre National de la Recherche ScientifiqueAix-Marseille Université
KeywordsHeparanaseComputational biologyBiologyPathophysiologyBioinformaticsMedicineHeparan sulfateBiochemistryCellPathology

Abstract

fetched live from OpenAlex

Heparanase 1 (HPSE1) is a unique endoglycosidase responsible for the enzymatic cleavage of heparan sulfate, thereby playing important functions in cancer processes. In contrast, the structurally related Heparanase 2 (HPSE2) lacks catalytic activity and appears to counteract HPSE1 activities. However, contradictory observations in various pathologies highlight the need for a better understanding of the respective contributions of both heparanases. In this review, we provide a comprehensive resource about the biology of HPSE1 and HPSE2 based on findings from different mouse models, with an emphasis on immune cells and their involvement in skin pathophysiology. In addition, we explore the evolutionary relationships between the two heparanases and describe the structure-function of HPSE2 using the advanced protein-prediction tool AlphaFold 3 (AF3). These approaches unveil new insights for deciphering the functional molecular determinants that distinguish HPSE1 from HPSE2.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.021
GPT teacher head0.314
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueThe FASEB JournalSame topicProteoglycans and glycosaminoglycans researchFrench-language works237,207